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THURSDAY, 13 OCTOBER

 

Trends and Advances 

9:30 Chairperson’s Opening Remarks

9:35 Translational Informatics in the Era of Social Computing

Yike Guo, Ph.D., Professor, Computing Science, Computing, Imperial College London

This presentation focuses on our research on developing a revolutionary collective intelligence platform for global collaboration in genomics-based translational research. This platform integrates some key technology development such as cloud computing, social network, next generation sequencing, multi-tenancy database, distributed file system, semantic web and high performance bioinformatics algorithms. The research and development of this technology will address the key issues in collective knowledge discovery and management in the scientific research community.

10:05 Next Generation Sequencing in Clinical and Translational Research - Results and Lessons Learned

Andreas Kremer, Ph.D., Department of Bioinformatics, Erasmus University Medical Center, Rotterdam

Besides in house sequencing with Illumina technology, the Erasmus MC utilizes next generation sequencing technology from Complete Genomics Inc to identify genetic variations associated with human disease at higher resolution and greater sensitivity than previously possible. The technology is a powerful tool for the diagnosis of genetic diseases (e.g. congenital malformations) as well as for the understanding cancer genesis and patient stratification. Next generation sequencing will play a role diagnostics, in understanding of complex diseases and in the future genome variations will be studies in the relation to differences in treatment response. Current next generation sequencing studies face limitations due to the depth of sequencing coverage and thus the accuracy of SNV detection which can have a high error rate. The Bioinformatics team of the Erasmus MC has built a human variome database and applications to facilitate the analysis of variants across samples (human diploid genomes). This reference can be utilized for prioritizing disease causative single nucleotide variants in genetic screens and cancer studies and to identify natural variations which are not yet described. It can also be envisaged that such a human variome database initiated in a research environment forms the basis for a clinical solution necessary for every medical center that plans to use next generation sequencing for diagnostics. Our database solution uses industry standards, guarantees privacy and will facilitate classifications of variants like benign, likely benign, pathogenic, likely pathogenic across a genome side-by-side to variants of (still) unknown significance. We will describe various analysis workflows, filters and annotation sources used and present selected examples.

10:35 Coffee Break - Networking with Sponsors

Sponsored by
Ariadne Genomics
11:00 Integrating Biological Knowledge for Decision Support

Yannick Le Piol, Ph.D., Ariadne Genomics

Drug discovery and development scientists are challenged to make fast and accurate decisions based on available facts from multiple structured and unstructured data sources. Ariadne’s Pathway Studio software provides an easy, practical solution with rapid and accurate text extraction and data integration from both multiple data sources, efficiently connecting different phases of R&D. Several applications will be discussed.

 

Featured Speaker 

Ting Chao Chou11:15 The Mass-Action Law based Algorithms for Computer Simulation and Quantitative Drug Discovery Informatics

Ting-Chao Chou, Ph.D., Director, Preclinical Pharmacology Core, Molecular Pharmacology & Chemistry Program, Memorial Sloan-Kettering Cancer Center

The mass-action law based median-effect equation is obtained via mathematical induction and deduction from over 300 equations. Its algorithm, along with its experimental design and computer simulation, allow the reduced requirement of data points for small size experimentation and yet yields useful bioinformatics. The scope of the median-effect equation encompasses single entities to multiple entities and covers 1st order to higher order dynamics, and it yields mathematical forms for four basic equations in biochemistry and biophysics. Thus, the median-effect principle enables the integration for quantitative, efficient bio-research, low cost biomedical investigations and drug discoveries and drug development. Its vast utilities points to a mass-action law based econo-green biomedical research.

12:00 Economical Prediction of Large Scale Protein Motions in Binding Drugs and Other Ligands

Samuel Flores, Ph.D., Assistant Professor, Cell and Molecular Biology, Uppsala Universit

Knowledge of the structure of proteins bound to known or potential ligands is crucial for drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods. We describe how to generate alternate conformations of proteins that move by hinge bending, the largest class of motions. We use the method to predict the conformational change required for drug and small ligand binding for several well studied proteins.

12:30 Lunch for Purchase in Exhibit Hall 9

13:45 Dedicated Poster Viewing in Exhibit Hall 9

 

Semantics-Based Science 

14:30 Chairperson’s Remarks

M. Scott Marshall, Ph.D., Co-Chair W3C Health Care and Life Sciences Interest Group, University of Amsterdam / Leiden University Medical Center

14:35 Semantic Web Approaches to Personalized Medicine

M. Scott Marshall, Ph.D., Co-Chair W3C Health Care and Life Sciences Interest Group, University of Amsterdam / Leiden University Medical Center

Beyond reducing costs by eliminating redundancy and easing data integration, a common vocabulary infrastructure will enable us to find information relevant to a particular patient based on associated data and patient attributes. Toward these ends, the W3C Health Care and Life Sciences Interest Group (HCLS IG) promotes the use of shared vocabularies and best practices by creating translational and personalized medicine demonstrations that facilitates interoperability and bridge the data of multiple disciplines, from patient to drug therapy.

15:05 Open PHACTS: An Innovative Medicines Initiative to Build a Semantics-Based Open Pharmacology Space for Drug Discovery

Carole Goble, Professor, Computer Science, University of Manchester

The Open PHACTS consortium, funded by the EU’s Innovative Medicines Initiative, aims to reduce the barriers to drug discovery by applying semantic web technologies to available data resources, creating an Open Pharmacological Space. The 22 partner consortium links: chemists with computer technologists; 8 pharmaceutical companies with bio IT companies and universities; and public data sets with commercial ones. The approach uses agile development techniques and linked data and ontologies methods from the semantic web.

Open Science 

15:35 Insilico DB: an Efficient Web-Based Platform To Search, Annotate, and Retrieve Public Genome-Wide Studies

Alain Coletta, Ph.D., U.L.B.- Université Libre de Bruxelles
David Y. Weiss Solís, Ph.D., Bioengineering, U.L.B.-Université Libre de Bruxelles

InSilico DB is a new web-based tool for fast collaborative curation and export of public genome-wide assays. InSilico DB provides the largest available collection of expert-verified genome-wide content with 105,603 assays from NCBI's GEO repository. Extensive GenePattern (GUI) and R/Bioconductor (Command-line) export integration enhances collaboration between biomedical researchers and biostatisticians.

16:05 Refreshment Break - Networking with Sponsors

 

16:30 Open Data + Open Source = Open Science

Lars Jorgensen, Senior Scientific Manager, Production Software & Sequencing Informatics, Wellcome Trust Sanger Institute

As sequencing and other DNA based technologies moves closer to the clinic the public interest in the techniques increase. Reproducibility and application of scientific results will become essential. I’ll show how openness in these areas can be used to influence the public. There will be several hands on examples from inside and outside Sanger.

17:00 ChEMBL - Open Access Data for Drug Discovery

John Overington, Team Leader, Chemogenomics, EMBL EBI Hinxton

An Open Data resource (ChEMBL - www.ebi.ac.uk/chembl) of bioactivity data will be presented. It contains in excess of 750,000 compound records, and over 3,000,000 abstracted bioactivity end-points. These can be data-mined to discover general rules of successful drugs, and used in a wide array of specific ways to support lead discovery and optimization. We will discuss recent enhancements to the resource include REST web services, and RDF forms of the data.

17:30 Close of Conference

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Hitachi Data Systems

IBM
 

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