Data Clustering and Bioinformatics
Organized by: Vassilis P. Plagianakos* and Dimitris K. Tasoulis**
*University of Central Greece
**Imperial College London

Description and Scope
Traditionally Data Clustering has played a key role in the scientific attempts to transform data to knowledge. Over the past few decades rapid developments in genomic and other molecular research technologies and developments in information technologies have combined to produce a tremendous amount of data related to molecular biology. As a natural consequence, a lot of research has been devoted to the adoption of Data Clustering methods to analyse this new wealth of data. In this stream, the "Data Clustering and Bioinformatics" Special Session as part of the "2010 International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics", aims to act as a forum for new ideas and paradigms. Of particular interest are Data Clustering approaches for the analysis of biological data, as well as Computational Intelligence algorithms applied to the same real life problems.

Topics
Technical areas addressed by this special session include, but are not limited to:

• Feature and phenotype discovery
• Class discovery
• Gene expression clustering
• Subspace clustering
• Biclustering
• Iterative feature selection and data clustering - Gene Shaving
• Clustering/classification of bioimages or patterns derived from bioimages
• Curse of dimensionality and microarray data clustering
• Cluster visualisation and bioinformatics
• Computational Intelligence algorithms for Bioinformatics

More Details in this link



Intelligent Clinical Decision Support Systems (i-CDSS)
Organized by: Alexandru Floares* and Leif Peterson**
*SAIA – OncoPredict & Solutions of Artificial Intelligence Applications, Cluj-Napoca, Romania
**Methodist Hospital Research Institute Houston, TX, USA

Description and Scope

Medicine and its scientific and technological background are rapidly and profoundly changing in the Information Age. The impact of the biomedical equipment used to produce and collect laboratory data, signals and images is impressive. New high-throughput technologies have appeared and existing technologies have been radically transformed. For example, techniques such as electroencephalography or radiography, which two decades ago seemed to reach a bottleneck, came to a new life, and their importance as diagnostic tools is continuously increasing. As a result, our capacity to produce and record huge amount of complex biomedical data - patient conditions, diagnostic tests, treatments, outcomes, different kind of "omics" data (genomics/proteomics, etc.), biosignals and images – have dramatically increased. These data provide an unprecedented source of information that can lead to potential improvements in medical diagnostic, prognostic, and individualized, optimized treatment strategy.
However, much more work is required. Although technology has brought about tremendous new sources of important biomedical data, we have not moved very far with regard to extracting the knowledge that lies latent in this data. In recent years, modern computer science has brought forth tremendous new tools such as artificial neural networks, decision trees, fuzzy logic, evolutionary computing, support vector machines, and the like.  Also, the prevailing reductionist view by its own result seems to lead biomedicine to the systemic view.  In some recent studies, omics data are placed in a pathways/networks context, but most often only the structure of these networks is investigated – leaving the more complex dynamics as an unresolved challenge for dynamical systems analysis and control theoretic applications.

Yet the professional, political, and social issues that separate the medical community and the intelligent computing and dynamical systems communities have delayed the serious application of these tools to accelerate progress in translational medicine, genome-to-phenome, bench-to-bedside and clinical trials, ultimately hindering implementation in public health programs.

The mission of these annually held special sessions is to develop a foundation for Knowledge Based Medicine (KBM), the next step beyond Evidence Based Medicine (EBM), combining computational intelligence and dynamical systems.

Topics

We encourage papers describing new or applying existing intelligent computing methods to real and practical medical and health-care problems in which the biomedical problems are central. The topics of interest include, but are not limited to:

• disease modeling, diagnosis and prevention
• prognostic and treatment outcome predictions
• patient monitoring and alarm systems
• optimization of patient-management workflows
• biomedical data\text\web mining and data visualization
• integration of biomedical data sources and domain knowledge
• translational bioinformatics (genomics, proteomics, etc.)
• biomedical signals and images processing
• design of clinical trials

Submissions addressing theoretical problems should clearly outline the expected impact of the proposed solution to the medical field.

Audience

• Medical informaticians
• Bioinformaticians
• Neuroinformaticians
• Computer scientists
• Statisticians
• Molecular biologists and medical doctors
• Biomedical and electrical engineers
• Other researchers and developers

Session Chairs

Alexandru Floares, SAIA – OncoPredict & Solutions of Artificial Intelligence Applications, Cluj-Napoca, Email: alexandru _ dot  _ floares _ at _ iocn _ dot _ ro

Leif Peterson, Center for Biostatistics, The Methodist Hospital Research Institute, Houston, Texas USA,  E-mail: peterson _ dot _ leif _ at _ ieee _ dot _ org

Program Committee



Important Dates

Manuscript submission deadline: August 09, 2010
Notification of acceptance: August 15, 2010
Camera-ready papers due: August 30, 2010
Conference:   September 16-18, 2010


Submissions (Instructions to Authors)

Papers submitted for this session should be submitted by August 09, 2010.  To submit a paper, please use the following steps:

1. The authors should send the papers to This e-mail address is being protected from spambots. You need JavaScript enabled to view it
   

2. Authors of the accepted papers shoul pay th conference fee before August 23th. Please see instructions on Fees page of this web site.
   

Prepare your paper in LATEX following the guidelines available at http://cibb10.pa.icar.cnr.it/images/cibb-sample-v.1.2.zip. The size of the paper should not exceed 10 pages in that format.

Proceedings

Accepted papers will be published in the compact disk of conference proceedings with ISBN.

A selection of papers presented at CIBB 2010 will be published in revised extended form as a post conference volume.  Revised papers of the previous editions of CIBB were published in the Springer Verlag LNBI/LNCS (see http://www.springer.com/series/538 ).