期刊名称 | BioData Mining BIODATA MIN |
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期刊ISSN | 1756-0381 |
期刊官方网站 | https://biodatamining.biomedcentral.com |
是否OA | Yes |
出版商 | BioMed Central Ltd |
出版周期 | |
文章处理费 | 登录后查看 |
始发年份 | 2008 |
年文章数 | 32 |
影响因子 | 4.0(2023) scijournal影响因子 greensci影响因子 |
大类学科 | 小类学科 | Top | 综述 |
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生物4区 | MATHEMATICAL & COMPUTATIONAL BIOLOGY 数学与计算生物学3区 | 否 | 否 |
CiteScore排名 | CiteScore | SJR | SNIP | ||
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学科 | 排名 | 百分位 | 7.9 | 0.958 | 1.413 |
Mathematics Computational Mathematics |
11/189 | 94% |
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Computer Science Computational Theory and Mathematics |
17/176 | 90% |
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Computer Science Computer Science Applications |
166/817 | 79% |
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Biochemistry, Genetics and Molecular Biology Genetics |
76/347 | 78% |
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Biochemistry, Genetics and Molecular Biology Biochemistry |
104/438 | 76% |
自引率 | 3.00% |
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H-index | 23 |
SCI收录状况 |
Science Citation Index Expanded |
官方审稿时间 | 登录后查看 |
网友分享审稿时间 | 数据统计中,敬请期待。 |
接受率 | 登录后查看 |
PubMed Central (PMC) | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1756-0381%5BISSN%5D |
期刊投稿网址 | https://www.editorialmanager.com/BIDM |
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收稿范围 | BioData Mining is an open access, open peer-reviewed, informatics journal encompassing research on all aspects of Artificial Intelligence (AI), Machine Learning, and Visual Analytics, applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, genomic, metabolomic data and/or electronic health records, social determinants of health, and environmental exposure 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. Data types include Imaging Electronic health records Biobanks Environmental data Social and behavioral data Wearable devices Social media data |
收录体裁 | Methodology Research Review Short report Software article |
投稿指南 | https://biodatamining.biomedcentral.com/submission-guidelines |
投稿模板 | https://biodatamining.biomedcentral.com/submission-guidelines/preparing-your-manuscript |
参考文献格式 | https://biodatamining.biomedcentral.com/submission-guidelines/preparing-your-manuscript |
编辑信息 |
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