Your browser doesn't support javascript.
loading
amPEPpy 1.0: a portable and accurate antimicrobial peptide prediction tool.
Lawrence, Travis J; Carper, Dana L; Spangler, Margaret K; Carrell, Alyssa A; Rush, Tomás A; Minter, Stephen J; Weston, David J; Labbé, Jessy L.
Afiliação
  • Lawrence TJ; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Carper DL; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Spangler MK; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Carrell AA; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Rush TA; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Minter SJ; Cryomagnetics, Inc., Oak Ridge, TN 37830, USA.
  • Weston DJ; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
  • Labbé JL; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
Bioinformatics ; 37(14): 2058-2060, 2021 08 04.
Article em En | MEDLINE | ID: mdl-33135060
ABSTRACT

SUMMARY:

Antimicrobial peptides (AMPs) are promising alternative antimicrobial agents. Currently, however, portable, user-friendly and efficient methods for predicting AMP sequences from genome-scale data are not readily available. Here we present amPEPpy, an open-source, multi-threaded command-line application for predicting AMP sequences using a random forest classifier. AVAILABILITY AND IMPLEMENTATION amPEPpy is implemented in Python 3 and is freely available through GitHub (https//github.com/tlawrence3/amPEPpy). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Genoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Genoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
...