ProteinNet: a standardized data set for machine learning of protein structure

Background Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has been driven by standardized data sets that facilitate fair assessment of new me...

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Veröffentlicht in:	BMC bioinformatics Jg. 20; H. 1; S. 311 - 10
1. Verfasser:	AlQuraishi, Mohammed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 11.06.2019 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Accessibility Algorithms Amino Acid Sequence Analysis Artificial intelligence Automation Binding sites Bioinformatics Biomedical and Life Sciences CASP Co-evolution Coevolution Computational biology Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer vision Databases, Protein Datasets Deep learning Historical structures Homology Internet Learning algorithms Life Sciences Machine Learning Machine Learning and Artificial Intelligence in Bioinformatics Methods Microarrays Natural language processing Protein research Protein sequence Protein structure Protein structure prediction Proteins Proteins - chemistry Reference Standards Sequence Alignment Structure (Literature) Technology application Training United States Proteins Deep learning CASP Machine learning PSSM Database Protein sequence Protein structure prediction Co-evolution Protein structure
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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