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BioData Mining
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Featured article: The role of visualization and 3-D printing
in biological data mining
© 2015 Weiss et al.
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. Methodology
r2VIM: A new variable selection method for random forests in genomewide association studies
Silke Szymczak, Emily Holzinger, Abhijit Dasgupta, James D. Malley, Anne M. Molloy,
James L. Mills, Lawrence C. Brody, Dwight Stambolian and Joan E. Bailey-Wilson
Published on: 1 February 2016
2. SOFTWARE ARTICLE
SequenceCEROSENE: a computational method and web server to
visualize spatial residue neighborhoods at the sequence level
Florian Heinke, Sebastian Bittrich, Florian Kaiser and Dirk Labudde
Published on: 27 January 2016
3. Research
The prediction accuracy of dynamic mixed-effects models in clustered data
Brian S. Finkelman, Benjamin French and Stephen E. Kimmel
Published on: 27 January 2016
4. Methodology
Prediction of donor splice sites using random forest with a new sequence
encoding approach
Prabina Kumar Meher, Tanmaya Kumar Sahu and Atmakuri Ramakrishna Rao
Published on: 22 January 2016
5. Short report
Network-based analysis of genetic variants associated with hippocampal
volume in Alzheimer’s disease: a study of ADNI cohorts
Ailin Song, Jingwen Yan, Sungeun Kim, Shannon Leigh Risacher, Aaron K. Wong,
Andrew J. Saykin, Li Shen and Casey S. Greene
Published on: 19 January 2016
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1. Research
Search extension transforms Wiki into a relational system: A case for
flavonoid metabolite database
Masanori Arita and Kazuhiro Suwa
Published on: 17 September 2008
2. Review
Using graph theory to analyze biological networks
Georgios A Pavlopoulos, Maria Secrier, Charalampos N Moschopoulos, Theodoros G
Soldatos, Sophia Kossida, Jan Aerts, Reinhard Schneider and Pantelis G Bagos
Published on: 28 April 2011
3. Review
Unraveling genomic variation from next generation sequencing data
Georgios A Pavlopoulos, Anastasis Oulas, Ernesto Iacucci, Alejandro Sifrim, Yves
Moreau, Reinhard Schneider, Jan Aerts and Ioannis Iliopoulos
Published on: 25 July 2013
4. Review
A survey of visualization tools for biological network analysis
Georgios A Pavlopoulos, Anna-Lynn Wegener and Reinhard Schneider
Published on: 28 November 2008
5. Review
Applications of the MapReduce programming framework to clinical big
data analysis: current landscape and future trends
Emad A Mohammed, Behrouz H Far and Christopher Naugler
Published on: 29 October 2014
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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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Editors' profiles
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).
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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