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Home PLOS Computational Biology

PLOS Computational Biology

Q1 Journal Open Access Journal
Country
United States
Northern America
Subject Area and Category
Agricultural and Biological Sciences
Computational Theory and Mathematics Q1
Ecology Q1
Ecology, Evolution, Behavior and Systematics Q1
SJR 2025
1.466
Q1
SJR Score
H-Index
237
Citations / Doc (2yr)
3.50
Total Docs. (latest)
878
Total Citations (3yr)
9,152
Publication type
Journals
ISSN
15537358, 1553734X
Coverage
2005-2026
Journal Rank
#2,536

Subject Categories

Computational Theory and Mathematics Q1
Ecology Q1
Ecology, Evolution, Behavior and Systematics Q1
Genetics Q1
Modeling and Simulation Q1
Molecular Biology Q1
Cellular and Molecular Neuroscience Q2

Aims & Scope

PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.

Abstracting & Indexing

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Detailed Metrics

Total Docs. (latest) 878
Total Docs. (3 years) 2,355
Total Refs. 53,085
Total Citations (3 years) 9,152
Citable Docs. (3 years) 2,346
Citations / Doc. (2 years) 3.50
Ref. / Doc. 60.46
% Female 33.1%

Metrics Visualization

Latest year data vs 3-year cumulative figures

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Journal Information

SJR1.466
Best QuartileQ1
H Index237
ISSN15537358, 1553734X
PublisherPublic Library of Science
CountryUnited States
RegionNorthern America
Coverage2005-2026
Open AccessYes
TypeJournal
Rank#2,536

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