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Nucleic Acids Research 2005 33(Database Issue):D556-D561; doi:10.1093/nar/gki122
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Nucleic Acids Research, 2005, Vol. 33, Database issue D556-D561
© 2005, the authors
Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved

GeneTide—Terra Incognita Discovery Endeavor: a new transcriptome focused member of the GeneCards/GeneNote suite of databases

Maxim Shklar*, Liora Strichman-Almashanu, Orit Shmueli, Michael Shmoish, Marilyn Safran1 and Doron Lancet

Department of Molecular Genetics and 1 Department of Biological Services (Bioinformatics Unit), The Weizmann Institute of Science, Rehovot 76100, Israel

* To whom correspondence should be addressed. Tel: +972 8 934 3455; Fax: +972 8 934 4113; Email: maxim.shklar{at}weizmann.ac.il
Correspondence may also be addressed to Marilyn Safran. Tel: +972 8 934 3455; Fax: +972 8 934 4113; Email: marilyn.safran{at}weizmann.ac.il

Received August 2, 2004; Revised and Accepted October 21, 2004

GeneCards® is an automatically mined database of human genes that strives to create, along with its auxiliary databases—GeneLoc, GeneNote and GeneAnnot—the most inclusive resource of gene-centered information of the human genome. GeneTide, the Gene Terra Incognita Discovery Endeavor (http://genecards.weizmann.ac.il/genetide/), the newest addition to this family, is a transcriptome-focused database which aims to enhance GeneCards with additional expressed sequence tag (EST)-based genes. This is achieved by comprehensively mapping >85% of the ~5.6 million human ESTs currently available at dbEST to known genes by means of data mining and integration of genomic resources including UniGene, DoTS, AceView and in-house resources. GeneTide thus creates comprehensive links between ESTs and GeneCards genes. Furthermore, groups of unassociated transcripts serve as a basis for defining novel EST-based GeneCards Candidates (EGCs). These EGCs, nearly 25 000 of which were defined in version 0.3 of GeneTide, are further annotated with various parameters, including splicing evidence and expression data extracted from the GeneNote database, to determine their validity as possible de novo genes.


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