An Iterative Statistical Approach to The Identification of Protein Phosphorylation Motifs from Large Scale Data Sets  

Oleh:

Schwartz, Daniel ; Gygi, Steven P.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Nature Biotechnology: The Science and Business of Biotechnology vol. 23 no. 11 (Nov. 2005), page 1391-1398.
Topik: PROTEIN; iterative statistical; protein phosphorylation; large scale data sets

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: NN9.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

With the recent exponential increase in protein phosphoylation sites identified by mass spectrometry, a unique opportunity has arisen to understand the motifs surrounding such sites. Here we present an algorithm designed to extract motifs from large data sets of naturally occuring phosphorylation motifs from recently published serine, threonine and tyrosine phosphorylation studies. When applied to a linguistic data set to test the versatility of the approach, the algorithm successfully extracted hundreds of language motifs. This method, in addition to shedding light on the consensus sequences or identified and as yet unidentified kinases and modular protein domains, may also eventually be used as a tool to determine potential phosphorylation sites in proteins of interest.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali