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 and protein sequences, DNA microarrays, protein interactions, to disease pathways, biomedical images, 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 the data.
To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. 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 various data sources (e.g. linking genomic data, proteomics data with clinical databases) are new challenges faced by biologists in the post-genome era.
Data mining has been designed to handle such challenging data analysis problems. We can therefore expect data mining to play an increasingly crucial role in revolutionizing biological research. Data mining will be the next technical innovation employed by biologists to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.
As data mining is poised to become integrated into the next-generation pipeline of biomedical discovery process, there are unprecedented opportunities for data mining researchers from the computer science domain to come together to contribute to this meaningful scientific pursuit with the biologists and clinical scientists. The mission of this workshop is therefore 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 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.
Dear Colleagues,
We are writing to invite you to submit your papers to the ICDM-2011 workshop on Biological Data Mining and its Applications in Healthcare, which will be held in Vancouver, Canada on December 11 2011. ICDM, the IEEE International Conference on Data Mining, is one of the premier conferences in the field of Data Mining.
By co-locating with ICDM 2011, we hope the workshop will bring better awareness of interesting and challenging biological and medical problems that inspire new data mining solutions, and attract the participation of researchers in the areas of data mining and machine learning who are interested in the real-world applications of data mining in computational biology and healthcare.
We look forward to your submissions. In addition, we will greatly appreciate it if you can distribute the Call for Papers to your colleagues, students and other community members and encourage them to contribute to the workshop.
Thank you!
Sincerely,
Workshop Co-Chairs
Xiao-Li Li, See-Kiong Ng and Jason T. L. Wang
The topics of interest include (but are not limited to) the following:
Aug 5, 2011: Due date for paper submission
September 20, 2011: Notification of paper acceptance
October 11, 2011: Camera-ready versions of accepted papers
December 11, 2011: Workshop date
Paper submissions are limited to a maximum of 8 pages (you can submit either full paper 8 pages or short paper 6 pages) in the IEEE 2-column format, which is the same as the camera-ready format (see the IEEE Computer Society Press Proceedings Author Guidelines). 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. You are strongly encouraged to print and double check your PDF file before its submission, especially if your paper contains Asian/European language symbols (such as Chinese/Korean characters or English letters with European fonts). 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).
Zhang Aidong, State University of New York at Buffalo (UB), USA
Tatsuya Akutsu, Kyoto University, Japan
Zeyar Aung, Masdar Institute of Science and Technology, UAE
Vladimir Bajic, King Abdullah University of Science and Technology, Saudi Arabia
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
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
Jimmy Huang, York University, Canada
Raphael Isokpehi, Jackson State University, USA
Dawei Li, Yale University, USA
Haiquan Li, University of Chicago, USA
Igor Jurisica, University of Toronto, Canada
Daisuke Kihara, Purdue University, USA
Shonali Krishnaswamy, Monash University, Australia
Chee Keong Kwoh, Nanyang Technological University, Singapore
Hiroshi Mamitsuka, Kyoto University, Japan
Laxmi Parida, IBM T. J. Watson Research Center, USA
George Perry, University of Texas at San Antonio, USA
Mark A. Ragan, The University of Queensland, Australia
Raul Rabadan, Columbia University, USA
Jianhua Ruan, University of Texas at San Antonio, USA
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
Philip S. Yu, University of Illinois at Chicago, USA
Erliang Zeng, University of Notre Dame, USA
Xiaoling Zhang, Boston University, Boston, MA
Marketa Zvelebil, Breaktrhough Breast Cancer Research - ICR, UK
Co-Reviewer:
We have two keynotes for the workshop:
1. Title: Non-conventional approach to stem cell image classification
Keynote speaker: Prof Ming Li, University of Waterloo, Canada
Abstract: What do we mean by two images being similar? We will give an ultimate mathematical definition to this question. We will show that our definition is optimal and then apply it to stem cell image classification. Previous methods for stem cell image classification require fluorescent to light up the nuclei (to allow the segmentation algorithms work well). However, the fluorescent interferes with cell growth. Our method does not require this and does not do cell segmentation. Our classification results are shown to be very comparable to the traditional approach.
Biography: Ming Li is a Canada Research Chair in Bioinformatics and a University Professor at the University of Waterloo. He is a fellow of the Royal Society of Canada, ACM, and IEEE. He is a recipient of E.W.R. Steacie Fellowship Award in 1996, the 2001 Killam Fellowship, and the 2010 Killam Prize. Together with Paul Vitanyi they have co-authored the book "An Introduction to Kolmogorov Complexity and Its Applications". He is a co-managing editor of Journal of Bioinformatics and Computational Biology. He is an associate editor-in-Chief of Journal of Computer Science and Technology.2. Title: Combinatorial Biomarker Discovery
Keynote speaker: Prof. Raymond Ng, University of British Columbia, Canada
Abstract: Personalized medicine has been hailed as one of the main directions for medical research in this century. In the first half of the talk, we give an overview on our projects that use gene expression, proteomics and DNA features for biomarker discovery. A biomarker panel is called a combinatorial panel if it includes more than one of the above types of features. In the second half of the talk, we overview some of the challenges in interpreting and analyzing genomics data. The importance of data cleansing and pre-processing is often overlooked. Along this front, we give an overview of several of the techniques we have developed.
Biography: Dr. Raymond Ng is a professor in Computer Science at the University of British Columbia. His main research area for the past two decades is on data mining, with a specific focus on health informatics and text mining. He has published over 150 peer-reviewed publications on data clustering, outlier detection, OLAP processing, health informatics and text mining. He is the recipient of two best paper awards - from 2001 ACM SIGKDD conference, which is the premier data mining conference worldwide, and the 2005 ACM SIGMOD conference, which is one of the top database conferences worldwide. He was one of the program co-chairs of the 2009 International conference on Data Engineering, and one of the program co-chairs of the 2002 ACM SIGKDD conference. He was also one of the general co-chairs of the 2008 ACM SIGMOD conference. He was an editorial board member of the Very large Database Journal and the IEEE Transactions on Knowledge and Data Engineering until 2008. For the past decade, Dr. Ng has co-led several large scale genomic projects, funded by Genome Canada, Genome BC and NSERC. The total amount of funding of those projects well exceeded $40 million Canadian dollars. He now holds the Chief Informatics Officer position of the PROOF Centre of Excellence, which focuses on biomarker development for end-stage organ failures.
For questions about submissions or suggestions/comments about the workshop, please contact Workshop Co-Chairs:
Xiao-Li Li: xlli@i2r.a-star.edu.sg
See-Kiong Ng: skng@i2r.a-star.edu.sg
Jason T.L. Wang: wangj@njit.edu