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Archive for the ‘BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceuticall R&D Informatics, Clinical Genomics, Cancer Informatics’ Category


Bioinformatics Tool Review: Genome Variant Analysis Tools

Curator: Stephen J. Williams, Ph.D.

Updated 11/15/2018

The following post will be an ongoing curation of reviews of gene variant bioinformatic software.

 

The Ensembl Variant Effect Predictor.

McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F.

Genome Biol. 2016 Jun 6;17(1):122. doi: 10.1186/s13059-016-0974-4.

Author information

1

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. wm2@ebi.ac.uk.

2

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.

3

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. fiona@ebi.ac.uk.

Abstract

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

 

Rare diseases can be difficult to diagnose due to low incidence and incomplete penetrance of implicated alleles however variant analysis of whole genome sequencing can identify underlying genetic events responsible for the disease (Nature, 2015).  However, a large cohort is required for many WGS association studies in order to produce enough statistical power for interpretation (see post and here).  To this effect major sequencing projects have been initiated worldwide including:

A more thorough curation of sequencing projects can be seen in the following post:

Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies

 

And although sequencing costs have dramatically been reduced over the years, the costs to determine the functional consequences of such variants remains high, as thorough basic research studies must be conducted to validate the interpretation of variant data with respect to the underlying disease, as only a small fraction of variants from a genome sequencing project will encode for a functional protein.  Correct annotation of sequences and variants, identification of correct corresponding reference genes or transcripts in GENCODE or RefSeq respectively offer compelling challenges to the proper identification of sequenced variants as potential functional variants.

To this effect, the authors developed the Ensembl Variant Effect Predictor (VEP), which is a software suite that performs annotations and analysis of most types of genomic variation in coding and non-coding regions of the genome.

Summary of Features

  • Annotation: VEP can annotate two broad categories of genomic variants
    • Sequence variants with specific and defined changes: indels, base substitutions, SNVs, tandem repeats
    • Larger structural variants > 50 nucleotides
  • Species and assembly/genomic database support: VEP can analyze data from any species with assembled genome sequence and annotated gene set. VEP supports chromosome assemblies such as the latest GRCh38, FASTA, as well as transcripts from RefSeq as well as user-derived sequences
  • Transcript Annotation: VEP includes a wide variety of gene and transcript related information including NCBI Gene ID, Gene Symbol, Transcript ID, NCBI RefSeq ID, exon/intron information, and cross reference to other databases such as UniProt
  • Protein Annotation: Protein-related fields include Protein ID, RefSeq ID, SwissProt, UniParc ID, reference codons and amino acids, SIFT pathogenicity score, protein domains
  • Noncoding Annotation: VEP reports variants in noncoding regions including genomic regulatory regions, intronic regions, transcription binding motifs. Data from ENCODE, BLUEPRINT, and NIH Epigenetics RoadMap are used for primary annotation.  Plugins to the Perl coding are also available to link other databases which annotate noncoding sequence features.
  • Frequency, phenotype, and citation annotation: VEP searches Ensembl databases containing a large amount of germline variant information and checks variants against the dbSNP single nucleotide polymorphism database. VEP integrates with mutational databases such as COSMIC, the Human Gene Mutation Database, and structural and copy number variants from Database of Genomic Variants.  Allele Frequencies are reported from 1000 Genomes and NHLBI and integrates with PubMed for literature annotation.  Phenotype information is from OMIM, Orphanet, GWAS and clinical information of variants from ClinVar.
  • Flexible Input and Output Formats: VEP supports input data format called “variant call format” or VCP, a standard in next-gen sequencing. VEP has the ability to process variant identifiers from other database formats.  Output formats are tab deliminated and give the user choices in presentation of results (HTML or text based)
  • Choice of user interface
    • Online tool (VEP Web): simple point and click; incorporates Instant VEP Functionality and copy and paste features. Results can be stored online in cloud storage on Ensembl.
    • VEP script: VEP is available as a downloadable PERL script (see below for link) and can process large amounts of data rapidly. This interface is powerfully flexible with the ability to integrate multiple plugins available from Ensembl and GitHub.  The ability to alter the PERL code and add plugins and code functions allows the flexibility to modify any feature of VEP.
    • VEP REST API: provides robust computational access to any programming language and returns basic variant annotation. Can make use of external plugins.

 

 

Watch Video on VES Instructional Webinar: https://youtu.be/7Fs7MHfXjWk

Watch Video on VES Web Version training on How to Analyze Your Sequence in VEP

 

 

Availability of data and materials

The dataset supporting the conclusions of this article is available from Illumina’s Platinum Genomes [93] and using the Ensembl release 75 gene set. Pre-built data sets are available for all Ensembl and Ensembl Genomes species [94]. They can also be downloaded automatically during set up whilst installing the VEP.

 

References

Large-scale discovery of novel genetic causes of developmental disorders.

Deciphering Developmental Disorders Study.

Nature2015 Mar 12;519(7542):223-8. doi: 10.1038/nature14135. PMID:25533962

Updated 11/15/2018

 

Research Points to Caution in Use of Variant Effect Prediction Bioinformatic Tools

Although we have the ability to use high throughput sequencing to identify allelic variants occurring in rare disease, correlation of these variants with the underlying disease is often difficult due to a few concerns:

  • For rare sporadic diseases, classical gene/variant association studies have proven difficult to perform (Meyts et al. 2016)
  • As Whole Exome Sequencing (WES) returns a considerable number of variants, how to differentiate the normal allelic variation found in the human population from disease-causing pathogenic alleles
  • For rare diseases, pathogenic allele frequencies are generally low

Therefore, for these rare pathogenic alleles, the use of bioinformatics tools in order to predict the resulting changes in gene function may provide insight into disease etiology when validation of these allelic changes might be experimentally difficult.

In a 2017 Genes & Immunity paper, Line Lykke Andersen and Rune Hartmann tested the reliability of various bioinformatic software to predict the functional consequence of variants of six different genes involved in interferon induction and sixteen allelic variants of the IFNLR1 gene.  These variants were found in cohorts of patients presenting with herpes simplex encephalitis (HSE). Most of the adult population is seropositive for Herpes Simplex Virus (HSV) however a minor fraction (1 in 250,000 individuals per year) of HSV infected individuals will develop HSE (Hjalmarsson et al., 2007).  It has been suggested that HSE occurs in individuals with rare primary immunodeficiencies caused by gene defects affecting innate immunity through reduced production of interferons (IFN) (Zhang et al., Lim et al.).

 

References

Meyts I, Bosch B, Bolze A, Boisson B, Itan Y, Belkadi A, et al. Exome and genome sequencing for inborn errors of immunity. J Allergy Clin Immunol. 2016;138:957–69.

Hjalmarsson A, Blomqvist P, Skoldenberg B. Herpes simplex encephalitis in Sweden, 1990-2001: incidence, morbidity, and mortality. Clin Infect Dis. 2007;45:875–80.

Zhang SY, Jouanguy E, Ugolini S, Smahi A, Elain G, Romero P, et al. TLR3 deficiency in patients with herpes simplex encephalitis. Science. 2007;317:1522–7.

Lim HK, Seppanen M, Hautala T, Ciancanelli MJ, Itan Y, Lafaille FG, et al. TLR3 deficiency in herpes simplex encephalitis: high allelic heterogeneity and recurrence risk. Neurology. 2014;83:1888–97.

 

Genes Immun. 2017 Dec 4. doi: 10.1038/s41435-017-0002-z.

Frequently used bioinformatics tools overestimate the damaging effect of allelic variants.

Andersen LL1Terczyńska-Dyla E1Mørk N2Scavenius C1Enghild JJ1Höning K3Hornung V3,4Christiansen M5,6Mogensen TH2,6Hartmann R7.

 

Abstract

We selected two sets of naturally occurring human missense allelic variants within innate immune genes. The first set represented eleven non-synonymous variants in six different genes involved in interferon (IFN) induction, present in a cohort of patients suffering from herpes simplex encephalitis (HSE) and the second set represented sixteen allelic variants of the IFNLR1 gene. We recreated the variants in vitro and tested their effect on protein function in a HEK293T cell based assay. We then used an array of 14 available bioinformatics tools to predict the effect of these variants upon protein function. To our surprise two of the most commonly used tools, CADD and SIFT, produced a high rate of false positives, whereas SNPs&GO exhibited the lowest rate of false positives in our test. As the problem in our test in general was false positive variants, inclusion of mutation significance cutoff (MSC) did not improve accuracy.

