Tuesday, November 02, 2004

Harvard Medical School Division of Genetics

The definition of statistical approaches for studying genetic variation has evolved at a frightening speed. Such technologies are applied in population studies to investigate divergence and modifications over time.

The proposed research will utilize these techniques on a very refined sample to demonstrate how easily the consciousness of humans can change their own DNA. This direct application will open the door for more direct control and development of specific techniques for creating desired genetic modifications.

Brigham and Women's Division of Genetics - Sunyaev Lab: "Lab: Research Interests
We are a computational biology laboratory. We develop and apply computational methods to pursue various problems in fields of genetics, genomics and proteomics. Our main interest is to analyse the population genetic variation and the genome divergence between species with the major focus on the protein coding regions. The effect of amino acid substitutions on function and structure of proteins can be frequently understood and even predicted via comparative sequence analysis and analysis of the protein structure. We relate the above functional studies to the evolutionary process of natural selection in order to track the evolution of proteins at the molecular level. Large-scale statistical approaches are suitable to study the way new mutations, genetic drift and natural selection shape the population genetic variation and how this variation once becomes a species divergence. The results of structural and evolutionary studies can be further applied to the data on human genetic polymorphisms with the goal to understand the complex mechanisms of inheritance and most importantly the genetic basis of human multifactorial diseases.
Our future effort will be directed towards the development of methods to extract knowledge on functionality and evolution from the novel massive data on closely related genomes and population genetic variants. We are hoping to reveal epistatic interactions between allelic variants and understand their molecular basis, thus getting closer to the understanding of the interplay of genetic variants to give rise to phenotypes. We are planning to utilise the knowledge gained to study the data on genotypes of patients suffering from common complex disorders through the established collaborations with groups involved in large medical genetics research projects. "

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