aMLProt: an automated machine learning library for protein applications

aMLProt is available on https://github.com/etiur/aMLProt.git and https://doi.org/10.5281/zenodo.14971157; The aMLProt plugin is available via the official Horus Plugin Repository https://horus.bsc.es/repo/plugins/amlprot, and Horus itself can be freely downloaded from https://horus.bsc.es. Moreover, a demo of aMLProt can be found, without previous registration or download, at the horus.bsc.es/amlprot and horus.bsc.es/amlprot-suggest. The results and data from the pH optima regression model are available at: https://zenodo.org/records/15394097.

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Publication Details

Journal
Bioinformatics
Published
2025-09-23
DOI
https://doi.org/10.1093/bioinformatics/btaf543
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

aMLProt: an automated machine learning library for protein applications

Ruite Xiang, Albert Cañellas-Solé, Vı́ctor Guallar, Christian Domínguez-Dalmases
Bioinformatics
Advanced Proteomics Techniques and Applications
article

aMLProt: an automated machine learning library for protein applications

Ruite Xiang, Albert Cañellas-Solé, Vı́ctor Guallar, Christian Domínguez-Dalmases
article en

Abstract

aMLProt is available on https://github.com/etiur/aMLProt.git and https://doi.org/10.5281/zenodo.14971157; The aMLProt plugin is available via the official Horus Plugin Repository https://horus.bsc.es/repo/plugins/amlprot, and Horus itself can be freely downloaded from https://horus.bsc.es. Moreover, a demo of aMLProt can be found, without previous registration or download, at the horus.bsc.es/amlprot and horus.bsc.es/amlprot-suggest. The results and data from the pH optima regression model are available at: https://zenodo.org/records/15394097.

BioinformaticsVol. 41(10)
Institució Catalana de Recerca i Estudis Avançats (ES), Barcelona Supercomputing Center (ES), Universitat de Barcelona (ES), Universitat Politècnica de Catalunya (ES)
European Commission, Ministerio de Ciencia e Innovación, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España, Agencia Estatal de Investigación
Openalex Percentile: Top 76%
Advanced Proteomics Techniques and Applications
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