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Herausgeber: 
  • Albert Y. (University of Western Australia) Zomaya
  • Mourad (University of Tunis El Manar, Tunisia) Ell
  • Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Januar 2014  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Bioinformatics & Computational Biology / Bioinformatik / Biowissenschaften / Data Mining / Data Mining Statistics / Life Sciences / Statistics / Statistik
    ISBN:  9781118132739 
    EAN-Code: 
    9781118132739 
    Verlag:  John Wiley & Sons Inc 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Wiley Series in Bioinformatics  
    Dimensionen:  H 259 mm / B 185 mm / D 58 mm 
    Gewicht:  2173 gr 
    Seiten:  1192 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data-and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)-providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing-also known as data mining-and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING * Part A: Biological Data Management * Part B: Biological Data Modeling * Part C: Biological Feature Extraction * Part D Biological Feature Selection BIOLOGICAL DATA MINING * Part E: Regression Analysis of Biological Data * Part F Biological Data Clustering * Part G: Biological Data Classification * Part H: Association Rules Learning from Biological Data * Part I: Text Mining and Application to Biological Data * Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.

      



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