Computational methods for metagenomic analysis

דובר:
איתי שקד, הרצאה סמינריונית לדוקטורט
תאריך:
יום רביעי, 3.2.2010, 12:00
מקום:
חדר 4 (1st floor), טאוב
מנחה:
Assoc. Prof. Oded Beja and Assoc. Prof. Ron Pinter

Metagenomics is a new field in which genetic material is extracted directly from the environment and is subsequently analyzed by a variety of biological and computational methods. Metagenomics makes it possible to study microbial communities directly from the environment and also to study microbial species that cannot be cultivated in the laboratory. Metagenomic data usually consists of many short (100-1,000 bp) DNA sequences, potentially originating from all organisms living in the examined environment. Several computational challenges arise as a result, some of them are known from genomics while others are unique to metagenomics. In this talk I will describe methods developed by me for analyzing metagenomic data, methods that concern two aspects of metagenomics analysis: (i) the statistics of functional analysis of metagenomes, and (ii) the study of genes and gene sets from metagenomic data. The viewpoint of functional analysis is global: given a metagenome, we are interested in profiling the functional capabilities of the microbial community as a whole, which may hint us as for the most important factors in the examined environment. Gene and gene sets analysis, on the other hand, takes a "local" view: in this case we are interested in answering focused questions concerning specific genes or systems. Application of the methods to real data will also be described.

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