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Reverse Engineering Biological Networks: Opportunities and Challenges in
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Reverse Engineering Biological Networks: Opportunities and Challenges in Computational Methods for Pathway Inference, Volume 1118 Paperback - 2007 - 1st Edition

by Gustavo Stolovitzky (Editor); Andrea Califano (Editor)


From the publisher

Computational biologists are striving to "reverse engineer" the underlying networks of interactions between the molecules in the cell. This volume and the conference it reports on attempt a systematic evaluation of reverse engineering methods. The DREAM project brings together a diverse group of researchers to clarify potentials and limitations of the enterprise of reverse engineering cellular networks. An important aspiration of the project is to compare the effectiveness of different methods in reverse engineering biological networks. Evaluating this requires a "gold standard" network for which at least the true topology of connections is known. Many participants, especially the computational biologists, believe that synthetic networks are good candidates for this purpose because, at least for now, only they can be described with certainty. Experimental biologists, however, worry that unless the project addresses real biological networks, it could evolve into a mathematical exercise with little impact on biology. These and other ideas are discussed.

NOTE: Annals volumes are available for sale as individual books or as a journal. For information on institutional journal subscriptions, please visit www.blackwellpublishing.com/nyas.

ACADEMY MEMBERS: Please contact the New York Academy of Sciences directly to place your order (www.nyas.org). Members of the New York Academy of Science receive full-text access to the Annals online and discounts on print volumes. Please visit http: //www.nyas.org/MemberCenter/Join.aspx for more information about becoming a member

From the rear cover

Computational biologists are striving to "reverse engineer" the underlying networks of interactions between the molecules in the cell. This volume and the conference it reports on attempt a systematic evaluation of reverse engineering methods. The DREAM project brings together a diverse group of researchers to clarify potentials and limitations of the enterprise of reverse engineering cellular networks. An important aspiration of the project is to compare the effectiveness of different methods in reverse engineering biological networks. Evaluating this requires a "gold standard" network for which at least the true topology of connections is known. Many participants, especially the computational biologists, believe that synthetic networks are good candidates for this purpose because, at least for now, only they can be described with certainty. Experimental biologists, however, worry that unless the project addresses real biological networks, it could evolve into a mathematical exercise with little impact on biology. These and other ideas are discussed.

NOTE: Annals volumes are available for sale as individual books or as a journal. For information on institutional journal subscriptions, please visit www.blackwellpublishing.com/nyas.

ACADEMY MEMBERS: Please contact the New York Academy of Sciences directly to place your order (www.nyas.org). Members of the New York Academy of Science receive full-text access to the Annals online and discounts on print volumes. Please visit www.nyas.org/membership/main.asp for more information about becoming a member.

Details

  • Title Reverse Engineering Biological Networks: Opportunities and Challenges in Computational Methods for Pathway Inference, Volume 1118
  • Author Gustavo Stolovitzky (Editor); Andrea Califano (Editor)
  • Binding Paperback
  • Edition number 1st
  • Edition 1
  • Pages 452
  • Volumes 1
  • Language ENG
  • Publisher Wiley-Blackwell
  • Date 2007
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • ISBN 9781573316897 / 157331689X
  • Library of Congress subjects Computational biology, Biology - Mathematical models
  • Library of Congress Catalog Number 2007039308
  • Dewey Decimal Code 570.151

About the author

Gustavo Stolovitzky is the editor of Reverse Engineering Biological Networks: Opportunities and Challenges in Computational Methods for Pathway Inference, Volume 1118, published by Wiley. Andrea Califano is the editor of Reverse Engineering Biological Networks: Opportunities and Challenges in Computational Methods for Pathway Inference, Volume 1118, published by Wiley.

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