VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques.

Yadav, Arvind Kumar; Singla, Deepak

Yadav, Arvind Kumar; Singla, Deepak.

Affiliation

Yadav AK; Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Solan, Himachal Pradesh 173 234, India.

J Biosci ; 452020.

Article in En | MEDLINE | ID: mdl-32975233

Subject(s)

Plant Proteins/genetics; Proteome/genetics; Software; Support Vector Machine; Vacuoles/genetics; Viridiplantae/genetics; Benchmarking; Computational Biology/methods; Databases, Protein; Datasets as Topic; Plant Cells/metabolism; Plant Proteins/classification; Plant Proteins/metabolism; Proteome/classification; Proteome/metabolism; ROC Curve; Vacuoles/metabolism; Viridiplantae/metabolism

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Collection: 01-internacional Database: MEDLINE Main subject: Plant Proteins / Vacuoles / Software / Proteome / Viridiplantae / Support Vector Machine Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: J Biosci Year: 2020 Document type: Article Affiliation country: India

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