COMPUTATIONAL BIOLOGY AND CHEMISTRY

期刊基本信息

期刊名称：COMPUTATIONAL BIOLOGY AND CHEMISTRY

出版国家或地区：ENGLAND

是否OA：No

期刊ISSN：1476-9271

期刊官方网站：http://www.elsevier.com/wps/find/journaldescription.cws_home/627320/description#description

期刊投稿网址：http://ees.elsevier.com/cbac/

通讯方式：ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD, ENGLAND, OXON, OX5 1GB

涉及的研究方向：生物-计算机：跨学科应用

出版周期：Bimonthly

出版年份：2003

期刊数据表：

COMPUTATIONAL BIOLOGY AND CHEMISTRY英文简介：

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.

COMPUTATIONAL BIOLOGY AND CHEMISTRY中文简介：

计算生物学和化学在计算生命科学的所有领域出版原始研究论文和评论文章。特别欢迎在核酸和蛋白质序列研究、分子进化、分子遗传学(功能基因组学和蛋白质组学)、生物特异性或化学生物特异性建模的理论和实践以及核酸和蛋白质的结构生物学等领域提供高质量的研究成果，这些研究成果是计算方面的重要组成部分。在生物信息学、系统生物学、生态学、计算药理学、代谢、生物医学工程、流行病学和统计遗传学方面的高质量研究工作也将被考虑。鉴于它们固有的不确定性，蛋白质模型和分子对接研究应该得到彻底的验证。在缺乏实验结果进行验证的情况下，例如，应该使用分子动力学模拟和详细的自由能计算作为补充技术来支持主要结论。没有额外的生物学见解的不成熟的模型练习的提交将不被考虑。评审文章一般由编辑委托撰写，未经明确邀请不得投稿。然而，欢迎未来的作者发送一个简短的(一到三页)概要，这将由编辑进行评估。

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