Call for Papers
ICDM-2013 Workshop on Biological Data Mining and its Applications in Healthcare
December 8, 2013, Dallas, Texas USA
Workshop Co-Chairs: Xiao-Li Li, See-Kiong Ng, Jason T.L. Wang
http://www1.i2r.a-star.edu.sg/~xlli/BioDM2013/BioDM.html
1. Introduction
The biologists are stepping up their efforts to understand the biological processes that underlie
disease pathways. This has resulted in a flood of biological and clinical data from genomic
sequences, DNA microarrays, and protein interactions, to biomedical images, disease pathways,
and electronic health records. We are in a situation where our ability to generate biomedical data has
greatly surpassed our ability to mine and analyze the data.
We can expect data mining to play an increasingly crucial role in furthering biological research,
since data mining is designed to handle challenging data analysis problems. In fact, it is our hope
that data mining will be the next technical innovation employed by biologists to enable them to make
insightful observations and groundbreaking discoveries from their wide array of heterogeneous data from
molecular biology to pharmaceutical and clinical domains.
There are still many fundamental data analysis challenges to be overcome in order to discover
new knowledge from the biomedical data to translate into clinical applications. These include
practical issues such as handling noisy and incomplete data (e.g. protein interactions have high false
positive and false negative rates), processing compute-intensive tasks (e.g. large scale graph
mining), and integrating heterogeneous data sources (e.g. linking genomic data, proteomics data
with clinical databases).
This is an unprecedented opportunity for data mining researchers from the computer science
domain to contribute to the meaningful scientific pursuit together with the biologists and clinical
scientists. This workshop’s mission is to disseminate the research results and best practices of data
mining approaches to the cross-disciplinary researchers and practitioners from both the data
mining disciplines and the life sciences domains. We encourage submission of papers describing the
design and use of data mining techniques to address the various challenging issues in biological
data analysis. We particularly welcome paper submissions that report the development of data
mining techniques in healthcare-related applications that integrate the use of biological data in a
clinical context for translational research.
2. The topics of interest
The topics of the workshop include but are not limited to:
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Biological and medical data collection, cleansing, and integration
Big biomedical data management, analysis, and prediction
Biological and medical data visualization
Bioimage analysis
Data pre-processing to handle noisy, missing biological and medical data
Knowledge representation and annotation of biological and medical data
Machine learning algorithms for biological and healthcare applications
Disease bioinformatics
Computational methods for drug discovery
Biological markers detection
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Pharmacogenomics data mining and personalized medicine
Big data mining with high-throughput and next-generation sequencing technologies
(DNA-seq, RNA-seq, ChIP-seq, etc.)
Analysis of complex disorders
Integration of biological and clinical data for translational research
Bioinformatics databases and resources
Text mining algorithms for biological and healthcare applications
Biological network analysis (protein interaction network, metabolic network,
transcription factor network, signalling network, etc.)
Pattern analysis in computational genetics, genomics and proteomics
Semantic web and knowledge acquisition in biology and healthcare
Electronic health records and biomedical repositories
3. Important Dates
Aug 3, 2013:
Oct 1, 2013:
Dec 8, 2013:
Due date for paper submission
Notification of paper acceptance to authors
Workshop date
4. Submissions
Paper submissions are limited to a maximum of 8 pages in the IEEE 2-column format (Please refer
to http://icdm2013.rutgers.edu/dates). All papers will be reviewed by the Program Committee
based on technical quality, relevance to data mining, originality, significance, and clarity. A double
blind reviewing process will be adopted. Authors should therefore avoid using identifying
information in the text of the paper. All papers should be submitted through the ICDM Workshop
Submission Site.
All accepted workshop papers will be published in a separate ICDM workshop proceedings
published by the IEEE Computer Society Press. In addition, authors with accepted papers to the
workshop will have the opportunity to be invited to publish their extended versions in the
following two venues: a) as book chapters in an edited book which will be published by World
Scientific and b) as journal papers in International Journal of Knowledge Discovery in
Bioinformatics (IJKDB).
5. PC members
Zhang Aidong, State University of New York at Buffalo (UB), USA
Tatsuya Akutsu, Kyoto University, Japan
Zeyar Aung, Masdar Institute of Science and Technology, United Arab Emirates
Vladimir Bajic, King Abdullah University of Science and Technology, Saudi Arabia
Christopher Baker, University of New Brunswick, Canada
Jake Chen, Indiana University School of Informatics, Indianapolis, USA
Jin Chen, Michigan State University, USA
Phoebe Chen, La Trobe University, Australia
Honnian Chua, Harvard University, USA
Juan Cui, University of Georgia, USA
Yang Dai, University of Illinois at Chicago, USA
Aryya Gangopadhyay, University of Maryland, Baltimore County, USA
Xiaoxu Han, Eastern Michigan University, USA
David Hansen, Australian e-Health Research Centre, Australia
Wen-Lian Hsu, Academia Sinica, Taiwan
Jun (Luke) Huan, University of Kansas, USA
Jimmy Huang, York University, Canada
Raphael Isokpehi, Jackson State University, USA
Asif Javed, IBM Thomas J. Watson Research Center, USA
Igor Jurisica, University of Toronto, Canada
Maricel Kann, University of Maryland, Baltimore County, USA
Daisuke Kihara, Purdue University, USA
Shonali Krishnaswamy, Monash University, Australia
Chee Keong Kwoh, Nanyang Technological University, Singapore
Dawei Li, Yale University, USA
Haiquan Li, University of Chicago, USA
Ming Li, University of Waterloo, Canada
Yongjin Li, St Jude Children's Research Hospital, USA
Hiroshi Mamitsuka, Kyoto University, Japan
Sean Mooney, Indiana University, USA
Laxmi Parida, IBM T. J. Watson Research Center, USA
George Perry, University of Texas at San Antonio, USA
Raul Rabadan, Columbia University, USA
Mark A. Ragan, The University of Queensland, Australia
Jianhua Ruan, University of Texas at San Antonio, USA
Saeed Salem, North Dakota State University
Indra Neil Sarkar, University of Vermont, USA
Ambuj K Singh, University of California at Santa Barbara, USA
Narayanaswamy Srinivasan, Indian Institute of Science, India
Zeeshan Syed, University of Michigan, USA
Vincent S. Tseng, National Cheng Kung University, Taiwan
Alfonso Valencia, Spanish National Cancer Research Centre, Spain
Hong Yan, City University of Hong Kong, China
Sungroh Yoon, Seoul National University, Korea
Philip S. Yu, University of Illinois at Chicago, USA
Xiaoling (Shirley) Zhang, Boston University, Boston, MA
Erliang Zeng, University of Notre Dame, USA
Marketa Zvelebil, Breakthrough Breast Cancer Research - ICR, UK