Prosdocimi ucb cdao
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CDAO presentation. The idea of the comparative analysis ontoloty has been presented worldwide, including: NESCent (USA), IGBMC (France), UFRJ (Brazil). Providing a semantic framework for evolutionary analysis in a high-throughtput way after the next and third generation sequencing is the way to approach evolutionary-based studies into genome-wide analysis. The darwinian core of reasoning also allows CDAO to be used with other entities.
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Prosdocimi ucb cdao
- 1. Francisco Prosdocimi Brandon Chisham Enrico Pontelli Arlin Stoltzfus Julie Thompson Framework for a C omparative D ata A nalysis O ntology IGBMC Department Seminar February 2009, Strasbourg Linking Evolution and Integrative Biology
- 31. CDAO meeting August, 2009 Las cruces, New Mexico
Editor's Notes
- Talk about individual medicine, if you want, but slide is too busy
- * NJ algorithm has a number of implementations and sometimes the research simply doesn’t know which NJ-algorithm he is using at a given analysis (idiosyncrasy) When speaking about NOT-SCALABLE, I must comment about the necessity of high-throughput techniques in evolutionary analysis New problems associated to evolutionary and comparative biology
- 3.1 Family alignment: identify homologues, generate family alignment 3.2 Sequence family evolution: infer sequence family tree and detect positive selection 3.3 Modeling character evolution: kinase inhibitor sensitivities 3.4 Functional inference: identifying "functional" sites by "evolutionary trace" and related methods 3.5 Structural genomics: identifying Giardia protein targets for structural characterization 3.6 Human variation: handicapping population SNPs as potential disease alleles 3.7 Population analysis: to be determined 3.8 Molecular evolution: differences in data sets and methods in intron studies 3.9 Tree of life: whole-genome phylogeny and horizontal transfer 3.10 Phylogenetic footprinting/shadowing 3.11 Bayesian supertrees: build composite estimates of phylogeny from bipartition frequencies 3.12 Inferring a phylogenetic tree on morphological characters 3.13 Calculating support values for a phylogenetic tree inferred from morphological characters 3.14 Inferring a phylogenetic tree or supertree on multiple datasets 3.15 Determine concordance between two or more phylogenies 3.16 Determine correlation of a phylogeny with other variables 3.17 Estimate divergence times 3.18 Determine genome-wide distribution of Ks (silent site substitutions) 3.19 Tree reconciliation (orthology analysis)
- Lets suppose…
- Transformation is done by Pierres
- Go very quickly! overview
- Ontology as
- CARB, the Center for Advanced Research in Biotechnology, jointly sponsored by UMBI and NIST UMBI, the University of Maryland Biotechnology Institute NIST, the National Institute of Standards and Technology