| 000 | 04734nam a22005415i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-05630-2 | ||
| 003 | DE-He213 | ||
| 005 | 20200421111853.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 140319s2014 gw | s |||| 0|eng d | ||
| 020 |
_a9783319056302 _9978-3-319-05630-2 |
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| 024 | 7 |
_a10.1007/978-3-319-05630-2 _2doi |
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| 050 | 4 | _aQH324.2-324.25 | |
| 072 | 7 |
_aPSA _2bicssc |
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| 072 | 7 |
_aUB _2bicssc |
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| 072 | 7 |
_aCOM014000 _2bisacsh |
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| 082 | 0 | 4 |
_a570.285 _223 |
| 100 | 1 |
_aMaji, Pradipta. _eauthor. |
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| 245 | 1 | 0 |
_aScalable Pattern Recognition Algorithms _h[electronic resource] : _bApplications in Computational Biology and Bioinformatics / _cby Pradipta Maji, Sushmita Paul. |
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
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| 300 |
_aXXII, 304 p. 55 illus., 10 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _aIntroduction to Pattern Recognition and Bioinformatics -- Part I Classification -- Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA -- Design of String Kernel to Predict Protein Functional Sites Using Kernel-Based Classifiers -- Part II Feature Selection -- Rough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Molecules -- f -Information Measures for Selection of Discriminative Genes from Microarray Data -- Identification of Disease Genes Using Gene Expression and Protein-Protein Interaction Data -- Rough Sets for Insilico Identification of Differentially Expressed miRNAs -- Part III Clustering -- Grouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy Clustering -- Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification -- Possibilistic Biclustering for Discovering Value-Coherent Overlapping d -Biclusters -- Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images. | |
| 520 | _aRecent advances in high-throughput technologies have resulted in a deluge of biological information. Yet the storage, analysis, and interpretation of such multifaceted data require effective and efficient computational tools. This unique text/reference addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The book reviews both established and cutting-edge research, following a clear structure reflecting the major phases of a pattern recognition system: classification, feature selection, and clustering. The text provides a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Topics and features: Reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics Integrates different soft computing and machine learning methodologies with pattern recognition tasks Discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets Presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images Includes numerous examples and experimental results to support the theoretical concepts described Concludes each chapter with directions for future research and a comprehensive bibliography This important work will be of great use to graduate students and researchers in the fields of computer science, electrical and biomedical engineering. Researchers and practitioners involved in pattern recognition, machine learning, computational biology and bioinformatics, data mining, and soft computing will also find the book invaluable. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aRadiology. | |
| 650 | 0 | _aData mining. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aPattern recognition. | |
| 650 | 0 | _aBioinformatics. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aComputational Biology/Bioinformatics. |
| 650 | 2 | 4 | _aPattern Recognition. |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
| 650 | 2 | 4 | _aImaging / Radiology. |
| 700 | 1 |
_aPaul, Sushmita. _eauthor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319056296 |
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-05630-2 |
| 912 | _aZDB-2-SCS | ||
| 942 | _cEBK | ||
| 999 |
_c56223 _d56223 |
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