IAPR-TC20 logo.JPG




Executive Board


Raj Acharya                        Co-Chair

Shandar Ahamad               Information

Madhu Chetty                    Chair

Alioune Ngom                   Publicity

Jagath C. Rajapakse           PRIB Steering Committee



TC-20 Committee Members

The goal of TC20 is to bring together pattern recognition scientists and life scientists to find solutions to problems in bioinformatics, and foster multidisciplinary research in the pattern recognition community.


In order to achieve its goal, TC-20 will expand its activities in the following areas:

Education: through the website, educational materials such as lecture notes, tutorials, etc., will be made available.

Research: a database of bioinformatics applications, literature, tools, and benchmark datasets will be maintained.

Events: organize PRIB conferences, special sessions at conferences, special issues of journals, and competitions, etc.



The past decade has witnessed an explosion and implosion of the amount and complexity of bioinformatics data such as DNA and protein sequences, gene and protein expressions, structures, pathways, genetic information, biomedical text data, and molecular images. Although the analyses of these data involve pattern recognition and data mining, novel and efficient data analysis techniques are yet to be discovered to realize their true potential.

Bioinformatics is aimed at discovering knowledge from life sciences data with the aid of Information Technology, to find answers to unresolved problems in biology.  One of the important discoveries of pattern recognition in bioinformatics is that specific patterns of our genomes and proteomes are able to tell our characters and how prone we are for certain diseases. In the coming years, medical practitioners will be able to personalize our medication by just looking at these patterns.


Research Interests

Pattern recognition in the following areas:

  • Computational and comparative genomics
  • Functional genomics
  • Structural genomics and proteomics
  • Cheminformatics, chemigenomics
  • Systems biology, pathway analysis
  • Synthetic biology
  • Immunoinformatics
  • Pharmacogenomics, drug discovery
  • Medical informatics
  • Biological imaging


Pattern Recognition for Bioinformatics

DNA molecules store the blueprint of cell function. Information stored in DNA, a chain of four nucleotides (A, T, G, and C), is first transcribed to mRNA and then translated to the functional form of life, proteins. The initiation of translation or transcription process depends on the presence of specific signals and patterns, referred to as motifs, present in DNA and RNA. Research on in silico detection of specific patterns of DNA sequences such as genes, binding sites, and promoters, leads to better understanding of molecular level function of a cell. Comparative genomics focus on comparison of different genomes to find conserved patterns or significant mutations over the evolution, which could possess some functional significance. Construction of evolutionary trees is useful to infer how genome and proteome are evolved and branch across species by ways of a complete library of motifs and genes.

A protein’s functionality or interaction with other proteins is mainly determined by its 3-D structure. Prediction of protein’s 3-D structure from its 1-D amino-acid sequence remains an important problem in structural genomics; protein-protein interactions are responsible for most molecular functions in living cells. Computational modeling and visualization tools of 3-D structures of proteins and interaction help biologists to infer cellular activities.

The challenge in functional genomics is to analyze gene expressions accumulated by microarray techniques to discover co-regulated genes and thereby gene regulatory networks. Discovering and understanding how genes and proteins interact in specific pathways are gateways to systems biology. Molecular and cellular imaging provides techniques for in vivo sensing or imaging of cellular events such as movement of cells and subcellular localization of proteins. Potential techniques to fuse and integrate different types of life sciences data are yet to be realized.

The ever expanding knowledge of biomedical and phenotype data, combined with genotypes, is becoming difficult to be analyzed by traditional methods. Advanced data mining techniques, where the use of metadata for constructing precise descriptors of medical concepts and procedures, are required in the field of medical informatics. The vast amount of biological literature is posing new challenges in the field of text mining. These text mining techniques along with the aid of information fusion methods could help find pathways and interaction networks.

Today, high throughput and high content screening techniques allow biologists to gather data at an unprecedented rate. However, pattern recognition techniques to make inferences from these data are not evolving at a rate sufficient to meet the demand.


Annual Reports


2008-09; 2007-08; 2006-07;  2005-06;  2004-05


PRIB Conference

International Conference on Pattern Recognition in Bioinformatics (PRIB) is the major event of TC-20.

    PRIB 2010, Nijmegen, The Netherlands

    PRIB 2009, Sheffield, UK

    PRIB 2008, Melbourne, Australia

    PRIB 2007, Singapore

    PRIB 2006, Hong Kong, China


PRIB Conferences are held under the guidance of PRIB Steering Committee. Your proposal to hold PRIB in 2011 should be sent to the PRIB Secretariat and will be evaluated by the Steering Committee.


The PRIB Committee membership is open to the participants of PBIR conferences. Enquiries on IAPR TC-20 or PRIB Membership should be directed to the PRIB Secretariat.

PRIB Committee Members


Special Sessions


    Analysis of gene and protein expression data

    Prediction of protein structures and features




·         V. Kadirkamanathan, G. Sanguinetti, M.  Girolami, M. Niranjan, J. Noirel,  (Eds.), Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009, Proceedings, Lecture Notes in Computer Science (Subseries: Lecture Notes in Bioinformatics) , Vol. 5780, 2009, XIV, 452 p., ISBN: 978-3-642-04030-6

·         Special Issue on “Pattern Discovery in Bioinformatics”, IEEE Engineering in Medicine and Biology Magazine, Vol. 28, No. 4, July/August Issue, 2009; Guest Editor: J. C. Rajapakse

·         M. Chetty, A. Ngom, S. Ahmad, (Eds.), Pattern Recognition in Bioinformatics: Third IAPR International Conference,  PRIB 2008, Melbourne, Lecture Notes in Computer Science (Sub-series: Lecture Notes in Computer Science), Vol. 5265, Oct 2008

·         IAPR Newsletter, Volume 30, Number 1, January 2008

·         J. C. Rajapakse, B. Schmidt, and G. Volkert (Eds.) Pattern Recognition in Bioinformatics: Second IAPR International Workshop, PRIB 2007, Singapore, Lecture Notes in Computer Science (Sub-series: Lecture Notes in Bioinformatics), Vol. 4774, Oct 2007, ISBN 978-3-540-75285-1

·         J. C. Rajapakse, L. Wong, and R. Acharya (Eds.) Pattern Recognition in Bioinformatics: International Workshop, PRIB 2006, Hong Kong, Lecture Notes in Computer Science (Sub-series: Lecture Notes in Bioinformatics), Vol. 4146, August 2006, ISBN 3-540-37446-9, 183 pages

·         IAPR Newsletter, Volume 27, Number 2, April 2005



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Last modified on 02/09/09