PLoS Computational Biology
Note: The following journal information is for reference only. Please check the journal website for updated information prior to submission.
Journal Title
PLoS Computational Biology
PLOS COMPUT BIOL
ISSN / eISSN
1553-734X / 1553-7358
Aims and 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.
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.
Subject Area
BIOCHEMICAL RESEARCH METHODS
MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
View Trend
CiteScore Ranking
| Category | Quartile | Rank |
|---|---|---|
| Mathematics - Modeling and Simulation | Q1 | #29/316 |
| Mathematics - Ecology, Evolution, Behavior and Systematics | Q1 | #76/687 |
| Mathematics - Computational Theory and Mathematics | Q1 | #19/165 |
| Mathematics - Ecology | Q1 | #53/437 |
| Mathematics - Genetics | Q2 | #92/328 |
| Mathematics - Cellular and Molecular Neuroscience | Q2 | #32/90 |
| Mathematics - Molecular Biology | Q2 | #155/380 |
Web of Science Core Collection
| Science Citation Index Expanded (SCIE) | Social Sciences Citation Index (SSCI) |
|---|---|
| Indexed | - |
| Category (Journal Citation Reports 2023) | Quartile |
|---|---|
| BIOCHEMICAL RESEARCH METHODS - SCIE | Q1 |
| MATHEMATICAL & COMPUTATIONAL BIOLOGY - SCIE | Q1 |
H-index
138
Country/Area of Publication
UNITED STATES
Publisher
Public Library of Science
Annual Article Volume
737
Open Access
YES
Contact
1160 BATTERY STREET, STE 100, SAN FRANCISCO, USA, CA, 94111
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