- Tytuł:
- Prediction of signal peptides in protein sequences by neural networks
- Autorzy:
-
Plewczynski, Dariusz
Slabinski, Lukasz
Ginalski, Krzysztof
Rychlewski, Leszek - Powiązania:
- https://bibliotekanauki.pl/articles/1040738.pdf
- Data publikacji:
- 2008
- Wydawca:
- Polskie Towarzystwo Biochemiczne
- Tematy:
-
neural networks
protein database
protein sequences
signal peptides - Opis:
- We present here a neural network-based method for detection of signal peptides (abbreviation used: SP) in proteins. The method is trained on sequences of known signal peptides extracted from the Swiss-Prot protein database and is able to work separately on prokaryotic and eukaryotic proteins. A query protein is dissected into overlapping short sequence fragments, and then each fragment is analyzed with respect to the probability of it being a signal peptide and containing a cleavage site. While the accuracy of the method is comparable to that of other existing prediction tools, it provides a significantly higher speed and portability. The accuracy of cleavage site prediction reaches 73% on heterogeneous source data that contains both prokaryotic and eukaryotic sequences while the accuracy of discrimination between signal peptides and non-signal peptides is above 93% for any source dataset. As a consequence, the method can be easily applied to genome-wide datasets. The software can be downloaded freely from http://rpsp.bioinfo.pl/RPSP.tar.gz.
- Źródło:
-
Acta Biochimica Polonica; 2008, 55, 2; 261-267
0001-527X - Pojawia się w:
- Acta Biochimica Polonica
- Dostawca treści:
- Biblioteka Nauki
Artykuł