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Genomics
Article . 1998 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Genomics
Article . 1998
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Identification of High-Molecular-Weight Proteins with Multiple EGF-like Motifs by Motif-Trap Screening

Authors: Manabu Nakayama; Daisuke Nakajima; Naohiko Seki; Takahiro Nagase; Nobuo Nomura; Osamu Ohara;

Identification of High-Molecular-Weight Proteins with Multiple EGF-like Motifs by Motif-Trap Screening

Abstract

To identify large proteins with an EGF-like-motif in a systematic manner, we developed a computer-assisted method called motif-trap screening. The method exploits 5'-end single-pass sequence data obtained from a pool of cDNAs whose sizes exceed 5 kb. Using this screening procedure, we were able to identify five known and nine new genes for proteins with multiple EGF-like-motifs from 8000 redundant human brain cDNA clones. These new genes were found to encode a novel mammalian homologue of Drosophila fat protein, two seven-transmembrane proteins containing multiple cadherin and EGF-like motifs, two mammalian homologues of Drosophila slit protein, an unidentified LDL receptor-like protein, and three totally uncharacterized proteins. The organization of the domains in the proteins, together with their expression profiles and fine chromosomal locations, has indicated their biological significance, demonstrating that motif-trap screening is a powerful tool for the discovery of new genes that have been difficult to identify by conventional methods.

Related Organizations
Keywords

DNA, Complementary, Epidermal Growth Factor, Sequence Homology, Amino Acid, Protein Conformation, Molecular Sequence Data, Chromosome Mapping, Proteins, Sequence Analysis, DNA, Rats, Molecular Weight, Animals, Humans, Amino Acid Sequence, Cloning, Molecular

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
163
Top 10%
Top 1%
Top 1%
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