Produktbild: Scalable Pattern Recognition Algorithms
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Scalable Pattern Recognition Algorithms Applications in Computational Biology and Bioinformatics

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.08.2016

Abbildungen

XXII, 304 p. 55 illus., 10 illus. in color.

Verlag

Springer

Seitenzahl

304

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

499 g

Auflage

Softcover reprint of the original 1st ed. 2014

Sprache

Englisch

ISBN

978-3-319-37965-4

Beschreibung

Rezension

From the book reviews:

“This book provides unique insights into how various soft computing and machine learning methods can be formulated and used in building efficient pattern recognition models. … This is a great resource to students and researchers in the fields of computer science, electrical and biomedical engineering. The author has explained the complex ideas through numerous examples which make conceptualization easy. … The well-organized chapters as well as use of different notations and typescripts make it a user-friendly reference.” (Parthiv Amin, Doody’s Book Reviews, August, 2014)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.08.2016

Abbildungen

XXII, 304 p. 55 illus., 10 illus. in color.

Verlag

Springer

Seitenzahl

304

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

499 g

Auflage

Softcover reprint of the original 1st ed. 2014

Sprache

Englisch

ISBN

978-3-319-37965-4

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Scalable Pattern Recognition Algorithms

  • Introduction 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.