Methodology

  1. Identification of rare variants
  2. Genomes of nineteen Dutch patients with a history of HSE sequenced by WES and identification of novel HSE causing variants determined by filtering the single nucleotide polymorphisms (SNPs) that had a frequency below 1% in the NHBLI Exome Sequencing Project Exome Variant Server and the 1000 Genomes Project and were present within 204 genes involved in the immune response to HSV.
  3. Identified variants (204) manually evaluated for involvement of IFN induction based on IDBase and KEGG pathway database analysis.
  4. In-silico predictions: Variants classified by the in silico variant pathogenicity prediction programs: SIFT, Mutation Assessor, FATHMM, PROVEAN, SNAP2, PolyPhen2, PhD-SNP, SNP&GO, FATHMM-MKL, MutationTaster2, PredictSNP, Condel, MetaSNP, and CADD. Each program returned prediction scores measuring likelihood of a variant either being ‘deleterious’ or ‘neutral’. Prediction accuracy measured as

ACC = (true positive+true negative)/(true positive+true negative+false positive+false negative)

 

  1. Validation of prediction software/tools

In order to validate the predictive value of the software, HEK293T cells, deficient in IRF3, MAVS, and IKKe/TBK1, were cotransfected with the nine variants of the aforementioned genes and a luciferase reporter under control of the IFN-b promoter and luciferase activity measured as an indicator of IFN signaling function.  Western blot was performed to confirm the expression of the constructs.

 

Results

Table 2 Summary of the
bioinformatic predictions
HSE variants IFNLR1 variants Overall ACC
TN TP FN FP Total ACC TN TP FN FP Total ACC
Uniform cutoff
SIFT 4 1 0 4 9 0.56 8 1 0 7 16 0.56 0.56
Mutation assessor 6 1 0 2 9 0.78 9 1 0 6 16 0.63 0.68
FATHMM 7 1 0 1 9 0.89 0.89
PROVEAN 8 1 0 0 9 1.00 11 1 0 4 16 0.75 0.84
SNAP2 5 1 0 3 9 0.67 8 0 1 7 16 0.50 0.56
PolyPhen2 6 1 0 2 9 0.78 12 1 0 3 16 0.81 0.80
PhD-SNP 7 1 0 1 9 0.89 11 1 0 4 16 0.75 0.80
SNPs&GO 8 1 0 0 9 1.00 14 1 0 1 16 0.94 0.96
FATHMM MKL 4 1 0 4 9 0.56 13 0 1 2 16 0.81 0.72
MutationTaster2 4 0 1 4 9 0.44 14 0 1 1 16 0.88 0.72
PredictSNP 6 1 0 2 9 0.78 11 1 0 4 16 0.75 0.76
Condel 6 1 0 2 9 0.78 0.78
Meta-SNP 8 1 0 0 9 1.00 11 1 0 4 16 0.75 0.84
CADD 2 1 0 6 9 0.33 8 0 1 7 16 0.50 0.44
MSC 95% cutoff
SIFT 5 1 0 3 9 0.67 8 1 0 8 16 0.50 0.56
PolyPhen2 6 1 0 2 9 0.78 13 1 0 3 16 0.81 0.80
CADD 4 1 0 4 9 0.56 7 0 1 9 16 0.44 0.48

 

Note: TN: true negative, TP: true positive, FN: false negative, FP: false positive, ACC: accuracy

Functional testing (data obtained from reporter construct experiments) were considered as the correct outcome.

Three prediction tools (PROVEAN, SNP&GO, and MetaSNP correctly predicted the effect of all nine variants tested.

 

Other articles related to Genomics and Bioinformatics on this online Open Access Journal Include:

Finding the Genetic Links in Common Disease: Caveats of Whole Genome Sequencing Studies

 

Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes

 

US Personalized Cancer Genome Sequencing Market Outlook 2018 –

 

Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies

 

 

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Medcity Converge 2018 Philadelphia: Live Coverage @pharma_BI

Stephen J. Williams: Reporter

MedCity CONVERGE is a two-day executive summit that gathers innovative thought leaders from across all healthcare sectors to provide actionable insight on where oncology innovation is heading.

On July 11-12, 2018 in Philadelphia, MedCity CONVERGE will gather technology disruptors, payers, providers, life science companies, venture capitalists and more to discuss how AI, Big Data and Precision Medicine are changing the game in cancer. See agenda.

The conference highlights innovation and best practices across the continuum—from research to technological innovation to transformations of treatment and care delivery, and most importantly, patient empowerment—from some of the country’s most innovative healthcare organizations managing the disease.

Meaningful networking opportunities abound, with executives driving the innovation from diverse entities: leading hospital systems, medical device firms, biotech, pharma, emerging technology startups and health IT, as well as the investment community.

Day 1: Wednesday, July 11, 2018

7:30 AM

2nd Floor – Paris Foyer

Registration + Breakfast

8:15 AM–8:30 AM

Paris Ballroom

Welcome Remarks: Arundhati Parmar, VP and Editor-in-Chief, MedCity News

8:30 AM–9:15 AM

Paris Ballroom

Practical Applications of AI in Cancer

We are far from machine learning dictating clinical decision making, but AI has important niche applications in oncology. Hear from a panel of innovative startups and established life science players about how machine learning and AI can transform different aspects in healthcare, be it in patient recruitment, data analysis, drug discovery or care delivery.

Moderator: Ayan Bhattacharya, Advanced Analytics Specialist Leader, Deloitte Consulting LLP
Speakers:
Wout Brusselaers, CEO and Co-Founder, Deep 6 AI @woutbrusselaers ‏
Tufia Haddad, M.D., Chair of Breast Medical Oncology and Department of Oncology Chair of IT, Mayo Clinic
Carla Leibowitz, Head of Corporate Development, Arterys @carlaleibowitz
John Quackenbush, Ph.D., Professor and Director of the Center for Cancer Computational Biology, Dana-Farber Cancer Institute

9:15 AM–9:45 AM

Paris Ballroom

Opening Keynote: Dr. Joshua Brody, Medical Oncologist, Mount Sinai Health System

The Promise and Hype of Immunotherapy

Immunotherapy is revolutionizing oncology care across various types of cancers, but it is also necessary to sort the hype from the reality. In his keynote, Dr. Brody will delve into the history of this new therapy mode and how it has transformed the treatment of lymphoma and other diseases. He will address the hype surrounding it, why so many still don’t respond to the treatment regimen and chart the way forward—one that can lead to more elegant immunotherapy combination paths and better outcomes for patients.

Speaker:
Joshua Brody, M.D., Assistant Professor, Mount Sinai School of Medicine @joshuabrodyMD

9:45 AM–10:00 AM

Paris Foyer

Networking Break + Showcase

10:00 AM–10:45 AM

Paris Ballroom

The Davids vs. the Cancer Goliath Part 1

Startups from diagnostics, biopharma, medtech, digital health and emerging tech will have 8 minutes to articulate their visions on how they aim to tame the beast.

Start Time End Time Company
10:00 10:08 Belong.Life
10:09 10:17 Care+Wear
10:18 10:26 OncoPower
10:27 10:35 PolyAurum LLC
10:36 10:44 Seeker Health

Speakers:
Karthik Koduru, MD, Co-Founder and Chief Oncologist, OncoPower
Eliran Malki, Co-Founder and CEO, Belong.Life
Chaitenya Razdan, Co-founder and CEO, Care+Wear @_crazdan
Debra Shipley Travers, President & CEO, PolyAurum LLC @polyaurum
Sandra Shpilberg, Founder and CEO, Seeker Health @sandrashpilberg

10:45 AM–11:00 AM

Paris Foyer

Networking Break + Showcase

11:00 AM–11:45 AM

Montpellier – 3rd Floor

Breakout: Biopharma Gets Its Feet Wet in Digital Health

In the last few years, biotech and pharma companies have been leveraging digital health tools in everything from oncology trials, medication adherence to patient engagement. What are the lessons learned?

Moderator: Anthony Green, Ph.D., Vice President, Technology Commercialization Group, Ben Franklin Technology Partners
Speakers:
Derek Bowen, VP of Business Development & Strategy, Blackfynn, Inc.
Gyan Kapur, Vice President, Activate Venture Partners
Tom Kottler, Co-Founder & CEO, HealthPrize Technologies @HealthPrize

11:00 AM–11:45 AM

Paris Ballroom

Breakout: How to Scale Precision Medicine

The potential for precision medicine is real, but is limited by access to patient datasets. How are government entities, hospitals and startups bringing the promise of precision medicine to the masses of oncology patients

Moderator: Sandeep Burugupalli, Senior Manager, Real World Data Innovation, Pfizer @sandeepburug
Speakers:
Ingo ​Chakravarty, President and CEO, Navican @IngoChakravarty
Eugean Jiwanmall, Senior Research Analyst for Medical Policy & Technology Evaluation , Independence Blue Cross @IBX
Andrew Norden, M.D., Chief Medical Officer, Cota @ANordenMD
Ankur Parikh M.D, Medical Director of Precision Medicine, Cancer Treatment Centers of America @CancerCenter

11:50 AM–12:30 PM

Paris Ballroom

Fireside Chat with Michael Pellini, M.D.

Building a Precision Medicine Business from the Ground Up: An Operating and Venture Perspective

Dr. Pellini has spent more than 20 years working on the operating side of four companies, each of which has pushed the boundaries of the standard of care. He will describe his most recent experience at Foundation Medicine, at the forefront of precision medicine, and how that experience can be leveraged on the venture side, where he now evaluates new healthcare technologies.

Speaker:
Michael Pellini, M.D., Managing Partner, Section 32 and Chairman, Foundation Medicine @MichaelPellini

12:30 PM–1:30 PM

Chez Colette Restaurant – Lobby

Lunch Reception

1:30 PM–2:15 PM

Paris Ballroom

Clinical Trials 2.0

The randomized, controlled clinical trial is the gold standard, but it may be time for a new model. How can patient networks and new technology be leveraged to boost clinical trial recruitment and manage clinical trials more efficiently?

Moderator: John Reites, Chief Product Officer, Thread @johnreites
Speakers:
Andrew Chapman M.D., Chief of Cancer Services , Sidney Kimmel Cancer Center, Thomas Jefferson University Hospital
Michelle Longmire, M.D., Founder, Medable @LongmireMD
Sameek Roychowdhury MD, PhD, Medical Oncologist and Researcher, Ohio State University Comprehensive Cancer Center @OSUCCC_James

2:20 PM–3:00 PM

Paris Ballroom

CONVERGEnce on Steroids: Why Comcast and Independence Blue Cross?

This year has seen a great deal of convergence in health care.  One of the most innovative collaborations announced was that of Cable and Media giant Comcast Corporation and health plan Independence Blue Cross.  This fireside chat will explore what the joint venture is all about, the backstory of how this unlikely partnership came to be, and what it might mean for our industry.

sponsored by Independence Blue Cross

Moderator: Tom Olenzak, Managing Director Strategic Innovation Portfolio, Independence Blue Cross @IBX
Speakers:
Marc Siry, VP, Strategic Development, Comcast
Michael Vennera, SVP, Chief Information Officer, Independence Blue Cross

3:00 PM–3:15 PM

Paris Foyer

Networking Break + Showcase

3:15 PM–4:00 PM

Montpellier – 3rd Floor

Breakout: Charting the Way Forward in Gene and Cell Therapy

There is a boom underway in cell and gene therapies that are being wielded to tackle cancer and other diseases at the cellular level. FDA has approved a few drugs in the space. These innovations raise important questions about patient access, patient safety, and personalized medicine. Hear from interesting startups and experts about the future of gene therapy.

Moderator: Alaric DeArment, Senior Reporter, MedCity News
Speakers:
Amy DuRoss, CEO, Vineti
Andre Goy, M.D., Chairman and Director of John Theurer Cancer Center , Hackensack University Medical Center

3:15 PM–4:00 PM

Paris Ballroom

Breakout: What’s A Good Model for Value-Based Care in Oncology?

How do you implement a value-based care model in oncology? Medicare has created a bundled payment model in oncology and there are lessons to be learned from that and other programs. Listen to two presentations from experts in the field.

Moderator: Mahek Shah, M.D., Senior Researcher, Harvard Business School @Mahek_MD
Speakers:
Charles Saunders M.D., CEO, Integra Connect
Mari Vandenburgh, Director of Value-Based Reimbursement Operations, Highmark @Highmark

4:00 PM–4:10 PM

Paris Foyer

Networking Break + Showcase

4:10 PM–4:55 PM

Montpellier – 3rd Floor

Breakout: Trends in Oncology Investing

A panel of investors interested in therapeutics, diagnostics, digital health and emerging technology will discuss what is hot in cancer investing.

Moderator: Stephanie Baum, Director of Special Projects, MedCity News @StephLBaum
Speakers:
Karen Griffith Gryga, Chief Investment Officer, Dreamit Ventures @karengg 
Stacey Seltzer, Partner, Aisling Capital
David Shaywitz, M.D., Ph.D., Senior Partner, Takeda Ventures

4:10 PM–4:55 PM

Paris Ballroom

Breakout: What Patients Want and Need On Their Journey

Cancer patients are living with an existential threat every day. A panel of patients and experts in oncology care management will discuss what’s needed to make the journey for oncology patients a bit more bearable.

sponsored by CEO Council for Growth

Moderator: Amanda Woodworth, M.D., Director of Breast Health, Drexel University College of Medicine
Speakers:
Kezia Fitzgerald, Chief Innovation Officer & Co-Founder, CareAline® Products, LLC
Sara Hayes, Senior Director of Community Development, Health Union @SaraHayes_HU
Katrece Nolen, Cancer Survivor and Founder, Find Cancer Help @KatreceNolen
John Simpkins, Administrative DirectorService Line Director of the Cancer Center, Children’s Hospital of Philadelphia

5:00 PM–5:45 PM

Paris Ballroom

Early Diagnosis Through Predictive Biomarkers, NonInvasive Testing

Diagnosing cancer early is often the difference between survival and death. Hear from experts regarding the new and emerging technologies that form the next generation of cancer diagnostics.

Moderator: Heather Rose, Director of Licensing, Thomas Jefferson University
Speakers:
Bonnie Anderson, Chairman and CEO, Veracyte @BonnieAndDx
Kevin Hrusovsky, Founder and Chairman, Powering Precision Health @KevinHrusovsky

5:45 PM–7:00 PM

Paris Foyer

Networking Reception

Day 2: Thursday, July 12, 2018

7:30 AM

Paris Foyer

Breakfast + Registration

8:30 AM–8:40 AM

Paris Ballroom

Opening Remarks: Arundhati Parmar, VP and Editor-in-Chief, MedCity News

8:40 AM–9:25 AM

Paris Ballroom

The Davids vs. the Cancer Goliath Part 2

Startups from diagnostics, biopharma, medtech, digital health and emerging tech will have 8 minutes to articulate their visions on how they aim to tame the beast.

Start Time End Time Company
8:40 8:48 3Derm
8:49 8:57 CNS Pharmaceuticals
8:58 9:06 Cubismi
9:07 9:15 CytoSavvy
9:16 9:24 PotentiaMetrics

Speakers:
Liz Asai, CEO & Co-Founder, 3Derm Systems, Inc. @liz_asai
John M. Climaco, CEO, CNS Pharmaceuticals @cns_pharma 
John Freyhof, CEO, CytoSavvy
Robert Palmer, President & CEO, PotentiaMetrics @robertdpalmer 
Moira Schieke M.D., Founder, Cubismi, Adjunct Assistant Prof UW Madison @cubismi_inc

9:30 AM–10:15 AM

Paris Ballroom

Liquid Biopsy and Gene Testing vs. Reimbursement Hurdles

Genetic testing, whether broad-scale or single gene-testing, is being ordered by an increasing number of oncologists, but in many cases, patients are left to pay for these expensive tests themselves. How can this dynamic be shifted? What can be learned from the success stories?

Moderator: Shoshannah Roth, Assistant Director of Health Technology Assessment and Information Services , ECRI Institute @Ecri_Institute
Speakers:
Rob Dumanois, Manager – reimbursement strategy, Thermo Fisher Scientific
Eugean Jiwanmall, Senior Research Analyst for Medical Policy & Technology Evaluation , Independence Blue Cross @IBX
Michael Nall, President and Chief Executive Officer, Biocept

10:15 AM–10:25 AM

Paris Foyer

Networking Break + Showcase

10:25 AM–11:10 AM

Paris Ballroom

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Speakers:
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

11:10 AM–11:20 AM

Networking Break + Showcase

11:20 AM–12:05 PM

Paris Ballroom

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Speakers:
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

12:10 PM–12:40 PM

Paris Ballroom

Closing Keynote: Anne Stockwell, Cancer Survivor, Founder, Well Again

Finding Your Well Again
Anne Stockwell discusses her mission to help cancer survivors heal their emotional trauma and regain their balance after treatment. A multi-skilled artist as well as a three-time cancer survivor, Anne learned through experience that the emotional impact of cancer often strikes after treatment, isolating a survivor rather than lighting the way forward. Anne realized that her well-trained imagination as an artist was key to her successful reentry after cancer. Now she helps other survivors develop their own creative tools to help them find their way forward with joy.

