Open Access04-ERD-052-Final Report
Author(s) -
Gabriela G. Loots,
I Ovcharenko,
N Collette,
Pradeep Suresh Babu,
Joe Y. Chang,
Lisa Stubbs,
Xixi Lu,
C Pennachio,
Richard M. Harland
Publication year - 2007
Language(s) - English
Resource type - Reports
DOI - 10.2172/902387
Subject(s) - data science , human genome , informatics , function (biology) , genome , genomics , human disease , multidisciplinary approach , computational biology , computer science , biology , engineering , gene , evolutionary biology , genetics , social science , sociology , electrical engineering
Generating the sequence of the human genome represents a colossal achievement for science and mankind. The technical use for the human genome project information holds great promise to cure disease, prevent bioterror threats, as well as to learn about human origins. Yet converting the sequence data into biological meaningful information has not been immediately obvious, and we are still in the preliminary stages of understanding how the genome is organized, what are the functional building blocks and how do these sequences mediate complex biological processes. The overarching goal of this program was to develop novel methods and high throughput strategies for determining the functions of ''anonymous'' human genes that are evolutionarily deeply conserved in other vertebrates. We coupled analytical tool development and computational predictions regarding gene function with novel high throughput experimental strategies and tested biological predictions in the laboratory. The tools required for comparative genomic data-mining are fundamentally the same whether they are applied to scientific studies of related microbes or the search for functions of novel human genes. For this reason the tools, conceptual framework and the coupled informatics-experimental biology paradigm we developed in this LDRD has many potential scientific applications relevant to LLNL multidisciplinary research in bio-defense, bioengineering, bionanosciences and microbial and environmental genomics