- Jason Moore, University of Pennsylvania
- Marylyn Ritchie, Pennsylvania State University
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.
BioData Mining 2014, 7:22
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. Marylyn Ritchie, PhD is the Paul Berg Professor of Biochemistry and Molecular Biology and director for the Center for Systems Genomics at The Pennsylvania State University. She is also the founding Director of Biomedical and Translational Informatics at Geisinger Health System. Dr. Ritchie is a statistical and computational geneticist with a focus on understanding genetic architecture of complex human disease. She has expertise in developing novel bioinformatics tools for complex analysis of big data in genetics, genomics, and clinical databases, in particular in the area of Pharmacogenomics. Some of her methods include Multifactor Dimensionality Reduction (MDR), the Analysis Tool for Heritable and Environmental Network Associations (ATHENA), and the Biosoftware suite for annotating/ filtering variants and genomic regions as well as building models of biological relevance for gene-gene interactions and rare-variant burden/dispersion tests. More details about her research projects can be found at http://ritchielab.psu.edu.