Speaker:
Anne Stockwell, Founder and President, Well Again @annewellagain

12:40 PM–12:45 PM

Closing Remarks

 

Please follow on Twitter using the following #hashtags and @pharma_BI

#MCConverge

#cancertreatment

#healthIT

#innovation

#precisionmedicine

#healthcaremodels

#personalizedmedicine

#healthcaredata

And at the following handles:

@pharma_BI

@medcitynews

 

Please see related articles on Live Coverage of Previous Meetings on this Open Access Journal

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https://pharmaceuticalintelligence.com/press-coverage/

 

 

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Thriving at the Survival Calls during Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL

Author and Curator: Aviva Lev-Ari, PhD, RN

 

The source for the inspiration to write this curation is described in

Survival Calls during Careers in the Digital Age

https://pharmaceuticalintelligence.com/2018/06/13/survival-calls-during-careers-in-the-digital-age/

 

In this curation, I present the following concepts in three parts:

  1. Part 1: Authenticity of Careers in the Digital Age: In Focus, the BioTechnology Sector
  2. Part 2: Top 10 books to help you survive the Digital Age

  3. Part 3: A case study on Thriving at the Survival Calls during Careers in the Digital Age: Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76 

 

Part 1: Authenticity of Careers in the Digital Age: 

In Focus, the BioTechnology Sector

 

Lisa LaMotta, Senior Editor, BioPharma Dive wrote in Conference edition | June 11, 2018

Unlike that little cancer conference in Chicago last week, the BIO International convention is not about data, but about the people who make up the biopharma industry.

The meeting brings together scientists, board members, business development heads and salespeople, from the smallest virtual biotechs to the largest of pharmas. It allows executives at fledgling biotechs to sit at the same tables as major decision-makers in the industry — even if it does look a little bit like speed dating.

But it’s not just a partnering meeting.

This year’s BIO also sought to shine a light on pressing issues facing the industry. Among those tackled included elevating the discussion on gender diversity and how to bring more women to the board level; raising awareness around suicide and the need for more mental health treatments; giving a voice to patient advocacy groups; and highlighting the need for access to treatments in developing nations.

Four days of meetings and panel discussions are unlikely to move the needle for many of these challenges, but debate can be the first step toward progress.

I attended the meetings on June 4,5,6, 2018 and covered in Real Time the sessions I attended. On the link below, Tweets, Re-Tweets and Likes mirrors the feelings and the opinions of the attendees as expressed in real time using the Twitter.com platform. This BioTechnology events manifested the AUTHENTICITY of Careers in the Digital Age – An AGE like no Other, also known as, DIGITAL.

The entire event is covered on twitter.com by the following hash tag and two handles:

 

I covered the events on two tracks via two Twitter handles, each handle has its own followers:

The official LPBI Group Twitter.com account

The Aviva Lev-Ari, PhD, RN Twitter.com account

Track A:

  • Original Tweets by @Pharma_BI and by @AVIVA1950 for #BIO2018 @IAmBiotech @BIOConvention – BIO 2018, Boston, June 4-7, 2018, BCEC

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/11/original-tweets-by-pharma_bi-and-by-aviva1950-from-bio2018-iambiotech-bioconvention-bio-2018-boston-june-4-7-2018-bcec/

 

  • Reactions to Original Tweets by @Pharma_BI and by @AVIVA1950 from #BIO2018

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/12/reactions-to-original-tweets-by-pharma_bi-and-by-aviva1950-from-bio2018/

Track B:

  • Re-Tweets and Likes by @Pharma_BI and by @AVIVA1950 from #BIO2018 @IAmBiotech @BIOConvention – BIO 2018, Boston, June 4-7, 2018, BCEC

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/06/11/re-tweets-and-likes-by-pharma_bi-aviva1950-from-bio2018-iambiotech-bioconvention-bio-2018-boston-june-4-7-2018-bcec/

Part 2: Top 10 books to help you survive the digital age

From Philip K Dick’s obtuse robots to Mark O’Connell’s guide to transhumanism, novelist Julian Gough picks essential reading for a helter skelter world

Here are 10 of the books that did help me [novelist Julian Gough]: they might also help you understand, and survive, our complicated, stressful, digital age.

  1. Marshall McLuhan Unbound by Marshall McLuhan (2005)
    The visionary Canadian media analyst predicted the internet, and coined the phrase the Global Village, in the early 1960s. His dense, complex, intriguing books explore how changes in technology change us. This book presents his most important essays as 20 slim pamphlets in a handsome, profoundly physical, defiantly non-digital slipcase.
  2. Ubik by Philip K Dick (1969)
    Pure pulp SF pleasure; a deep book disguised as a dumb one. Dick shows us, not a dystopia, but a believably shabby, amusingly human future. The everyman hero, Joe Chip, wakes up and argues with his robot toaster, which refuses to toast until he sticks a coin in the slot. Joe can’t do this, because he’s broke. He then has a stand-up row with his robot front door, which won’t open, because he owes it money too … Technology changes: being human, and broke, doesn’t. Warning: Dick wrote Ubik at speed, on speed. But embedded in the pulpy prose are diamonds of imagery that will stay with you for ever.
  3. The Singularity Is Near by Ray Kurzweil (2005)
    This book is what Silicon Valley has instead of a bible. It’s a visionary work that predicts a technological transformation of the world in our lifetime. Kurzweil argues that computer intelligence will soon outperform human thought. We will then encode our minds, upload them, and become one with our technology, achieving the Singularity. At which point, the curve of technological progress starts to go straight up. Ultimately – omnipotent, no longer mortal, no longer flesh – we transform all the matter in the universe into consciousness; into us.
  4. To Be a Machine by Mark O’Connell (2017)
    This response to Kurzweil won this year’s Wellcome prize. It’s a short, punchy tour of transhumanism: the attempt to meld our minds with machines, to transcend biology and escape death. He meets some of the main players, and many on the fringes, and listens to them, quizzically. It is a deliberately, defiantly human book, operating in that very modern zone between sarcasm and irony, where humans thrive and computers crash.
  5. A Visit from the Goon Squad by Jennifer Egan (2011)
    This intricately structured, incredibly clever novel moves from the 60s right through to a future maybe 15 years from now. It steps so lightly into that future you hardly notice the transition. It has sex and drugs and rock’n’roll, solar farms, social media scams and a stunningly moving chapter written as a PowerPoint presentation. It’s a masterpiece. Life will be like this.
  6. What Technology Wants by Kevin Kelly (2010)
    Kelly argues that we scruffy biological humans are no longer driving technological progress. Instead, the technium, “the greater, global, massively interconnected system of technology vibrating around us”, is now driving its own progress, faster and faster, and we are just caught up in its slipstream. As we accelerate down the technological waterslide, there is no stopping now … Kelly’s vision of the future is scary, but it’s fun, and there is still a place for us in it.
  7. The Meme Machine by Susan Blackmore (1999)
    Blackmore expands powerfully and convincingly on Richard Dawkins’s original concept of the meme. She makes a forceful case that technology, religion, fashion, art and even our personalities are made of memes – ideas that replicate, mutate and thus evolve over time. We are their replicators (if you buy my novel, you’ve replicated its memes); but memes drive our behaviour just as we drive theirs. It’s a fascinating book that will flip your world upside down.
  8. Neuromancer by William Gibson (1984)
    In the early 1980s, Gibson watched kids leaning into the screens as they played arcade games. They wanted to be inside the machines, he realised, and they preferred the games to reality. In this novel, Gibson invented the term cyberspace; sparked the cyberpunk movement (to his chagrin); and vividly imagined the jittery, multi-screened, anxious, technological reality that his book would help call into being.
  9. You Are Not a Gadget: A Manifesto by Jaron Lanier (2010)
    Lanier, an intense, brilliant, dreadlocked artist, musician and computer scientist, helped to develop virtual reality. His influential essay Digital Maoism described early the downsides of online collective action. And he is deeply aware that design choices made by (mainly white, young, male) software engineers can shape human behaviour globally. He argues, urgently, that we need to question those choices, now, because once they are locked in, all of humanity must move along those tracks, and we may not like where they take us. Events since 2010 have proved him right. His manifesto is a passionate argument in favour of the individual voice, the individual gesture.
  10. All About Love: New Visions by bell hooks (2000)
    Not, perhaps, an immediately obvious influence on a near-future techno-thriller in which military drones chase a woman and her son through Las Vegas. But hooks’s magnificent exploration and celebration of love, first published 18 years ago, will be far more useful to us, in our alienated digital future, than the 10,000 books of technobabble published this year. All About Love is an intensely practical roadmap, from where we are now to where we could be. When Naomi and Colt find themselves on the run through a militarised American wilderness of spirit, when GPS fails them, bell hooks is their secret guide.

