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PLoS Computational Biology
短名 | PLoS Comput Biol |
Journal Impact | 3.97 |
国际分区 | MATHEMATICAL & COMPUTATIONAL BIOLOGY(Q1) |
期刊索引 | SCI Q1中科院 2 区 |
ISSN | 1553-734X, 1553-7358 |
h-index | 217 |
国内分区 | 生物学(2区)生物学生化研究方法(2区)生物学数学与计算生物学(2区) |
PLOS 计算生物学期刊发表具有重要意义的研究,旨在通过应用计算方法加深我们对生命系统的理解,涵盖从分子和细胞到患者群体和生态系统的各个尺度。该期刊的读者包括生命科学和计算科学的研究人员,他们可以利用这里的重要发现推动新的研究进展。所有研究文章必须明确声明属于相关部分,具体要求请参见提交指南。研究文章应模拟生物系统的各个方面,展示方法和科学的新颖性,并提供深刻的新生物学见解。通常情况下,计算发现的生物学可靠性和意义应通过实验研究进行验证,尽管发表时不强制要求包含实验验证,但应尽可能引用相关实验。仅通过计算验证的适度生物学发现并不足以使手稿适合发表在PLOS 计算生物学期刊上。特别指定为方法论文的研究文章应描述那些已被广泛采用或有潜力被广泛使用的杰出方法,这些方法必须具有特殊的重要性,或者能够提供新的生物学见解。只有当这些增强功能带来显著的新特性时,才会考虑对现有已发布方法的改进。
期刊主页投稿网址阅读文献时,研飞即可帮你快速了解期刊,查询影响因子与分区,智能高亮期刊预警!
涉及主题 | 生物化学遗传学计算机科学生物化学医学物理基因计算生物学数学心理学人工智能内科学工程类神经科学统计量子力学细胞生物学哲学 |
出版信息 | 出版商: Public Library of Science,出版周期: Monthly,期刊类型: journal |
基本数据 | 创刊年份: 2005,原创研究文献占比: 99.19%,自引率:5.30%, Gold OA占比: 99.67% |
平均审稿周期 | 网友分享经验:平均3.0个月 |
平均录用比例 | 网友分享经验:很难 |
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