PLoS Computational Biology
PLoS Computational Biology
期刊ISSN: 1553-7358
E-ISSN: -
影响因子: 登录后查看数据
自引率: 2.8%
SCI期刊JCR分区
SCI期刊JCR分区等级:1区
按学科分区
BIOCHEMICAL RESEARCH METHODS
Q2
MATHEMATICAL & COMPUTATIONAL BIOLOGY
Q1
BIOCHEMICAL RESEARCH METHODS
Q1
MATHEMATICAL & COMPUTATIONAL BIOLOGY
Q1
《新锐期刊分区表》(2026年3月发布)
大类学科
生物
2区
小类学科
生化研究方法
1区
数学与计算生物学
1区
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综述期刊
最新中科院SCI期刊分区(2025年3月升级版)
大类学科
生物学
2区
小类学科
生化研究方法
2区
数学与计算生物学
2区
Top期刊
综述期刊
期刊简介
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.
出版信息
出版商
Public Library of Science
涉及的研究方向
Environmental Science-Ecology
年文章数
741
出版国家或地区
United States
是否OA
Cite Score(2025年最新版)
Cite Score SJR SNIP 排名
7.2 1.503 1.137
学科
大类学科:Agricultural and Biological Sciences
小类学科:Ecology, Evolution, Behavior and Systematics
分区
Q1
学科
大类学科:Agricultural and Biological Sciences
小类学科:Modeling and Simulation
分区
Q1
学科
大类学科:Agricultural and Biological Sciences
小类学科:Ecology
分区
Q1
学科
大类学科:Agricultural and Biological Sciences
小类学科:Computational Theory and Mathematics
分区
Q1
学科
大类学科:Agricultural and Biological Sciences
小类学科:Genetics
分区
Q2
学科
大类学科:Agricultural and Biological Sciences
小类学科:Molecular Biology
分区
Q2
学科
大类学科:Agricultural and Biological Sciences
小类学科:Cellular and Molecular Neuroscience
分区
Q2
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