BioData Mining
Q1 Journal
Open Access
Journal
Country
United Kingdom
Western Europe
Subject Area and Category
Biochemistry, Genetics and Molecular Biology
└
Biochemistry
Q1
└
Computational Mathematics
Q1
└
Computational Theory and Mathematics
Q1
Publisher
SJR 2025
1.245
Q1
SJR Score
H-Index
46
Citations / Doc (2yr)
9.74
Total Docs. (latest)
89
Total Citations (3yr)
1,044
Publication type
Journals
ISSN
17560381
Coverage
2009-2026
Journal Rank
#3,407
Subject Categories
Biochemistry
Q1
Computational Mathematics
Q1
Computational Theory and Mathematics
Q1
Computer Science Applications
Q1
Genetics
Q1
Molecular Biology
Q2
Aims & Scope
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.
Abstracting & Indexing
Scopus
Google Scholar
Directory of Open Access Journals (DOAJ)
Web of Science
Embase
Detailed Metrics
| Total Docs. (latest) | 89 |
| Total Docs. (3 years) | 126 |
| Total Refs. | 5,224 |
| Total Citations (3 years) | 1,044 |
| Citable Docs. (3 years) | 123 |
| Citations / Doc. (2 years) | 9.74 |
| Ref. / Doc. | 58.70 |
| % Female | 42.3% |
Metrics Visualization
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