BioData Mining is an open access, open peer-reviewed journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data.
Topical areas include, but are not limited to:
-Development, evaluation, and application of novel data mining and machine learning algorithms.
-Adaptation, evaluation, and application of traditional data mining and machine learning algorithms.
-Open-source software for the application of data mining and machine learning algorithms.
-Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies.
-Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.
《Biodata Mining》是一本由BMC出版商出版的专业生物期刊,该刊创刊于2008年,刊期1 issue/year,该刊已被国际权威数据库SCIE收录。在中科院最新升级版分区表中,该刊分区信息为大类学科:生物 3区,小类学科:数学与计算生物学 3区;在JCR(Journal Citation Reports)分区等级为Q1。该刊发文范围涵盖数学与计算生物学等领域,旨在及时、准确、全面地报道国内外数学与计算生物学工作者在该领域取得的最新研究成果、工作进展及学术动态、技术革新等,促进学术交流,鼓励学术创新。2021年影响因子为4.079,平均审稿速度23 Weeks。
大类学科 | 分区 | 小类学科 | 分区 | Top期刊 | 综述期刊 |
生物学 | 4区 | MATHEMATICAL & COMPUTATIONAL BIOLOGY 数学与计算生物学 | 3区 | 否 | 否 |
JCR分区等级 | JCR所属学科 | 分区 | 影响因子 |
Q1 | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Q1 | 4.079 |
影响因子 | h-index | Gold OA文章占比 | 研究类文章占比 | OA开放访问 | 平均审稿速度 |
4.079 | 23 | 98.85% | 100.00% | 开放 | 23 Weeks |
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