SOURCE

https://www.theguardian.com/books/2018/may/30/top-10-books-to-help-you-survive-the-digital-age?utm_source=esp&utm_medium=Email&utm_campaign=Bookmarks+-+Collections+2017&utm_term=277690&subid=25658468&CMP=bookmarks_collection

Part 3: A case study on Thriving at the Survival Calls during Careers in the Digital Age:  Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76

 

On June 10, 2018

 

Following, is a case study about an alumna of HUJI and UC, Berkeley as an inspirational role model. An alumna’s profile in context of dynamic careers in the digital age. It has great timeliness and relevance to graduate students, PhD level at UC Berkeley and beyond, to all other top tier universities in the US and Europe. As presented in the following curations:

Professional Self Re-Invention: From Academia to Industry – Opportunities for PhDs in the Business Sector of the Economy

https://pharmaceuticalintelligence.com/2018/05/22/professional-self-re-invention-from-academia-to-industry-opportunities-for-phds-in-the-business-sector-of-the-economy/

 

Pioneering implementations of analytics to business decision making: contributions to domain knowledge conceptualization, research design, methodology development, data modeling and statistical data analysis: Aviva Lev-Ari, UCB, PhD’83; HUJI, MA’76 

https://pharmaceuticalintelligence.com/2018/05/28/pioneering-implementations-of-analytics-to-business-decision-making-contributions-to-domain-knowledge-conceptualization-research-design-methodology-development-data-modeling-and-statistical-data-a/

 

This alumna is Editor-in-Chief of a Journal that has other 173 articles on Scientist: Career Considerations 

https://pharmaceuticalintelligence.com/category/scientist-career-considerations/

 

In a 5/22/2018 article, Ways to Pursue Science Careers in Business After a PhD by Ankita Gurao,

https://bitesizebio.com/38498/ways-to-pursue-the-business-of-science-after-a-ph-d/?utm_source=facebook&utm_medium=social&utm_campaign=SocialWarfare

Unemployment figures of PhDs by field of science are included, Ankita Gurao identifies the following four alternative careers for PhDs in the non-academic world:

  1. Science Writer/Journalist/Communicator
  2. Science Management
  3. Science Administration
  4. Science Entrepreneurship

My career, as presented in Reflections on a Four-phase Career: Aviva Lev-Ari, PhD, RN, March 2018

https://pharmaceuticalintelligence.com/2018/03/06/reflections-on-a-four-phase-career-aviva-lev-ari-phd-rn-march-2018/

has the following phases:

  • Phase 1: Research, 1973 – 1983
  • Phase 2: Corporate Applied Research in the US, 1985 – 2005
  • Phase 3: Career Reinvention in Health Care, 2005 – 2012
  • Phase 4: Electronic Scientific Publishing, 4/2012 to present

These four phases are easily mapped to the four alternative careers for PhDs in the non-academic world. One can draw parallel lines between the four career opportunities A,B,C,D, above, and each one of the four phases in my own career.

Namely, I have identified A,B,C,D as early as 1985, and pursued each of them in several institutional settings, as follows:

A. Science Writer/Journalist/Communicator – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to present 

B. Science Management – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005 and Phase 3: Career Reinvention in Health Care, 2005 – 2012 

C. Science Administration – see link above for Phase 2: Corporate Applied Research in the US, 1985 – 2005and Phase 4: Electronic Scientific Publishing, 4/2012 to present 

D. Science Entrepreneurship – see link above for Phase 4: Electronic Scientific Publishing, 4/2012 to present  

Impressions of My Days at Berkeley in Recollections: Part 1 and 2, below.

  • Recollections: Part 1 – My days at Berkeley, 9/1978 – 12/1983 –About my doctoral advisor, Allan Pred, other professors and other peers

https://pharmaceuticalintelligence.com/2018/03/15/recollections-my-days-at-berkeley-9-1978-12-1983-about-my-doctoral-advisor-allan-pred-other-professors-and-other-peer/

  • Recollections: Part 2 – “While Rolling” is preceded by “While Enrolling” Autobiographical Alumna Recollections of Berkeley – Aviva Lev-Ari, PhD’83

https://pharmaceuticalintelligence.com/2018/05/24/recollections-part-2-while-rolling-is-preceded-by-while-enrolling-autobiographical-alumna-recollections-of-berkeley-aviva-lev-ari-phd83/

The topic of Careers in the Digital Age is closely related to my profile, see chiefly: Four-phase Career, Reflections, Recollections Parts 1 & 2 and information from other biographical sources, below.

Other sources for my biography

 

Read Full Post »


Synopsis Track 7: NGS in Real Time @pharma_BI 2018 CHI’s BioIT World conference & Expo, May 15 – 17, 2018, Boston, MA – Seaport World Trade Center

http://www.bio-itworldexpo.com/

LPBI Group will cover Track 7: NGS in Real Time

@pharma_BI

@AVIVA1950

Aviva Lev-Ari, PhD, RN will be in attendance

 

 

 

 

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2018 Plenary Keynote Speakers

Mark BoguskiMark Boguski, MD, PhD
Executive Vice President and Chief Medical Officer, Liberty BioSecurity
tanya cashTanya Cashorali
Founder, TCB Analytics 
John ReyndersJohn Reynders, PhD
Vice President, Data Sciences, Genomics, and Bioinformatics, Alexion Pharmaceuticals, Inc.

 

Jerald SchindlerJerald Schindler, DrPH
Vice President, Biostatistics, Merck Research Laboratories (Retired)
Yu LihuaLihua Yu, PhD
Chief Data Science Officer, H3 Biomedicine

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TUESDAY, MAY 15

7:00 am Workshop Registration Open and Morning Coffee

 

8:00 – 11:30 Recommended Morning Pre-Conference Workshops*

W4. Introduction to Scalable and Reproducible RNA-Seq Data Processing, Analysis, and Result Reporting Using AWS, R, knitr, and LaTex

12:30 – 4:00 pm Recommended Afternoon Pre-Conference Workshops*

W13. Leveraging Cloud Technologies to Enable Large-Scale Integration of Human Genome and Clinical Outcomes Data

* Separate registration required.

2:00 – 6:30 Main Conference Registration Open

4:00 PLENARY KEYNOTE SESSION

Click here for detailed information

5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing

WEDNESDAY, MAY 16

7:00 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION

Click here for detailed information

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

LARGE-SCALE RNA-SEQ AND GENE EXPRESSION VARIABILITY

10:50 Chairperson’s Remarks

11:00 KEYNOTE PRESENTATION: RNA-Seq X: Look Back and Look Ahead

Shanrong Zhao, PhD, Director, Computational Biology and Bioinformatics, Pfizer, Inc.

Since Dr. Mortazavi published his groundbreaking research entitled “Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq” in Nature Methods in 2008, RNA-seq has evolved rapidly and revolutionized biological research, drug development and clinical diagnostics. 2018 is the 10-year anniversary of RNA-seq, and it’s the right time to look back and look forward.

11:30 LCA: A Robust and Scalable Algorithm to Reveal Subtle Diversity in Large-Scale Single-Cell RNA Sequencing Data

Xiang Chen, PhD, Assistant Member, Department of Computational Biology, St. Jude Children’s Research Hospital

We developed Latent Cellular Analysis (LCA), a machine learning based single-cell RNA sequencing (scRNA-seq) analytical pipeline that combines similarity measurement by latent cellular states and a graph based clustering algorithm featuring dual-space model search for both the optimal number of subpopulations and the informative cellular states distinguishing them. LCA has proved to be robust, accurate and powerful by comparison to multiple state-of-the-art computational methods on large-scale real and simulated scRNA-seq data.

12:00 pm Presentation to be Announced

 

12:15 RSEQREP: An Open-Source Cloud-Enabled Framework for Reproducible RNA-Seq Data Processing, Analysis & Result Reporting

Johannes Goll, Director, Bioinformatics, The Emmes Corporation

RSEQREP (RNA-Seq Reports) is a new open-source cloud-enabled framework that allows researchers to execute start-to-end RNA-Seq analysis to characterize transcriptomics changes in human cells following treatment. It outputs dynamically generated reports using R and LaTeX. We provide results for a published RNA-Seq study to characterize transcriptomics changes following influenza vaccination.

