New choices in commercially available DNA-sequencing platforms has resulted in a flurry of activity which has energized the sequencing community and, more than ever before, encouraged new interest in the field. The once thought elusive goal of “The $1000 Genome” is rapidly becoming a reality. However, each next generation sequencing platform best lends itself to specific sequencing goals. Cambridge Healthtech Institute’s Exploring Next Generation Sequencing offers an unparalleled opportunity to compare and contrast these next generation sequencing platforms to best suit your research needs.
Tech-nol-o-gy (těk-nől'o-jé) n., pl.-gies (the application of science, especially to industrial or commercial objectives)
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TECHnology Platform EXPO
Explore available next generation screening platforms as presented by sequencing leaders. An unparalleled opportunity to compare and contrast these next generation sequencing platforms to best suit your research needs.
Why Length Matters in Next Generation Sequencing
Michael Egholm, Ph.D., Vice President of R&D, 454 Life Sciences, A Roche Company
SOLiD- Sequencing by Stepwise Ligation Platform
Applied Bio/Agencourt (invited)
Helicos BioSciences (invited)
Clonal Single Molecule ArrayTM Technology Platform
Sequencing is Dead. Long Live Sequencing!
Kevin Ulmer, Ph.D., C.E.O., Really Tiny Stuff, Inc.
Genome Resequencing for Mutation Screening
Genetic Testing for Cancer Predisposition: Opportunities Offered by Next Generation Sequencing
Alexander Gutin, Ph.D., Senior Vice President, Bioinformatics, Myriad Genetics, Inc
Toward a Non-Coding RNA Revolution in the Cancer Society
George A. Calin, M.D., Ph.D., Associate Professor, Experimental Therapeutics & Cancer Genetics, University of Texas, MD Anderson Cancer Center
Consensus Coding Sequences of Human Breast and Colorectal Cancers
Will Parsons, Ph.D., Johns Hopkins University
Deep Genomic Analysis of Tumors for the Discovery of Sequence Variation: From the Surgical Suite to the Genome Sequencer
Raphael Bueno, M.D., Division of Thoracic Surgery, Brigham and Women's Hospital (tentative)
Structural Variation Analysis
High-Resolution Analysis of Structural Variation in the Human Genome
Lars Feuk, Senior Research Associate, Center for Applied Genomics, Hospital for Sick Children, Toronto
Charting and Sequencing Structural Variation Using High-Resolution Paired-End Mapping (HR-PEM)
Jan Korbel, Postdoctoral Fellow, Molecular Biophysics and Biochemistry Department, Yale University
Identification of Complex DNA Variants in a Single Human
Samuel Levy, Ph.D., Senior Scientist, Human Genomic Medicine, J. Craig Venter Institute
Next-Next Generation Sequencing Technologies
Real-Time DNA Sequencing
Susan H. Hardin, Ph.D., President and CEO, VisiGen Biotechnologies, Inc.
Low Cost Instrument for Next Generation Sequencing by Synthesis
Steven Gordon, M.D., Ph.D., CEO, Intelligent Bio-Systems, Inc.
Polony Multiplex Analysis of Gene Expression (PMAGE) and Mouse Hypertrophic Cardiomyopathy
Jonathan Seidman, Ph.D., Professor, Department of Genetics, Harvard Medical School
Deep Sequence Analysis of Clinically Relevant env Region Sequence Variants from HIV
Ian James, Ph.D., Associate Director, Pfizer Corporation (tentative)
Deep Sequence of HIV RT Regions in Search of Drug Resistance Mutations in Patients Undergoing RT Inhibitor Treatment
E. Randall Lanier, Research Scientist, GlaxoSmithKline
Sensitive Detection of Somatic Mutations Using Deep Sequencing and ARMS Allele Specific PCR
Neil Gibson, Ph.D., Team Leader, R&D Genetics, AstraZeneca Pharmaceuticals
Software Tools for Polymorphism Discovery in Next-Generation Sequencer Data
Gabor Marth, Assistant Professor, Biology, Boston College
Whole-Genome Sequencing and Assembly with High-Throughput, Short-Read Technologies
Andreas Sundquist, Stanford University
Preceded by: Third Annual
Quantitative PCR, Microarrays, and Biological Validation
Capturing the Complete Biological Story
October 15-17, 2007
Renaissance Providence Hotel, Providence, RI
- Gene expression profiling continues as the predominant tool to identify markers associated with disease or therapy targets:
- Gene expression data is prone to variance from experiment to experiment, lab to lab, platform to platform
- Gene expression data must be validated with independent quantitative analysis tools
Biological research is costly - both in time and resources - making the careful design and validation of gene expression experiments to generate useful data for diagnostics, target identification, screening, and genotyping applications critical. All researchers are still confronted with difficult questions after completing any expression profiling experiment - how to validate and standardize the data that has been generated. Learn from seasoned and savvy researchers capturing the complete biological story at Cambridge Healthtech Institute's Third Annual Quantitative PCR, Microarrays, and Biological Validation.
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