Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Computational recognition of potassium channel sequences

Heil, B., Ludwig, J., Lichtenberg-Fraté, H., & Lengauer, T. (2006). Computational recognition of potassium channel sequences. Bioinformatics, 13, 1562-1568.

Item is

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Heil, Burkhard, Autor
Ludwig, Jost, Autor
Lichtenberg-Fraté, Hella, Autor
Lengauer, Thomas1, Autor           
Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: Motivation: Potassium channels are mainly known for their role in regulating and maintaining the membrane potential. Since this is one of the key mechanisms of signal transduction, malfunction of these potassium channels leads to a wide variety of severe diseases. Thus potassium channels are priority targets of research for new drugs, despite the fact that this protein family is highly variable and closely related to other channels, which makes it very difficult to identify new types of potassium channel sequences. Results: Here we present a new method for identifying potassium channel sequences (PSM, Property Signature Method), which—in contrast to the known methods for protein classification—is directly based on physicochemical properties of amino acids rather than on the amino acids themselves. A signature for the pore region including the selectivity filter has been created, representing the most common physicochemical properties of known potassium channels. This string enables genome-wide screening for sequences with similar features despite a very low degree of amino acid similarity within a protein family.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2007-02-202006
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: eDoc: 314422
Anderer: Local-ID: C125673F004B2D7B-2DDC20F0E256D1E8C125725F002FF200-Lengauer2006b
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Bioinformatics
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 13 Artikelnummer: - Start- / Endseite: 1562 - 1568 Identifikator: ISBN: 1367-4803