Bms 2010
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The document discusses bioinformatics and metagenomics. It provides an overview of bioinformatics, describing how it uses tools and algorithms to analyze high-throughput biological data. It then discusses metagenomics, which involves directly sequencing environmental DNA without culturing to study microbial communities. Metagenomics projects have revealed that less than 0.5% of DNA in environments represents known organisms, and it provides thousands of new gene families.
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Bms 2010
- 1. Philip E. Bourne Skaggs School of Pharmacy and Pharmaceutical Sciences [email_address] http://www.sdsc.edu/pb The BMS Bioinformatics Focus Sept 27, 2010
- 3. Bioinformatics In General Biological Experiment Data Information Knowledge Discovery Collect Characterize Compare Model Infer Sequence Structure Assembly Sub-cellular Cellular Organ Higher-life Year 90 05 Computing Power Sequencing Technology Data 1 10 100 1000 100000 95 00 E.Coli Genome C.Elegans Genome ESTs Yeast Genome Gene Chips Virus Structure Ribosome Metaboloic Pathway of E.coli Complexity Technology Brain Mapping Neuronal Modeling Cardiac Modeling Human Genome # People/Web Site (C) Copyright Phil Bourne 1998 10 6 10 2 1 10 1000000 .1 GWAS 4 th Gen Translational Medicine Meta- genomics
- 4. Consider one Bioinformatics Growth Area Pioneered by a BMS Alumni Sept 27, 2010
- 10. Example Courses http://bioinformatics.ucsd.edu/page/99/ Sept 27, 2010
- 11. Support Infrastructure San Diego Supercomputer Center California Institute for Telecommunications & Information Technology Sept 27, 2010
- 14. Rotation Projects http://bioinformatics.ucsd.edu/page/53/ Sept 27, 2010
- 17. A Reverse Engineering Approach to Drug Discovery Across Gene Families Characterize ligand binding site of primary target (Geometric Potential) Identify off-targets by ligand binding site similarity (Sequence order independent profile-profile alignment) Extract known drugs or inhibitors of the primary and/or off-targets Search for similar small molecules Dock molecules to both primary and off-targets Statistics analysis of docking score correlations … Computational Methodology Sept 27, 2010
- 19. A Systems Biology Approach to Explaining & Subsequently Minimizing Side Effects Sept 27, 2010 PNAS Submitted Strong Binding Medium Binding Weak Binding Positive Regulation Negative Regulation Positive & Negative Regulation
Hinweis der Redaktion
- Biology is undergoing a revolution in the same way that chemistry and physics did ealier this century. It happened in physics and chemistry thorugh breakthroughs in our understanding of the physical universe. It is happening in biology through a greater understanding of ourselves. As such it is likely to be even more profound since it’s impact is something to which we all relate.A large part of that understanding is coming from analysis of vast amounts of data being generated in biology. So important is this proces that it has its own name - bioinformatics. Initially played down by experiemental biologists, it is a discipline now realized as being critical to our undetsnading of biological systems. Bioinformatics was born thanks to the human genome porject. The genome project for the first time revealed the importance of computation, first for achieving the goals of the project - to have sequenced the 3 billion bases before 2005 and later for using this information effectively in medical care. This happened around 1990, a clear decade after medicine had realized the importance of computation and had spawed the discipline of medical informatics. Bioinformatics can the thought of as the distillation of raw experimental data - data which is groiwng exponentially - and initially turning it into data. That is something of recognized significance