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:
• 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
• 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: Due date for paper submission
Oct 1, 2013: Notification of paper acceptance to authors
Dec 8, 2013: 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. Confirmed PC members
Aidong Zhang, State University of New York at Buffalo (UB), USA
Alfonso Valencia, Spanish National Cancer Research Centre, Spain
Philip S. Yu, University of Illinois at Chicago, USA
Tatsuya Akutsu, Kyoto University, Japan
Gianluca Bontempi, Université libre de Bruxelles, Belgium
Vincent S. Tseng, National Cheng Kung University, Taiwan
Yang Dai, University of Illinois at Chicago, USA
Aryya Gangopadhyay, University of Maryland, Baltimore County, USA
Vladimir Bajic, King Abdullah University of Science and Technology, Saudi Arabia
David Hansen, Australian e-Health Research Centre, Australia
Daisuke Kihara, Purdue University, USA
Hiroshi Mamitsuka, Kyoto University, Japan
Mark A. Ragan, The University of Queensland, Australia
George Perry, University of Texas at San Antonio, USA
Narayanaswamy Srinivasan, Indian Institute of Science, India
Zeyar Aung, Masdar Institute of Science and Technology, United Arab Emirates
Hong Yan, City University of Hong Kong, China
Xin Gao, King Abdullah University of Science and Technology, Saudi Arabia
Xiaoxu Han, Eastern Michigan University, USA
Raphael Isokpehi, Jackson State University, USA
Shonali Krishnaswamy, Monash University, Australia
Chee Keong Kwoh, Nanyang Technological University, Singapore
Haiquan Li, University of Chicago, USA
Yongjin Li, St Jude Children's Research Hospital, USA
Raul Rabadan, Columbia University, USA
Honnian Chua, Institute for Infocomm Research, Singapore
Jianhua Ruan, University of Texas at San Antonio, USA
Saeed Salem, North Dakota State University
Zeeshan Syed, University of Michigan, USA
Sungroh Yoon, Seoul National University, Korea
Erliang Zeng, University of Notre Dame, USA
Xiaoling (Shirley) Zhang, Boston University, Boston, MA