BioDM: ICDM 2014 Workshop on Biological Data Mining and Its Applications in Healthcare
December 14, 2014
Shenzhen, China
http://www1.i2r.a-star.edu.sg/~xlli/BioDM2014/BioDM.html

Key Dates
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Paper Submission Due: Aug 18, 2014
Acceptance Notification: Sep 26, 2014
Workshop Date: Dec 14, 2014
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Submission Website:
https://wi-lab.com/cyberchair/2014/icdm14/scripts/submit.php?subarea=S6&undisplay_detail=1&wh=/cyberchair/2014/icdm14/scripts/ws_submit.php

Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. 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 scenario where our capability to generate biomedical data has greatly surpassed our abilities to mine and analyze them.

To exploit these biomedical data for discovering new knowledge that can be translated into clinical applications, there are a lot of challenges. Practical issues such as handling noisy and incomplete data (e.g. protein interactions have high false positive and false negative rates), processing computation-intensive tasks (e.g. large scale graph mining), and integrating heterogeneous data sources (e.g. linking genomic data, proteomics data with clinical databases).

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 therefore unprecedented opportunities for data mining researchers from the computer science domain to contribute to this meaningful scientific pursuit together with the biologists and clinical scientists. The mission of this workshop 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 therefore encourage submission of papers using data mining techniques to address the challenging issues in various biological data analysis. In particular, we especially welcome the submissions reporting data mining techniques in healthcare related applications that integrate the use of biological data in a clinical context for translational research.

The topics of the workshop include but are not limited to:
- Biological and medical data collection, cleansing, and integration
- Visual analytics for biological and medical data
- Pre-processing for noisy, sparse biological and medical data
- Knowledge representation and annotation of biological and medical data
- Application of analytical algorithms for biological and healthcare data
- Computational methods for drug discovery
- Biological markers detection
- Pharmacogenomics data mining
- 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

Submission Guidelines:
Paper submissions are limited to a maximum of 8 pages in the IEEE 2-column format (Please refer to http://icdm2014.sfu.ca/submission.html). 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 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 Springer and b) as journal papers in IEEE Transactions on Computational Biology and Bioinformatics (TCBB).

Workshop Co-Chairs:
- Xiao-Li Li, A*STAR
- See-Kiong Ng, A*STAR
- Jason T.L. Wang, New Jersey Institute of Technology
- Fei Wang, IBM T.J. Watson Research Center

Publicity Chair:
- Xiang Wang, IBM T.J. Watson Research Center