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Computational Biology And ChemistrySCIE

國際簡稱：COMPUT BIOL CHEM 參考譯名：計算生物學和化學

中科院分區(qū)
4區(qū)
CiteScore分區(qū)
Q1
JCR分區(qū)
Q2

基本信息：: ISSN：1476-9271; E-ISSN：1476-928X; 是否OA：未開放; 是否預警：否; TOP期刊：否

出版信息：: 出版地區(qū)：ENGLAND; 出版商：Elsevier Ltd; 出版語言：English; 出版周期：Bimonthly; 出版年份：2003; 研究方向：生物-計算機：跨學科應用

評價信息：: 影響因子：2.6; H-index：55; CiteScore指數(shù)：6.1; SJR指數(shù)：0.497; SNIP指數(shù)：0.782

發(fā)文數(shù)據：: Gold OA文章占比：6.84%; 研究類文章占比：100.00%; 年發(fā)文量：144; 自引率：0.0322...; 開源占比：0.043; 出版撤稿占比：0; 出版國人文章占比：0.19; OA被引用占比：0.0232

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英文簡介期刊介紹 CiteScore數(shù)據中科院SCI分區(qū) JCR分區(qū) 發(fā)文數(shù)據常見問題

英文簡介Computational Biology And Chemistry期刊介紹

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.

期刊簡介Computational Biology And Chemistry期刊介紹

《Computational Biology And Chemistry》自2003出版以來，是一本生物學優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學研究結果，并為生物學各個領域的原創(chuàng)研究提供一個展示平臺，以促進生物學領域的的進步。該刊鼓勵先進的、清晰的闡述，從廣泛的視角提供當前感興趣的研究主題的新見解，或審查多年來某個重要領域的所有重要發(fā)展。該期刊特色在于及時報道生物學領域的最新進展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預警期刊名單，目前已被權威數(shù)據庫SCIE收錄，得到了廣泛的認可。

該期刊投稿重要關注點：

預計審稿時間：約15.0個月
生物學
BIOLOGY
SCIE
中科院4區(qū)
非預警

Cite Score數(shù)據（2024年最新版）Computational Biology And Chemistry Cite Score數(shù)據

CiteScore：6.1
SJR：0.497
SNIP：0.782

學科類別	分區(qū)	排名	百分位
大類：Mathematics 小類：Computational Mathematics	Q1	27 / 189	85%
大類：Mathematics 小類：Organic Chemistry	Q2	66 / 211	68%
大類：Mathematics 小類：Structural Biology	Q2	21 / 49	58%
大類：Mathematics 小類：Biochemistry	Q2	190 / 438	56%

CiteScore 是由Elsevier(愛思唯爾)推出的另一種評價期刊影響力的文獻計量指標。反映出一家期刊近期發(fā)表論文的年篇均引用次數(shù)。CiteScore以Scopus數(shù)據庫中收集的引文為基礎，針對的是前四年發(fā)表的論文的引文。CiteScore的意義在于，它可以為學術界提供一種新的、更全面、更客觀地評價期刊影響力的方法，而不僅僅是通過影響因子(IF)這一單一指標來評價。

歷年Cite Score趨勢圖

中科院SCI分區(qū)Computational Biology And Chemistry 中科院分區(qū)

中科院 2023年12月升級版 綜述期刊：否 Top期刊：否

大類學科	分區(qū)	小類學科	分區(qū)
生物學	4區(qū)	BIOLOGY 生物學 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計算機：跨學科應用	4區(qū) 4區(qū)

中科院分區(qū)表 是以客觀數(shù)據為基礎，運用科學計量學方法對國際、國內學術期刊依據影響力進行等級劃分的期刊評價標準。它為我國科研、教育機構的管理人員、科研工作者提供了一份評價國際學術期刊影響力的參考數(shù)據，得到了全國各地高校、科研機構的廣泛認可。

中科院分區(qū)表 將所有期刊按照一定指標劃分為1區(qū)、2區(qū)、3區(qū)、4區(qū)四個層次，類似于“優(yōu)、良、及格”等。最開始，這個分區(qū)只是為了方便圖書管理及圖書情報領域的研究和期刊評估。之后中科院分區(qū)逐步發(fā)展成為了一種評價學術期刊質量的重要工具。

歷年中科院分區(qū)趨勢圖

JCR分區(qū)Computational Biology And Chemistry JCR分區(qū)

2023-2024 年最新版

按JIF指標學科分區(qū)	收錄子集	分區(qū)	排名	百分位
學科：BIOLOGY	SCIE	Q2	35 / 109	68.3%
學科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q2	80 / 169	53%

按JCI指標學科分區(qū)	收錄子集	分區(qū)	排名	百分位
學科：BIOLOGY	SCIE	Q2	43 / 109	61.01%
學科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q2	76 / 169	55.33%

JCR分區(qū)的優(yōu)勢在于它可以幫助讀者對學術文獻質量進行評估。不同學科的文章引用量可能存在較大的差異，此時單獨依靠影響因子(IF)評價期刊的質量可能是存在一定問題的。因此，JCR將期刊按照學科門類和影響因子分為不同的分區(qū)，這樣讀者可以根據自己的研究領域和需求選擇合適的期刊。

歷年影響因子趨勢圖

發(fā)文數(shù)據

2023-2024 年國家/地區(qū)發(fā)文量統(tǒng)計

國家/地區(qū)數(shù)量
India169
CHINA MAINLAND149
USA51
Iran42
Turkey29
Pakistan26
South Korea19
Brazil18
Italy18
Australia16

本刊中國學者近年發(fā)表論文

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