From ORFeome to biology: a functional genomics pipeline.

Szczegóły
Abstrakt

Tytuł:: From ORFeome to biology: a functional genomics pipeline.
Autorzy:: Wiemann S; Molecular Genome Analysis, German Cancer Research Center, 69120 Heidelberg, Germany. />Arlt D
Huber W
Wellenreuther R
Schleeger S
Mehrle A
Bechtel S
Sauermann M
Korf U
Pepperkok R
Sültmann H
Poustka A
Źródło:: Genome research [Genome Res] 2004 Oct; Vol. 14 (10B), pp. 2136-44.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Original Publication: Cold Spring Harbor, N.Y. : Cold Spring Harbor Laboratory Press, c1995-
MeSH Terms:: Databases, Genetic*
Genomics*
Protein Interaction Mapping*
Proteomics*
DNA, Complementary/*genetics
Open Reading Frames/*physiology
Animals ; Computational Biology ; Gene Expression Profiling ; Humans ; Information Storage and Retrieval ; Mice ; Oligonucleotide Array Sequence Analysis ; Subcellular Fractions
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Substance Nomenclature:: 0 (DNA, Complementary)
Entry Date(s):: Date Created: 20041019 Date Completed: 20041116 Latest Revision: 20181113
Update Code:: 20240104
PubMed Central ID:: PMC528930
DOI:: 10.1101/gr.2576704
PMID:: 15489336
: Czasopismo naukowe

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.

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