Plos Computational Biology

SCI SCIE

国际简称：PLOS COMPUT BIOL 参考译名：Plos 计算生物学

主要研究方向：Environmental Science-Ecology 非预警期刊审稿周期：32 Weeks

《Plos 计算生物学》(Plos Computational Biology)是一本由Public Library of Science出版的以Environmental Science-Ecology为研究特色的国际期刊，发表该领域相关的原创研究文章、评论文章和综述文章，及时报道该领域相关理论、实践和应用学科的最新发现，旨在促进该学科领域科学信息的快速交流。该期刊是一本开放期刊，近三年没有被列入预警名单。该期刊享有很高的科学声誉，影响因子不断增加，发行量也同样高。

2区中科院分区
Q1 JCR分区
853 年发文量
3.7 IF影响因子
开放是否OA
138 H-index
2005 创刊年份
Monthly 出版周期
English 出版语言

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.

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Plos Computational Biology期刊信息

ISSN：1553-7358
出版语言：English
是否OA：开放
E-ISSN：1553-7358
出版地区：United States
是否预警：否
出版商：Public Library of Science
出版周期：Monthly
创刊时间：2005
开源占比：0.9896
Gold OA文章占比：99.96%
OA被引用占比：1
出版国人文章占比：0.04
出版撤稿占比：0
研究类文章占比：99.41%

Plos Computational Biology CiteScore评价数据（2026年6月最新版）

CiteScore

SJR

SNIP

CiteScore 指数

6.2

1.466

1.197

学科类别	分区	排名	百分位
大类：Agricultural and Biological Sciences 小类：Ecology, Evolution, Behavior and Systematics	Q1	87 / 736	88%
大类：Agricultural and Biological Sciences 小类：Modeling and Simulation	Q1	52 / 397	87%
大类：Agricultural and Biological Sciences 小类：Ecology	Q1	75 / 491	84%
大类：Agricultural and Biological Sciences 小类：Computational Theory and Mathematics	Q1	38 / 203	81%
大类：Agricultural and Biological Sciences 小类：Genetics	Q2	106 / 357	70%
大类：Agricultural and Biological Sciences 小类：Cellular and Molecular Neuroscience	Q2	42 / 102	59%
大类：Agricultural and Biological Sciences 小类：Molecular Biology	Q2	173 / 414	58%

名词解释：CiteScore 是衡量期刊所发表文献的平均受引用次数，是在 Scopus 中衡量期刊影响力的另一个指标。当年CiteScore 的计算依据是期刊最近4年（含计算年度）的被引次数除以该期刊近四年发表的文献数。例如，2022年的 CiteScore 计算方法为：2022年的 CiteScore =2019-2022年收到的对2019-2022年发表的文件的引用数量÷2019-2022年发布的文献数量注：文献类型包括：文章、评论、会议论文、书籍章节和数据论文。

Plos Computational Biology中科院评价数据

《新锐期刊分区表》（2026年3月发布）

Top期刊	综述期刊	大类学科		小类学科
否	否	生物学	2区	BIOCHEMICAL RESEARCH METHODS 生化研究方法 MATHEMATICAL & COMPUTATIONAL BIOLOGY 数学与计算生物学	1区 1区

Plos Computational Biology JCR评价数据

2025-2026年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：BIOCHEMICAL RESEARCH METHODS	SCIE	Q2	27 / 85	68.8
学科：MATHEMATICAL & COMPUTATIONAL BIOLOGY	SCIE	Q1	12 / 67	82.8
学科：BIOCHEMICAL RESEARCH METHODS	SCIE	Q1	19 / 85	78.24
学科：MATHEMATICAL & COMPUTATIONAL BIOLOGY	SCIE	Q1	10 / 67	85.82

Plos Computational Biology历年数据统计

影响因子

中科院分区

Plos Computational Biology中国学者发文选摘

1、PhageCGRNet: Integrating Chaos Game Representation of Genomes with Convolutional Neural Network for accurate phage host classification predictio
Author: Wang, Ting; Yu, Zu-Guo; Li, Jinyan; Lin, Xuan

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014130
2、Rural-to-urban migrant worker mobility shaped measles epidemics in Chin
Author: Wang, Peihua; Wang, Xianwen; Zhang, Wenyi; Wang, Yong; Pei, Sen; Xu, Xiao-Ke; Yang, Wan

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014182
3、Efficiency, accuracy and robustness of probability generating function based parameter inference method for stochastic biochemical reaction
Author: Li, Shiyue; Wang, Yiling; Shu, Zhanpeng; Grima, Ramon; Jiang, Qingchao; Cao, Zhixing

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014160
4、Systematic prioritization of potential therapeutic targets for glomerulonephritis using multi-omics Mendelian randomizatio
Author: Li, Guoqiang; Jianhan, Fu; Gu, Jiashu; Wang, Yinhuai; Liu, Jiachen; Yang, Dong; Zeng, Dianjie; Zhao, Pengcheng

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014174
5、Perceptual prediction error supports implicit process in motor learnin
Author: Zhang, Xiaoyue; Wu, Wencheng; Wei, Kunlin

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014196
6、A phase-field model for vesicle membranes incorporating area-difference elasticit
Author: Liang, Yihong; Celiker, Emine; Lin, Ping

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 4, pp. -. DOI: 10.1371/journal.pcbi.1014185
7、CFGSCDSA: Predicting circRNA-drug sensitivity associations based on collaborative feature learning and graph structure learnin
Author: Zhang, Xue; Zou, Quan; Wang, Chunyu; Niu, Mengting

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 3, pp. -. DOI: 10.1371/journal.pcbi.1014072
8、Combining visual motion and luminance features to enhance the detection of small moving objects in a bioinspired mode
Author: Li, Shuai; Guo, Aike; Wang, Yizheng; Li, Liang; Wang, Gang; Wu, Zhihua

Journal: PLOS COMPUTATIONAL BIOLOGY. 2026; Vol. 22, Issue 3, pp. -. DOI: 10.1371/journal.pcbi.1014036