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Pattern Recognition in Bioinformatics - 8th IAPR International Conference, PRIB 2013, Nice, France, June 17-20, 2013. Proceedings (Paperback, 2013 ed.)
Alioune Ngom, Enrico Formenti, Jin-Kao Hao, Xing-Ming Zhao, Twan van Laarhoven
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R1,527
Discovery Miles 15 270
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 8th IAPR
International Conference on Pattern Recognition in Bioinformatics,
PRIB 2013, held in Nice, France, in June 2013. The 25 revised full
papers presented were carefully reviewed and selected from 43
submissions. The papers are organized in topical sections on
bio-molecular networks and pathway analysis; learning,
classification, and clustering; data mining and knowledge
discovery; protein: structure, function, and interaction; motifs,
sites, and sequence analysis.
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Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings (Paperback, 2014 ed.)
Matteo Comin, Lukas Kall, Elena Marchiori, Alioune Ngom, Jagath Chandana Rajapakse
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R1,276
Discovery Miles 12 760
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 8th IAPR
International Conference on Pattern Recognition in Bioinformatics,
PRIB 2014, held in Stockholm, Sweden in August 2014. The 9 revised
full papers and 9 revised short papers presented were carefully
reviewed and selected from 29 submissions. The focus of the
conference was on the latest Research in Pattern Recognition and
Computational Intelligence-Based Techniques Applied to Problems in
Bioinformatics and Computational Biology.
In the post-genomic era, a holistic understanding of biological
systems and p- cesses,inalltheircomplexity,is
criticalincomprehendingnature'schoreography 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 ?eld. With the ever-increasing
application of lar-
scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass
spectrometry methods, the enormous body of information is growing
rapidly. Bioinformaticians are posed with a large number of di?cult
problems to solve, arising not only due to the complexities in
acquiring the molecular infor- tion but also due to the size and
nature of the generated data sets and/or the limitations of the
algorithms required for analyzing these data. Although the ?eld of
bioinformatics is still in its embryonic stage, the recent
advancements in computational and information-theoretic techniques
are enabling us to c-
ductvariousinsilicotestingandscreeningofmanylab-basedexperimentsbefore
these are actually performed in vitro or in vivo. These in silico
investigations are providing new insights for interpretation and
establishing a new direction for a deeper understanding. Among 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 - going bioinformatics revolution may, in future,
inevitably play a major role in many aspects of medical practice
and/or the discipline of life sciences.
Technology is taking us to a world where myriads of heavily
networked devices interact with the physical world in multiple
ways, and at many levels, from the
globalInternetdowntomicroandnanodevices.
Manyofthesedevicesarehighly mobile and autonomous and must adapt to
the surrounding environment in a totally unsupervised way. A
fundamental research challenge is the design of robust
decentralized c- puting systemsthat arecapableofoperating in
changing environmentsandwith noisy input, and yet exhibit the
desired behavior and response time, under c- straints such as
energy consumption, size, and processing power. These systems
should be able to adapt and learn how to react to unforeseen
scenarios as well as to display properties comparable to social
entities. The observation of nature has brought us many great and
unforeseen concepts. Biological systems are able to handle many of
these challenges with an elegance and e?ciency far beyond
currenthumanartifacts. Basedonthisobservation,
bio-inspiredapproacheshave been proposed as a means of handling the
complexity of such systems. The goal is to obtain methods to
engineer technical systems, which are of a stability and e?ciency
comparable to those found in biological entities. This Special
Issue on Biological and Biologically-inspired Communication
contains the best papers from the Second International Conference
on Bio- Inspired Models of Network, Information, and Computing
Systems (BIONET- ICS 2007). The BIONETICS conference aims to bring
together researchers and scientistsfromseveraldisciplines
incomputerscienceandengineeringwhereb- inspired methods are
investigated, as well as from bioinformatics, to deepen the
information exchange and collaboration among the di?erent
communities
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