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TC-20 Committee Leardership Board
(Chair) Monash University Australia
(Vice Chair) The Pennsylvania State University USA
(Past Chair) Nanyang Technological University Singapore
(PRIB 2009 General Chair) The University of Sheffield United Kingdom
(Web Chair) University of Windsor Canada
(Information Chair) National
Institute of Biomedical Innovation Japan TC-20 Executive Vladimir Brusic
Dana-Farber Cancer Institute USA
Natural Selection Inc. USA
University of Melbourne Australia
La Trobe University Australia
Auckland University of Technology New Zealand
Russian Academy of Sciences Russia
Vrije University The Netherlands
University of Arkansas at Little Rock USA
Indian Statistical Institute India
Kent State University USA
Massachussetts Institute of Technology USA
Simon Fraser University Canada
National University of Singapore Singapore
Wellcome Trust Sanger Institute United Kingdom
Georgia State University USA |
Goal The goal of the IAPR 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, the IAPR TC-20 will expand its
activities in the following areas: 1. Education: through the website,
educational materials such as lecture notes, tutorials, etc., will be made
available. 2. Research: a database of
bioinformatics applications, literature, tools, and benchmark datasets will
be maintained. 3. Events: organize PRIB
conferences, special sessions at conferences, special issues of journals, and
competitions, etc. Background In the post-genomic era,
a holistic understanding of biological systems and processes, in all their
complexity, is critical in comprehending nature’s choreography of life. As a
result, bioinformatics involving its two main disciplines, namely the life
sciences and the computational sciences, is fast becoming a very promising
multidisciplinary research field. With the ever increasing application of
large-scale high-throughput technologies, such as gene or protein microarrays
and mass spectrometry methods, the enormous body of information is growing
rapidly. Bioinformaticians are posed with a large number of difficult
problems to solve, arising not only due to the complexities in acquiring the
molecular information but also due to the size and nature of the generated
data sets and/or the limitations of the algorithms required for analyzing
this data. Although the field of bioinformatics is still in its embryonic
stage, the recent advancements in computational and information-theoretic
techniques are enabling us to conduct various in silico testing and screening of many lab-based experiments
before these are actually performed in vitro or in vivo. These in silico investigations are providing new insights for
interpretation and establishing new direction for a deeper understanding.
Amongst the various advanced computational methods currently being applied to
such studies, the pattern recognition techniques are mostly found to be at the core of the
whole discovery process for apprehending the underlying biological knowledge.
Thus, we can safely surmise that the ongoing bioinformatics revolution may, in future, inevitably play a major role
in many aspects of medical practice, and/or the discipline of life sciences. 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 ·
Computational and comparative genomics. ·
Functional genomics ·
Structural bioinformatics and proteomics ·
Cheminformatics, chemigenomics ·
Systems biology, pathway analysis ·
Phylogenic analysis of species, sequences, structures, etc ·
Immunoinformatics ·
Neuroinformatics ·
Drug discovery, pharmacogenomics ·
Medical informatics ·
Molecular and cellular imaging Pattern Recognition for
Bioinformatics 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. 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 sub-cellular
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. PRIB
Conferences The International Conference on Pattern
Recognition in Bioinformatics (PRIB) is the major event of IAPR TC-20,
organized. The aim of this conference
is to provide an opportunity to academia, researchers, scientists and
industry professionals to present their latest research in pattern
recognition and computational intelligence based techniques applied to
problems in bioinformatics and computational biology. It also provides them
with an excellent forum to interact with each other and share experiences. 1.
Fifth IAPR
International Conference on Pattern Recognition in Bioinformatics (PRIB 20010), Nijmegen, The Netherlands, September 22 - 24, 2010. 2.
Fourth IAPR
International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, United
Kingdom, September 7 - 9, 2009. 3.
Third IAPR
International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne,
Australia, October 15 – 17, 2008. 4.
Second IAPR
International Workshop on Pattern Recognition in Bioinformatics (PRIB
2007), Singapore, October 1 – 2, 2007. 5.
First
International Workshop on Pattern Recognition in Bioinformatics (PRIB
2006), Hong Kong, China, August 20, 2006. Special
Sessions PRIB 2009 ·
Machine Learning for Integrative Genomics (J. Hollmen, M.
Dugas and S. Bicciato) WCCI – IJCNN 2008 ·
Analysis
of gene and protein expression data (V. Kuznetsov and J. Rajapakse) ·
Prediction
of protein structures and features (S. Ahmad and M. Gromiha) Upcoming Publications 1. Special Issue on “Pattern Discovery
from Bioinformatics Data”, IEEE
Engineering in Medicine and Biology Magazine. To appear in 2009. 2. Special Issue on “Pattern Recognition in
Bioinformatics”, Pattern Recognition
Letters. To appear in 2010. 3. Special Issue on “Computational Intelligence
in Bioinformatics”, Neurocomputing
Journal. To appear in 2010. Past Publications 4. V. Kadirkamanathan, G.
Sanginetti, M. Girolami, M. Niranjan, and J. Noirel, (Eds.), Pattern
Recognition in Bioinformatics: Second IAPR International Workshop, PRIB 2009,
Sheffield, UK, Lecture Notes in Computer Science (Sub-series: Lecture
Notes in Computer Science), Vol. 5780, Sep 2009, ISBN
978-3-642-04030-6. 5. M. Chetty, A. Ngom, and S.
Ahmad, (Eds.), Pattern
Recognition in Bioinformatics: Second IAPR International Workshop, PRIB 2008,
Melbourne, Australia, Lecture Notes in Computer Science (Sub-series:
Lecture Notes in Computer Science), Vol. 5265, Oct 2008, ISBN
978-3-540-88434-7. 6. IAPR
Newsletter article, Volume 30, Number 1, January 2008 7. 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 8. 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 9. IAPR Newsletter article, Volume 27, Number 2, April 2005 Annual
Reports 2008-09; 2007-08; 2006-07; 2005-06; 2004-05 Membership The
IAPR TC-20 includes the PRIB Technical Committee,
membership of which is open to all those who have interest in bioinformatics
research. The membership to the TC-20 Committee is by invitation from the
TC-20 Chair. The TC-20 Committee Membership has a world-wide representation
and makes decisions on the TC-20 activities. Enquiries on membership for IAPR
TC-20 Committee or PRIB Technical Committee should be directed via email to
the TC-20 Chair: Dr. Madhu Chetty (madhu ‘dot’
chetty ‘at’ infotech ‘dot’ monash ‘dot’ edu ‘dot’ au). For web
queries, contact the TC-20 Web Chair: Dr. Alioune Ngom (angom ‘at’ cs ‘dot’ uwindsor ‘dot’ ca). For
information queries, contact the TC-20 Information Chair, Dr. Shandar Ahmad (shandar ‘at’ netasa ‘dot’ org). |
Selected
Publications of IAPR TC-20 Members
… … … coming soon
Tutorial
Presentations
… … … coming soon
Educational
Material
… … … coming soon
Bioinformatics Softwares
… … … coming soon
Benchmark
Data Sets
… … … coming soon
Others
… … … comning soon
Last edited on June 27, 2009