An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies

Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind.

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Bibliographische Detailangaben
Hauptverfasser: Mazin, Pavel V. (VerfasserIn) , Gelfand, Mikhail S. (VerfasserIn) , Mironov, Andrey A. (VerfasserIn) , Rakhmaninova, Aleksandra B. (VerfasserIn) , Rubinov, Anatoly R. (VerfasserIn) , Russell, Robert B. (VerfasserIn) , Kalinina, Olga V. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 15 July 2010
In: Algorithms for molecular biology
Year: 2010, Jahrgang: 5, Heft: 1, Pages: 1-12
ISSN:1748-7188
DOI:10.1186/1748-7188-5-29
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/1748-7188-5-29
Volltext
Verfasserangaben:Pavel V Mazin, Mikhail S Gelfand, Andrey A Mironov, Aleksandra B Rakhmaninova, Anatoly R Rubinov, Robert B Russell, Olga V Kalinina
Beschreibung
Zusammenfassung:Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind.
Beschreibung:Gesehen am 30.03.2023
Beschreibung:Online Resource
ISSN:1748-7188
DOI:10.1186/1748-7188-5-29