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Computational Biology And ChemistrySCIE

国际简称：COMPUT BIOL CHEM 参考译名：计算生物学和化学

中科院分区
4区
CiteScore分区
Q1
JCR分区
Q2

基本信息：: ISSN：1476-9271; E-ISSN：1476-928X; 是否OA：未开放; 是否预警：否; TOP期刊：否

出版信息：: 出版地区：ENGLAND; 出版商：Elsevier Ltd; 出版语言：English; 出版周期：Bimonthly; 出版年份：2003; 研究方向：生物-计算机：跨学科应用

评价信息：: 影响因子：2.6; H-index：55; CiteScore指数：6.1; SJR指数：0.497; SNIP指数：0.782

发文数据：: Gold OA文章占比：6.84%; 研究类文章占比：100.00%; 年发文量：144; 自引率：0.0322...; 开源占比：0.043; 出版撤稿占比：0; 出版国人文章占比：0.19; OA被引用占比：0.0232

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英文简介期刊介绍 CiteScore数据中科院SCI分区 JCR分区发文数据常见问题

英文简介Computational Biology And Chemistry期刊介绍

Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.

Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.

Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.

期刊简介Computational Biology And Chemistry期刊介绍

《Computational Biology And Chemistry》自2003出版以来，是一本生物学优秀杂志。致力于发表原创科学研究结果，并为生物学各个领域的原创研究提供一个展示平台，以促进生物学领域的的进步。该刊鼓励先进的、清晰的阐述，从广泛的视角提供当前感兴趣的研究主题的新见解，或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道生物学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单，目前已被权威数据库SCIE收录，得到了广泛的认可。

该期刊投稿重要关注点：

预计审稿时间：约15.0个月
生物学
BIOLOGY
SCIE
中科院4区
非预警

Cite Score数据（2024年最新版）Computational Biology And Chemistry Cite Score数据

CiteScore：6.1
SJR：0.497
SNIP：0.782

学科类别	分区	排名	百分位
大类：Mathematics 小类：Computational Mathematics	Q1	27 / 189	85%
大类：Mathematics 小类：Organic Chemistry	Q2	66 / 211	68%
大类：Mathematics 小类：Structural Biology	Q2	21 / 49	58%
大类：Mathematics 小类：Biochemistry	Q2	190 / 438	56%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础，针对的是前四年发表的论文的引文。CiteScore的意义在于，它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法，而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Computational Biology And Chemistry 中科院分区

中科院 2023年12月升级版 综述期刊：否 Top期刊：否

大类学科	分区	小类学科	分区
生物学	4区	BIOLOGY 生物学 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机：跨学科应用	4区 4区

中科院分区表 是以客观数据为基础，运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据，得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次，类似于“优、良、及格”等。最开始，这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Computational Biology And Chemistry JCR分区

2023-2024 年最新版

按JIF指标学科分区	收录子集	分区	排名	百分位
学科：BIOLOGY	SCIE	Q2	35 / 109	68.3%
学科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q2	80 / 169	53%

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：BIOLOGY	SCIE	Q2	43 / 109	61.01%
学科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q2	76 / 169	55.33%

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异，此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此，JCR将期刊按照学科门类和影响因子分为不同的分区，这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

发文数据

2023-2024 年国家/地区发文量统计

国家/地区数量
India169
CHINA MAINLAND149
USA51
Iran42
Turkey29
Pakistan26
South Korea19
Brazil18
Italy18
Australia16

本刊中国学者近年发表论文

1、Microscopic model on indoor propagation of respiratory droplets
Author: Mondal, Manas; Chakrabarti, Srabani; Gao, Yi Qin; Bhattacharyya, Dhananjay; Chakrabarti, Jaydeb

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 102, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2022.107806
2、QM/MM study of N501 involved intermolecular interaction between SARS-CoV-2 receptor binding domain and antibody of human origin
Author: Liu, Yuemin; Sulaiman, Hana F.; Johnson, Bruce R.; Ma, Rulong; Gao, Yunxiang; Fernando, Harshica; Amarasekara, Ananda; Ashley-Oyewole, Andrea; Fan, Huajun; Ingram, Heaven N.; Briggs, James M.

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 102, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107810
3、Molecular docking and molecular simulation studies for N-degron selectivity of chloroplastic ClpS from Chlamydomonas reinhardtii
Author: Wang, Ning; Gao, Jian-Guo; Wu, Ming-Wei

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 103, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107825
4、BRWMC: Predicting lncRNA-disease associations based on bi-random walk and matrix completion on disease and lncRNA networks
Author: Zhang, Guo-Zheng; Gao, Ying-Lian

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 103, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107833
5、Dual computational and biological assessment of some promising nucleoside analogs against the COVID-19-Omicron variant
Author: Abdalla, Mohnad; Rabie, Amgad M.

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 104, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2022.107768
6、Insights into beta(3)-adrenoceptor agonism through comprehensive in silico investigation
Author: Luan, Jiasi; Hu, Baichun; Wang, Hanxun; Liu, Haihan; Wang, Shizhun; Chen, Lu; Li, Weixia; Wang, Jian; Cheng, Maosheng

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 104, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107836
7、BCM-DTI: A fragment-oriented method for drug-target interaction prediction using deep learning
Author: Dou, Liang; Zhang, Zhen; Liu, Dan; Qian, Ying; Zhang, Qian

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 104, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107844
8、ECAmyloid: An amyloid predictor based on ensemble learning and comprehensive sequence-derived features
Author: Yang, Runtao; Liu, Jiaming; Zhang, Lina

Journal: COMPUTATIONAL BIOLOGY AND CHEMISTRY. 2023; Vol. 104, Issue , pp. -. DOI: 10.1016/j.compbiolchem.2023.107853