ProFeatX: A parallelized protein feature extraction suite for machine learning.

ABSTRACT: Machine learning algorithms have been successfully applied in proteomics, genomics and transcriptomics. and have helped the biological community to answer complex questions. However, most machine learning methods require lots of data, with every data point having the same vector size. The biological sequence data, such as proteins, are amino acid sequences of variable length, which makes it essential to extract a definite number of features from all the proteins for them to be used as input into machine learning models. There are numerous methods to achieve this, but only several tools let researchers encode their proteins using multiple schemes without having to use different programs or, in many cases, code these algorithms themselves, or even come up with new algorithms. In this work, w

SUBMITTER: Guevara-Barrientos D 

PROVIDER: S-EPMC9842958 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature