Extracting chemical reactions from text using Snorkel

Background Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these databases struggle to keep up with the exponential growth of the biomedical literature. Conventional text mining pipelines provide tools to aut...

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Veröffentlicht in:	BMC bioinformatics Jg. 21; H. 1; S. 217 - 15
Hauptverfasser:	Mallory, Emily K., de Rochemonteix, Matthieu, Ratner, Alex, Acharya, Ambika, Re, Chris, Bright, Roselie A., Altman, Russ B.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 27.05.2020 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Algorithms Annotations Bacteria Bacteria - metabolism Biochemical Phenomena Bioinformatics Biological activity Biomedical and Life Sciences Candidates Chemical reactions Computational Biology/Bioinformatics Computer Appl. in Life Sciences Construction Curation Data mining Data Mining - methods Databases, Factual Datasets Humans Labeling Language Learning algorithms Life Sciences Machine Learning Machine Learning and Artificial Intelligence in Bioinformatics Metabolism Microarrays Mining industry Natural language processing Proteins Recall Research Article Snorkel Software Text mining Training Text mining Curation Database Chemical reactions Snorkel
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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