12:30 Session Break

WuXi_Nextcode_notagline12:40 Luncheon Presentation I: Querying of 100k Genomes Using Google Cloud

Hákon Gudbjartsson, PhD, Chief Informatics Officer, WuXi NextCODE

Hákon Gudbjartsson will demonstrate the power of the GOR database in real time. GORdb is used to organize, mine and share massive genome datasets, providing a global architecture for the largest precision medicine efforts worldwide. It’s designed to enable fast, computationally-efficient use of sequence data, and allows for the query and application of data in the context of reference sets.

1:10 Luncheon Presentation II (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

1:40 Session Break

OPTIMIZING GENE BASES WITH CODON USAGE

1:50 Chairperson’s Remarks

Leonard Lipovich, PhD, Associate Professor with Tenure, Center for Molecular Medicine and Genetics, Wayne State University

1:55 Analysis of Codon Optimized Therapeutic Proteins Using Ribosome Profiling

Chava Kimchi-Sarfaty, PhD, Research Chemist, Principal Investigator, OTAT Acting Deputy Associate Director for Research, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, FDA | CBER | OTAT

Codon optimization is a genetic engineering technique used to improve the yield of recombinant therapeutic proteins. Despite being used ubiquitously to increase protein expression, codon optimization requires widespread substitution of synonymous codons across the native expression sequence. This degree of genetic manipulation can carry consequences, including altered conformation of the recombinant product. These unforeseen modifications can have impacts on protein function and health outcomes, and are of high regulatory importance. To study these techniques, we have used ribosome profiling, a technique used to characterize the translation pattern of the ribosome across the mRNA transcript. In this technique, actively translating ribosomes are cross‐linked to mRNA and is followed by nuclease digestion of mRNA not protected by a ribosome, generating short mRNA fragments (called “ribosome footprints”). These fragments are sequenced and aligned to generate a differential coverage map across portions of the transcript. This technique provides insight into the relative translation efficiency in a given area of the transcript. We have analyzed the ribosome profiling data for relationships to codon usage. By identifying regions of differential ribosome profiling patterns between wild type and codon optimized transcripts, we aim to create a method of selecting regions to leave unmodified, allowing recombinant proteins to benefit from increased expression while maintaining the integrity and safety of the protein product. Codon optimization as a technique relies heavily on accurate codon usage statistics of the organism in question, to identify rare codons to be replaced with common codons for an increase in translation efficiency. However, previous databases containing this information were either outdated or limited in scope. To address this gap in knowledge, we constructed a new database containing codon usage tables for all the species in GenBank and RefSeq. We designed a program in Python to download, parse, and organize all the sequence data available in these two repositories, and in Javascript designed an accessible web portal available to the public to query the new database. The new HIVE‐CUTs database contains substantially more organisms and coding sequence data and is a dramatic improvement upon prior databases. This tool will aid in the effective implementation of codon optimization techniques and other areas of recombinant protein design.

  1. FDA approved 2011-2017 – Therapeutic Proteins by Drug Class: i.e., Oncology , Hematology
  2. Effort on Gene therapy is primarily in Cancer Disease
  3. Factor 9 and Hemophillia B
  4. Codon Optimization to increase Protein expression TECHNIQUES:
  5. Transcription
  6. mRNA
  7. Codon Usage Database – Tables open to the public -9606 (Homo Sapient)
  8. Evaluation of Codon Optimized Factor 9 – Altered Protein Structure Binding Affinity, protein folding
  9. Riboson profile: Protected Profile 20-22 or 24-27 nucleotides [PCR Sequence] Sites: A, P, E
  10. Analysis of Ribosome Profiling Data: Correlations F9 and ACTB and GAPDH – each against Codon Optimizer
  11. In Silico: translation kinetics based solely on calculated codon usage frequency
  12. CONCLUSION:
  • Ribosomal profiling data do not correlate with codon Optimization
  • Genetically engineered therapeutics – benefit from Codon Optimization

 

 

2:25 Multidimensional Global Proteogenomics Identifies Persistent Ribosomal In-Frame Mis-Translation of Stop Codons as Amino Acids in Multiple Open Reading Frames from a Human Breast Cancer Long Non-Coding RNA

Leonard Lipovich, PhD, Associate Professor with Tenure, Center for Molecular Medicine and Genetics, Wayne State University

Two-thirds of the ~60,000 human genes (www.gencodegenes.org) do not encode known proteins, and aside from long non-coding RNA (lncRNA) genes with recently characterized functions, the possibility that these poorly understood genes’ transcripts serve as de-facto unconventional messenger RNAs has not been formally excluded. Our group was the first to use direct evidence from protein mass spectrometry, preceding efforts that employed indirect evidence from ribosome profiling, to demonstrate that specific lncRNAs are recurrently and nonrandomly translated in human cells (Bánfai et al 2012, Genome Research 22:1646-1657). In our current study, we integrated RNAseq, ribosome profiling, and mass spectrometry to globally assess lncRNA translation in human estrogen receptor alpha positive MCF7 breast cancer cells. We identified 27 peptides, mapping to multiple sense-strand open reading frames (ORFs) of the lncRNA gene MMP24-AS1, united by a novel and highly unconventional property: the existence of these peptides can only be explained by stop-to-nonstop in-frame replacements of specific UAG and UGA (but not UAA) stop codons by amino acids. This result, validated by the absence of any genomic mutations, polymorphisms, and RNA editing events in genomic and cDNA targeted resequencing, represents an unprecedented apparent gene-specific violation of the Genetic Code in human breast cancer cells, and hints at a new mechanism enhancing the combinatorial complexity of the cancer proteome.
[Note 1: This work has been funded in its entirety by the NIH Director’s New Innovator Award 1DP2-CA196375 to LL.]
[Note 2: This project encompasses collaborations. A full listing of co-authors will be shown during the talk.]

  • LncRNA
  • ENCODE –
  • WG 6-frame tRanslation + mass spectrometric data {mass specriptom] = empirical redefinition of the genomic sequencing field
  • MMP24 maps – Breast Cancer
  • Mechanism: MisTranslation – Translation Infidelity: why are only UAG and UGA, never UAA, reference-genome stop codons are affected

 

2:55 CO-PRESENTATION: Workflow Optimization for NGS Discovery – How to Drive BIX Insights

Jack DiGiovanna, PhD, General Manager, NGS Applications and Services, Seven Bridges Genomics (->2009) 250 CS

Isaac M. Neuhaus, PhD, Director, Computational Genomics, Bristol Myers Squibb

  • Predict immuno-oncoogy outcomes
  • Biomarkers
  • Microsatellite Instability (MSI) – short tanden repeats of 1 to 6 base-pairs: Detections of MSI mutations in somatic variants, Profiling
  • Whole Exome gene data
  • Companion diagnostics
  • Colorectal adenocarcinomas with MSI status
  • Validating predictions
  • Tumor Heterogeneity: Clones have different potentials to metastasize
  • Heterogeneity (purity) work flow & Validation – Variant Allele Frequency
  • MSI sensor score: Benchmarking MSIsensor vs Tumor Purity
  • Clinical MSI data

 

3:25 Refreshment Break in the Exhibit Hall with Poster Viewing

NGS DATA ANALYSIS, INTEGRATION, INTERPRETATION, AND VISUALIZATION

4:00 Variant Query Tool: Drag & Drop for a Scalable, Server-Less, Web UI to Querying Annotated Variants

William Van Etten, Senior Scientific Consultant, BioTeam

It’s a challenge to build an environment that provides real-time querying of reads and annotated variants for genomics research, requiring significant human and computational resources. Whether tens or thousands of genomes, the barrier to entry can be high for the biologists/geneticist, who might not also be computer scientist. BioTeam has developed a simple tool that leverages several AWS services (S3, Athena, Lambda, Cognito, IAM, CloudWatch) to enable a biologists/geneticist to drag & drop VCF and BAM files onto an S3 bucket, then point their web browser at this bucket, to provide a scalable, server-less, web UI to querying the reads and annotated variants within these files. We aim to demonstrate, explain, and promote what we’ve learned from this proof of concept software development in the hope that others might benefit from our experience.

http://vqt.bioteam.net

  • Amazon Athena API Introduced – Variant Query Tool – Server-less

 

 4:30 Building a GXP Validated Platform for NGS Analysis Pipelines

Anthony Rowe, PhD, Business Technology Leader, R&D IT, Janssen R&D LLC

An NGS applications approach the clinic the bioinformatics pipelines used to analyze the data have to be validated to demonstrate their correctness. This talk will present Janssen approach to deploying validated NGS applications with specific focus in microbiome metagnomics.

  • IBD: UlcerativeColitis  (UC), Crohn’s DIsease (CD)
  • $11Bil – $28Billion – Cost burden in Health Care systems
  • J&J and Vedanta announced a collaboration DNAnexus 
  • Microbiome based approach for IBD: Gut Dysbiosis, beneficial microbes symbionts, Pathogenesis
  • Jeanssen developing a new platform for DIsease therapy
  • How to analyze microbiome data as drug?
  • Stelara Biotherapeutics – 27 microbes
  • PK PD of antigen therapy
  • Biotherapeutic product like VE202 –
  • Can VE202 be detected in stool
  • Real Time NGS – The Clinical Novel NSG  for Clinical Trials – Emerging Science meets Regulated Science
  • Emerging Science: Novel NGS Informatics
  • Tool Box for Microbiome: Biomathematicians carried workflow to Clinical Trials
  • Computational workflow: Step 1: alienment 1,2,3,4
  • 7 samples 4 tools: Run Time cost result quality
  • Quality Control: for Clinical NGS Platform:Manufacturing, Software QA,
  • current system Overview: sequencing Vendors prtnerships
  • Establish scientific ladscape and a structured drug development process

Sapio Sciences

 

5:00 LIMS or ELN, Which Do You Need? [Electronic Lab Notebook]

Kevin Cramer, CEO, Sapio Sciences (->2007)

Both Biotech and Pharma need Laboratory Information Management (LIMS) and Electronic Lab Notebook (ELN) capabilities. Sapio has eliminated the barriers between these two product areas by leveraging its more than decade of unique experience offering both LIMS and ELN solutions and combining the key features of each solution into one, best of breed, product: Exemplar ELN Pro.

  • Configurable data model for LIMS Platform
  • LIMS 1.0 Configure Data Model
  • LIMS 2.0 Workflow enginw for tracking complex processes
  • NGS – 2008 Celexa,
  • ELN – 2015 Exemplar support ad Hoc experimentation, clean sheet design
  1. create RQS for Samples
  2. Assign processes
  3. Track progres
  4. register Samples
  5. Register plates Aliquoting Define Storage
  6. Graphical Assignment
  7. register consumables
  • ELN: Spreadsheets, Office Integration, Drag & Drop experiment items, Curve fitting, R Stat, Charting/visualization
  • Author/witness/Reviewer/Approver Accept/reject attach instrument design
  • ELN, LIMS, ELN Pro[fessional]
  • ELN Pro: ELN plus LIMS properties
  • Exemplar ELN Pro: storage mgm

Sapio Sciences – Exemplar ELN Pro

  • Integrate collaboration,charting tools
  • global repository
  • Chemaxon Integration
  • Prebuilt NGS pipelines out of the box

 

 

5:15 Sponsored Presentation (Opportunity Available)

5:30 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing

7:00 – 10:00 Bio-IT World After Hours @Lawn on D

THURSDAY, MAY 17

7:30 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION & AWARDS PROGRAM

Click here for detailed information

9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

 

APPLICATION OF NGS TO ONCOLOGY, IMMUNOLOGY, DIAGNOSTICS, AND THERAPEUTIC DEVELOPMENT

10:30 Chairperson’s Remarks, Bruce Press, EVP Seven Bridges Genomics

10:40 Instantiating a Single Point of Truth for Genomic Reference Data

David Herzig, Scientist, Research Informatics, Roche Pharmaceuticals

This talk will exemplify how expression and mutation data were made actionable by consolidating a scattered landscape of genomic reference data into a real SPoT.

  • Common System Landscapes
  1. Data Sources
  2. Silo Solutions
  3. API
  4. Consumers: Bioinformatics, Data Science, JBrowser
  • Single Source of Truth
  1. Moving away from Silo solutions
  2. Roche Data Commons

Physical HW

File SYstem & Workflow

Single Point of Truth SSOT

Integration Data Mart

UI

All data goes into Data Storage API as input and Output from the data storage

Evaluation

  • inhouse development
  • customization of open source
  • Ensembl
  1. Genomics Reference Data manu species
  2. Multi species DB [stable ID] MySQL DB is been used
  3. API & SW: REST, Tools, Web Code
  4. Modules – Variation, Funcgen, other features CORE – genome annotation
  5. SOLUTION – 150 hours = Homo-sapiens Variation is the most time consuming Ensebl REST API Endpoints
  6. Customization: NCBI: DOwnload, Unzip data – Import data – Ensembl PERL Script goes into SPoT (SSoT)
  7. Into CORE  – only species of interestLoading Log – UPDATE META TABLE (Roche Data from BioInformatics Dept)
  8. SSOT & Arvados – 2 updates a year, 5 versions are available in parallel: Portal Page, latest version: http://genomes.roce.com:3091 http://genomes.roche.com/latest 
  9. USE CASES: Comparative Genomics

 

11:10 A Network-Based Approach to Understanding Drug Toxicity

Yue Webster, PhD, Principal Research Scientist, Informatics Capabilities, Research IT, Eli Lilly and Company

Despite investment in toxicogenomics, nonclinical safety studies are still used to predict clinical liabilities for new drug candidates. Network-based approaches for genomic analysis help overcome challenges with whole-genome transcriptional profiling using limited numbers of treatments for phenotypes of interest. Herein, we apply co-expression network analysis to safety assessment using rat liver gene expression data to define 415 modules, exhibiting unique transcriptional control, organized in a visual representation of the transcriptome. Compared to gene-level analysis alone, the network approach identifies significantly more phenotype-gene associations, including established and novel biomarkers of liver injury.

  • Phase III Clinical Trials fail due to Drug Toxicity – TXG – MAP
  • Food preservative BHA
  • antibiotic TB patient Trecator – like Tunicamycin
  • blood thinner – Ticlid
  • n-dimensional problem space for Toxicity:Gene Expression COmplexity DYnamic COmplexity, pathophysiology complexity
  • TRANSLATION: from Animal to Human Clinical Trials – Failure of Clinical Trial equals to failure of the TRANSLATION
  • Modules in DNA and RNA
  • Protein structure
  • Reduce dimensionality of the information space
  • Changes of patterns – risk assessment of the confidence in translation
  • Gene vs System-level View – Tunicamycin – image TXG – MAP = unsupervised approach to convert a table of data into ONE image
  • How to build TXG – MAP: Genotype and Phenotype – for Predictions of Untargeted Effects, recomendations
  1. Data Input
  2. Training set – DrugMatrix
  3. Algorithm – 415 co-expression module
  4. Interpretation (Gene ontology)
  • use TXG – MAP for adaptive response: Measure changes in Biological processes usinf eigengene scores
  • TXG – MAP to compare Treatments: Apoptosis post treatment with Tunicamycin Red Induced expression Green supressed expression
  • Hypetrophy caused by antibiotic Tunicamycin
  • Building TXG – MAP – for sharing with Scientific Community across species to be used in Translation Research for preservation across cell lines, across species and for translation to Humans

11:40 Michael Rusch , Dir Bioinformatics, St. Jude Cloud

  • 2017 Genomic Test is ORDERABLE >400 patients as of May 2018
  • 300 approved access requests globally – PCGP Data Sharing – 8 attempts to download have failed once
  • Solution: 2015 Cloud: Secure, sustainable, expandable
  • SW development Partner DNAnexus on Microsoft ADURE in 2017, St.Jude CLoud
  • 3000 pediatric cancer survivors – Optimize therapy to improve quality of life
  • Simple Data Access Procedure : data securely into private cloud
  • Gene fusions – Turnaround Time Challenge – Assay – 42 days – Leukemia RNA Seq workflow 15 days to get seq done
  • Cost $5-$10 per sample running 5-8 days seq, manual Review and Reporting 20 Minutes
  • most runs completed in 12 hours
  • Variant annotation, pathogenicity: Germ line Mutations and Pediatric Cancer NEJM, Journal Pediatric Oncology
  • Recan PIE – Pathogenicity Information Exchange (PIE) for SNV/Indel Classification
  • Results overview Variant page: Gene info Protein Paint, Gene ingo
  • damage prediction algorithm – ACMG classification Tool: Variant page
  • 100 Registered users
  • 425 jobs
  • 340,000 variants
  • VisualizationProtein paint, PCGP Mutation: SOmatic and Germ line Pathogenic and Likely Pathogenic Variants

https://stjude.cloud

 

11:40 Sponsored Presentation (Opportunity Available)

12:10 pm Session Break

12:20 Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing

DATA MINING FOR DISEASE CLASSIFICATION – CITYVIEW I

1:55 Chairperson’s Remarks

John Methot, Director, Health Informatics Architecture, Dana-Farber Cancer Institute

2:00 Disease Classification in the Era of Data-Intensive Medicine

Kanix Wang, PhD, Research Professional, Booth School of Business, Institute for Genomics & Systems Biology, University of Chicago

We used insurance claims for over one-third of the U.S. population to create a subset of 128,989 families (481,657 unique individuals). Using these data, we estimated the heritability and familial environmental patterns of 149 diseases. We then computed the environmental and genetic disease classifications for a set of 29 complex diseases after inferring their pairwise genetic and environmental correlations.

