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010 _a 2019762256
020 _a9783319608167
024 7 _a10.1007/978-3-319-60816-7
_2doi
035 _a(DE-He213)978-3-319-60816-7
040 _aDLC
_beng
_epn
_erda
_cDLC
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2bicssc
072 7 _aUYQ
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082 0 4 _a006.3
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245 0 0 _a11th International Conference on Practical Applications of Computational Biology & Bioinformatics /
_cedited by Florentino Fdez-Riverola, Mohd Saberi Mohamad, Miguel Rocha, Juan F. De Paz, Tiago Pinto.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _a1 online resource (XIV, 330 pages 97 illustrations)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v616
505 0 _aProcessing 2D gel electrophoresis images for efficient Gaussian mixture modeling -- Development of text mining tools for information retrieval from patents -- Multidimensional Feature Selection and Interaction Mining with Decision Tree based ensemble methods -- Study of the Epigenetic Signals in the Human Genome -- An Ensemble Approach for Gene Selection in Gene Expression Data -- Dissimilar Symmetric Word Pairs in the Human Genome.
520 _aBiological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. The PACBB'17 conference was intended to contribute to this effort and promote this fruitful interaction, with a technical program that included 39 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Further, the conference promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists).
588 _aDescription based on publisher-supplied MARC data.
650 0 _aArtificial intelligence.
650 0 _aBioinformatics.
650 0 _aComputational intelligence.
650 1 4 _aComputational Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T11014
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 2 4 _aComputational Biology/Bioinformatics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I23050
700 1 _aDe Paz, Juan F,
_eeditor.
700 1 _aFdez-Riverola, Florentino,
_eeditor.
700 1 _aMohamad, Mohd Saberi,
_eeditor.
700 1 _aPinto, Tiago,
_eeditor.
700 1 _aRocha, Miguel,
_eeditor.
776 0 8 _iPrint version:
_t11th International Conference on Practical Applications of Computational Biology & Bioinformatics.
_z9783319608150
_w(DLC) 2017943012
776 0 8 _iPrinted edition:
_z9783319608150
776 0 8 _iPrinted edition:
_z9783319608174
830 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v616
906 _a0
_bibc
_corigres
_du
_encip
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999 _c3
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