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Autor(en): 
  • Datta Sujay
  • Mitra Sushmita
  • Perkins Theodore
  • Michailidis George
  • Introduction to Machine Learning and Bioinformatics 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2019  
    Genre:  Wirtschaft / Recht 
     
    advanced machine learning applications / Automatic control engineering / Bayesian inference methods / Biology, life sciences / BUSINESS & ECONOMICS / Statistics / COMPUTERS / Machine Theory / environmental science, engineering & technology / Environmental science, engineering and technology
    ISBN:  9780367387235 
    EAN-Code: 
    9780367387235 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Gewicht:  453 gr 
    Seiten:  384 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Lucidly Integrates Current Activities

    Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other.

    Examines Connections between Machine Learning & Bioinformatics

    The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website.

    Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems

    Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today's biological experiments.

      



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