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BioData Mining

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Featured article: The role of visualization and 3-D printing in biological data mining

Can 3-D printing be used as a visualization technology in biological data mining? It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results. We discuss the advantages and disadvantages of this novel method. Find out more in our recently published brief review of 3-D printing along with a case study to illustrate how it might be used in a research setting.

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  1. Content type: Review

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    Authors: Georgios A Pavlopoulos, Maria Secrier, Charalampos N Moschopoulos, Theodoros G Soldatos, Sophia Kossida, Jan Aerts, Reinhard Schneider and Pantelis G Bagos

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Editors-in-Chief

Dr Jason Moore, University of Pennsylvania, USA
Dr Marylyn Ritchie, Pennsylvania State University, USA

Aims and 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.

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Dr Jason Moore is the Edward Rose Professor of Informatics, Professor of Biostatistics and Epidemiology, and Professor of Genetics at the Perelman School of Medicine of the University of Pennsylvania. He serves as the first permanent Director of the Institute for Biomedical Informatics and founding Director of the Division of Informatics in the Department of Biostatistics and Epidemiology. He also serves as Senior Associate Dean for Informatics. His work has been communicated in more than 400 scientific publications and he serves as PI on several NIH R01 grants. He has been recognized as a national leader in informatics through election as a Fellow of the American Association for the Advancement of Sciences (AAAS) and as a Kavli Fellow of the National Academy of Sciences (NAS). He was recently elected a Fellow of the American College of Medical Informatics (ACMI).

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Dr Marylyn Ritchie 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.

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