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[Computational-biology] CFP: ICDM-2015 Workshop on Biological Data Mining and its Applications in Healthcare

Wu Min via comp-bio%40net.bio.net (by ustcwumin from gmail.com)
Fri May 1 19:00:07 EST 2015


Call for Papers
ICDM-2015 Workshop on Biological Data Mining and its Applications in Healthcare
Nov 13, 2015, Atlantic City, NJ, USA
Workshop Co-Chairs: Xiao-Li Li, See-Kiong Ng, Jason T.L. Wang, Fei Wang
http://www1.i2r.a-star.edu.sg/~xlli/BioDM2015/BioDM.html

1. Introduction 
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. 

2. The topics of interest 
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 
-Bioimage analysis 
-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 
-Disease bioinformatics 
-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 

3. Important Dates 

July 20, 2015:	 	Due date for paper submission 
Sep 1, 2015: 		Notification of paper acceptance to authors 
Nov 13, 2015: 		Workshop date 

4. Submissions 
Paper submissions are limited to a maximum of 8 pages in the IEEE 2-column format (Please refer to http://icdm2015.stonybrook.edu/). 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 a website which will be provided through the http://icdm2015.stonybrook.edu/content/call-workshops. 

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). 

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 
Xin Chen, Nanyang Technological University, Singapore
Honnian Chua, Harvard University, USA 
Juan Cui, University of Georgia, USA 
Yang Dai, University of Illinois at Chicago, USA 
Frank Eisenhaber, Bioinformatics Institute, Singapore
Aryya Gangopadhyay, University of Maryland, Baltimore County, USA
Xin Gao, King Abdullah University of Science and Technology, Saudi Arabia
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 
Jaebum Kim, Konkuk University, Korea  
Sun Kim, National Center for Biotechnology Information, USA
Shonali Krishnaswamy, Monash University, Australia 
Chee Keong Kwoh, Nanyang Technological University, Singapore 
Hon Wai Leong, National University of Singapore, Singapore
Dawei Li, Yale University, USA 
Haiquan Li, University of Chicago, USA 
Jinyan Li, University of Technology, Sydney, Australia
Ming Li, University of Waterloo, Canada 
Yongjin Li, St Jude Children's Research Hospital, USA 
Hiroshi Mamitsuka, Kyoto University, Japan
Fenglou Mao, University of Georgia, USA 
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
Min Wu, Institute for Infocomm Research, Singapore 
Hong Yan, City University of Hong Kong, China 
Sungroh Yoon, Seoul National University, Korea 
Philip S. Yu, University of Illinois at Chicago, USA 
Xuegong Zhang, Tsinghua University, China
Xiaoling (Shirley) Zhang, Boston University, Boston, MA 
Erliang Zeng, University of Notre Dame, USA
Jie Zheng, Nanyang Technological University, Singapore
Yun Zheng, Kunming University of Science and Technology, China
Shuigeng Zhou, Fudan University, China
Shanfeng Zhu, Fudan University, China
Zexuan Zhu, Shenzhen University, China
Marketa Zvelebil, Breakthrough Breast Cancer Research - ICR, UK



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