BioData Mining

BioData Min

1756-0381

Therapeutic Area

Biotechnology, Genomics

Biologists, Biomedical Researchers, Computer Scientists, Statisticians

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.

No associations affiliated with this journal

BioMed Central Ltd. (BMC)

Impact Factor JCR Categories/Rank Electronic Circulation Submission to Acceptance Acceptance to Online Publication Rejection Rate Frequency Journal Contact Author Submission Guidelines