2:30 Enviro-Geno-Pheno State Approach and State-Based Biomarkers for Differentiation, Prognosis, Subtypes, and Staging

Lei Xu, PhD, Director, Centre for Cognitive Machines and Computational Health; Zhiyuan Chair Professor, Department of Computer Science and Engineering, Shanghai Jiao Tong University

In the joint space of geno-measures, pheno-measures, and enviro-measures, one point represents a bio-system behavior and a subset of points that locate adjacently and share a common system status represents a ‘state’. The system is characterized by such states learned from samples. This enviro-geno-pheno state is considered a biomarker, indicating ‘health/normal’ versus ‘risk/abnormal’ together with its associated enviro-geno-pheno condition.

3:00 PANEL DISCUSSION: Can We Improve Breast Cancer Patient Outcomes through Artificial Intelligence?

Maya Said, ScD, President & CEO, Outcomes4me, Inc. (Moderator)

Panelists:
Regina Barzilay, PhD, MacArthur Fellow and Delta Electronics Professor, Massachusetts Institute of Technology (MIT) Department of Electrical Engineering and Computer Science; Member, Computer Science and Artificial Intelligence Laboratory, MIT

Kevin Hughes, MD, Co-Director, Avon Breast Evaluation Program, Massachusetts General Hospital; Associate Professor of Surgery, Harvard Medical School; Medical Director, Bermuda Cancer Genetics Risk Assessment Clinic

Newly diagnosed cancer patients attempting to understand their treatment options face the overwhelming task of filtering an information deluge, much of which is irrelevant, outdated and occasionally inaccurate. Additionally, matching their diagnosis to best-in-class treatments or potential clinical trials, while simultaneously learning to navigate an extremely complex healthcare system is daunting, even for the most highly trained physicians. We will explore various platforms aimed at improving patient outcomes by leveraging technology to help educate, track, and connect patients with personalized resources while simultaneously working to improve the care continuum and the development of new treatments. We will explore the nexus of healthcare networks and their IT systems, clinical decision-making and delivery, R&D, and patients, for whom we all create our innovation solutions. Attendees will be interested to understand how various groups are working to increase value across the entire system by bringing laboratory, clinical and pharmaceutical science, real-world evidence and patient-reported data together with technology and artificial intelligence to solve health challenges. These approaches offer the opportunity to generate deeper insights into how therapies perform in the real world and harness that understanding to improve efficiency, effectiveness, value, and ultimately, patient care.

  • Targeted Therapy in Breast Cancer more than another diseases

4:00 Conference Adjourns

SOURCE

http://www.bio-itworldexpo.com/next-gen-sequencing-informatics/

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International Award for Human Genome Project

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

The Thai royal family awarded its annual prizes in Bangkok, Thailand, in late January 2018 in recognition of advances in public health and medicine – through the Prince Mahidol Award Foundation under the Royal Patronage. This foundation was established in 1992 to honor the late Prince Mahidol of Songkla, the Royal Father of His Majesty King Bhumibol Adulyadej of Thailand and the Royal Grandfather of the present King. Prince Mahidol is celebrated worldwide as the father of modern medicine and public health in Thailand.

 

The Human Genome Project has been awarded the 2017 Prince Mahidol Award for revolutionary advances in the field of medicine. The Human Genome Project was completed in 2003. It was an international, collaborative research program aimed at the complete mapping and sequencing of the human genome. Its final goal was to provide researchers with fundamental information about the human genome and powerful tools for understanding the genetic factors in human disease, paving the way for new strategies for disease diagnosis, treatment and prevention.

 

The resulting human genome sequence has provided a foundation on which researchers and clinicians now tackle increasingly complex problems, transforming the study of human biology and disease. Particularly it is satisfying that it has given the researchers the ability to begin using genomics to improve approaches for diagnosing and treating human disease thereby beginning the era of genomic medicine.

 

National Human Genome Research Institute (NHGRI) is devoted to advancing health through genome research. The institute led National Institutes of Health’s (NIH’s) contribution to the Human Genome Project, which was successfully completed in 2003 ahead of schedule and under budget. NIH, is USA’s national medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases.

 

Building on the foundation laid by the sequencing of the human genome, NHGRI’s work now encompasses a broad range of research aimed at expanding understanding of human biology and improving human health. In addition, a critical part of NHGRI’s mission continues to be the study of the ethical, legal and social implications of genome research.

 

References:

 

https://www.nih.gov/news-events/news-releases/human-genome-project-awarded-thai-2017-prince-mahidol-award-field-medicine

 

http://www.mfa.go.th/main/en/news3/6886/83875-Announcement-of-the-Prince-Mahidol-Laureates-2017.html

 

http://www.thaiembassy.org/london/en/news/7519/83884-Announcement-of-the-Prince-Mahidol-Laureates-2017.html

 

http://englishnews.thaipbs.or.th/us-human-genome-project-influenza-researchers-win-prince-mahidol-award-2017/

 

http://genomesequencing.com/the-human-genome-project-is-awarded-the-thai-2017-prince-mahidol-award-for-the-field-of-medicine-national-institutes-of-health-press-release/

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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Cracking the Genome – Inside the Race to Unlock Human DNA – quotes in newspapers

Reporter: Aviva Lev-Ari, PhD, RN

 

Cracking the Genome

SOURCE
Paperback
, 352 pages
ISBN:

9780801871405
October 2002
$29.00
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Cracking the Genome

Inside the Race to Unlock Human DNA

In 1953, James Watson and Francis Crick unveiled the double helix structure of DNA. The discovery was a profound moment in the history of science, but solving the structure of the genetic material did not reveal what the human genome sequence actually was, or what it says about who we are. Cracking the code of life would take another half a century.

In 2001, two rival teams of scientists shared the acclaim for sequencing the human genome. Kevin Davies, founding editor of Nature Genetics, has relentlessly followed the story as it unfolded week by week since the dawn of the Human Genome Project in 1990. Here, in rich human and scientific detail, is the compelling story of one of the greatest scientific feats ever accomplished: the sequencing of the human genome.

In brilliant, accessible prose, Davies captures the drama of this momentous achievement, drawing on his own genetics expertise and on interviews with the key scientists. Davies details the fraught rivalry between the public consortium, chaperoned by Francis Collins, and Celera Genomics, directed by sequencer J. Craig Venter. And in this newly updated edition, Davies sheds light on the secrets of the sequence, highlighting the myriad ways in which genomics will impact human health for the generations to come.

Cracking the Genome is the definitive, balanced account of how the code that holds the answer to the origin of life, the evolution of humanity, and the future of medicine was finally broken.

Kevin Davies is the founding editor of Nature Genetics and is currently editor-in-chief of Bio•IT World. He graduated from Oxford University and holds a Ph.D. in genetics from the University of London.

“For an up-to-the-minute account of one of the most dramatic periods in present-day science, Cracking the Genome is an essential read.”

“A superb job… A tantalizing glimpse of the ethical perils and technological possibilities awaiting humanity.”

“A rollicking good tale about an enduring intellectual monument.”

“The race is over, and Davies was there, all along, providing the running commentary—and there, too, at the finish line. In Cracking the Genome, he hands out the prizes.”

“Davies has tracked one of the most important stories ever to unfold. Davies helps readers understand how the deciphering of our genetic code will revolutionize our lives while posing serious ethical dilemmas.”

“An impressive job of contextualizing the science within a political, economic, and social framework, creating a lively tale as accessible to non—specialists as it is to scientists.”

“Investors and others looking for a quick primer on the science and business of biotechnology will find this a useful guide.”

“In Davies’ prose, this story of molecular biology and the Human Genome Project is as compelling as any Arthurian legend. In a fast-moving approachable style, Davies captures the uncovering of biology’s Holy Grail, relying on his own expertise in genetics and interviews with key players such as Collins and Venter.”

SOURCE

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