Machine Learning Tools to Study Non-Globular proteins

ML4NGP COST Action CA21160 - Deliverable 5 “Report on state of the art ML approaches focused on different phenomena of NGPs”

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-21
DOI
https://doi.org/10.5281/zenodo.14200160
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
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article

Machine Learning Tools to Study Non-Globular proteins

Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Bioinformatics
article

Machine Learning Tools to Study Non-Globular proteins

article en

Abstract

ML4NGP COST Action CA21160 - Deliverable 5 “Report on state of the art ML approaches focused on different phenomena of NGPs”

Zenodo (CERN European Organization for Nuclear Research)
Silesian University of Technology (PL), Universitat Autònoma de Barcelona (ES), University of Padua (IT), American University of Armenia (AM), Barcelona Supercomputing Center (ES), University of Belgrade (RS), L. A. Orbeli Institute of Physiology NAS RA (AM), Institute of Biochemistry and Biophysics, Polish Academy of Sciences (PL), University of Belgrade – Faculty of Mathematics, Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 75%
Machine Learning in Bioinformatics
DOIOpen Access PDFOpenAlex
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Machine Learning Tools to Study Non-Globular proteins · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS