Return to home page
Searching: Muskingum library catalog
Some OPAL libraries remain closed or are operating at reduced service levels. Materials from those libraries may not be requestable; requested items may take longer to arrive. Note that pickup procedures may differ between libraries. Please contact your library for new procedures, specific requests, or other assistance.
  Previous Record Previous Item Next Item Next Record
  Reviews, Summaries, etc...
EBOOK
Title Gene network inference : verification of methods for systems genetics data / Alberto de la Fuente, editor.
Imprint Heidelberg : Springer, 2013.

LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Subject Genetics -- Data processing.
Systems biology.
Bioinformatics.
Gene Regulatory Networks -- genetics.
Algorithms.
Gene Expression Profiling.
Oligonucleotide Array Sequence Analysis.
Systems Biology -- methods.
Alt Name Fuente, Alberto de la (Geneticist),
Description 1 online resource (xi, 130 pages) : illustrations (some color)
polychrome rdacc
Contents Simulation of the Benchmark Datasets -- A Panel of Learning Methods for the Reconstruction of Gene Regulatory Networks in a Systems Genetics Context -- Benchmarking a simple yet effective approach for inferring gene regulatory networks from systems genetics data -- Differential Equation based reverse-engineering algorithms: pros and cons -- Gene regulatory network inference from systems genetics data using tree-based methods -- Extending partially known networks -- Integration of genetic variation as external perturbation to reverse engineer regulatory networks from gene expression data -- Using Simulated Data to Evaluate Bayesian Network Approach for Integrating Diverse Data.
Summary 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.
Bibliography Note Includes bibliographical references at the end of each chapters.
Note Online resource; title from PDF title page (SpringerLink, viewed January 6, 2014).
Print version record.
ISBN 9783642451614 (electronic bk.)
3642451616 (electronic bk.)
3642451608
9783642451607
9783642451607
ISBN/ISSN 10.1007/978-3-642-45161-4
OCLC # 869218626
Additional Format Print version: Gene network inference : verification of methods for systems genetics data. Heidelberg, Germany : Springer, 2013 xi, 130 pages 9783642451607


If you experience difficulty accessing or navigating this content, please contact the OPAL Support Team