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Gene Network Inference

Verification of Methods for Systems Genetics Data

  • Alberto de la Fuente

Table of contents

  1. Front Matter
    Pages i-xi
  2. Andrea Pinna, Nicola Soranzo, Alberto de la Fuente, Ina Hoeschele
    Pages 1-8
  3. David Allouche, Christine Cierco-Ayrolles, Simon de Givry, Gérald Guillermin, Brigitte Mangin, Thomas Schiex et al.
    Pages 9-31
  4. Gennaro Gambardella, Roberto Pagliarini, Francesco Gregoretti, Gennaro Oliva, Diego di Bernardo
    Pages 49-61
  5. Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
    Pages 63-85
  6. Pegah Tavakkolkhah, Robert Küffner
    Pages 87-105

About this book

Introduction

This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement.

The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.

Keywords

Gene Network Inference Gene Networks Network Inference Systems Biology Systems Genetics

Editors and affiliations

  • Alberto de la Fuente
    • 1
  1. 1.Leibniz-Institute for Farm Animal BiologyDummerstorfGermany

Bibliographic information

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