Computational classification of classically secreted proteins

Eric W Klee, Carlos P. Sosa

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

The ability to identify classically secreted proteins is an important component of targeted therapeutic studies and the discovery of circulating biomarkers. Here, we review some of the most recent programs available for the in silico prediction of secretory proteins, the performance of which is benchmarked with an independent set of annotated human proteins. The description of these programs and the results of this benchmarking provide insights into the most recently developed prediction programs, which will enable investigators to make more informed decisions about which program best addresses their research needs.

Original languageEnglish (US)
Pages (from-to)234-240
Number of pages7
JournalDrug Discovery Today
Volume12
Issue number5-6
DOIs
StatePublished - Mar 2007

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Benchmarking
Proteins
Program Development
Computer Simulation
Biomarkers
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Research
Therapeutics

ASJC Scopus subject areas

  • Drug Discovery
  • Pharmacology

Cite this

Computational classification of classically secreted proteins. / Klee, Eric W; Sosa, Carlos P.

In: Drug Discovery Today, Vol. 12, No. 5-6, 03.2007, p. 234-240.

Research output: Contribution to journalArticle

Klee, Eric W ; Sosa, Carlos P. / Computational classification of classically secreted proteins. In: Drug Discovery Today. 2007 ; Vol. 12, No. 5-6. pp. 234-240.
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