| Literature DB >> 30052052 |
İrfan Kösesoy1, Murat Gök1, Cemil Öz2.
Abstract
Recently, the number of the amino acid sequences shared in online databases is growing rapidly in huge amounts. By using sequence-derived features, machine learning algorithms are successfully applied to prediction of protein functional classes, protein-protein interactions, subcellular location, and peptides of specific properties in many studies. Protein Sequence Encoding System (PROSES) is a web server designed as freely and easily accessible for all researchers who want to use computational methods on protein sequence data. That is, PROSES provides users to encode their protein sequences easily without writing any programming code.Entities:
Keywords: feature extraction; machine learning; protein encoding; protein–protein interactions
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Year: 2018 PMID: 30052052 DOI: 10.1089/cmb.2018.0049
Source DB: PubMed Journal: J Comput Biol ISSN: 1066-5277 Impact factor: 1.479