• Jason Moore, University of Pennsylvania
  • Marylyn Ritchie, Pennsylvania State University


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Aims & scope

BioData Mining is an open access, peer reviewed, online 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.

Editors' profiles

Prof Jason Moore

Dr. Moore directs an NIH-funded research program that is focused on complex systems approaches to understanding the genetic basis for common human diseases. A major focus of the lab is on the development, evaluation and application of machine learning and data mining algorithms for detecting and characterizing nonlinear gene-gene and gene-environment interactions. Recent work is focused on the study of epistasis using network science and visual analytics. More information can be found at www.epistasis.org and compgen.blogspot.com.

Dr. Aguilar

Dr. Aguilar leads a research group on Bioinformatics. His group is involved in several projects related to gene association networks, protein structure prediction, disease prognosis and application of data mining or evolutionary techniques to biomedical problems. He is the Dean of the School of Engineering, at Pablo de Olavide University, Seville, Spain, and one of his main concerns is to approach biologists and computer scientists to common research goals.

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Indexed by

  • ACM
  • CAS
  • DBLP
  • DOAJ
  • Embase
  • EmBiology
  • Journal Citation Reports/Science Edition
  • PubMed
  • PubMed Central
  • Science Citation Index Expanded
  • Scopus

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ISSN: 1756-0381