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.

Topics of Interest

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

Tags:

Journals & Series

Journals & Series / Views

Home
— clouds
tags

Journal

BioData Mining

— acronym

BDM

— publisher

BioMed Central

URLs & IDs

home page

— Scopus

17300154988

— DBLP

journals/biodatamining

— online ISSN

1756-0381

https://www.scimagojr.com/journal_img.php?id=17300154988

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