The challenges of systems biology: community efforts to harness biological complexity
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston, Mass.
Blackwell
2009
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| Schriftenreihe: | Annals of the New York Academy of Sciences
1158 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XII, 316 S. Ill., graph. Darst. |
| ISBN: | 9781573317511 1573317519 |
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Titel: The challenges of systems biology
Autor: Stolovitzky, Gustavo
Jahr: 2009
ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
Volume 1158
The Challenges of Systems Biology
Community Efforts to Harness Biological Complexity
Editors
Gustavo Stolovitzky, Pascal Kahlem, and Andrea Califano
This volume is the result of the Second Dialogue on Reverse Engineering Assessment and Methods
(DREAM2) Challenges, posed to the systems biology community between July and October, 2007; the
DREAM2 Conference, held on December 3-4, 2007 at the New York Academy of Sciences in New York;
and the ENFIN-DREAM Conference, Assessment of Computational Methods in Systems Biology, held on
April 28-29, 2008 in Madrid, Spain.
CONTENTS
Preface. By Gustavo Stolovitzky, Pascal Kahlem, and Andrea Califano ix
Parti.
Selected Papers from the ENFIN-DREAM Joint Conference
Ranking Genes by Their Co-expression to Subsets of Pathway Members. By
Priit Adler, Hedi Peterson, Phaedra Agius, Juri Reimand, and Jaak Vilo . 1
Creating Reference Datasets for Systems Biology Applications Using Text Mining.
By Martin Krallinger, Ana Maria Rojas, and Alfonso Valencia 14
Selected Papers from the DREAM2 Conference
Transcriptional Modules and Regulatory Networks
The Condition-Dependent Transcriptional Network in Escherichia coli. By Karen
Lemmens, Tijl De Bie, Thomas Dhollander, Pieter Monsieurs, Bart De
Moor, Julio Collado-Vides, Kristof Engelen, and Kathleen Marchal 29
Reverse-Engineering Transcriptional Modules from Gene Expression Data. By
Tom Michoel, Riet De Smet, Anaghajoshi, Kathleen Marchal, and Yves Van
de Peer 36
Signaling and Metabolic Networks
Specification of Spatial Relationships in Directed Graphs of Cell Signaling
Networks. By Azi Lipshtat, Susana R. Neves, and Ravi Iyengar 44
v
vi Annals of the New York Academy of Sciences
Uncovering Metabolic Objectives Pursued by Changes of Enzyme Levels. By
Sabrina Hoffmann and Hermann-Georg Holzhiitter 57
Biological Network Models
Modeling of Gene Regulatory Network Dynamics Using Threshold Logic. By
Tejaswi Gowda, Sarma Vrudhula, and Seungchan Kim 71
Global Robustness and Identifiability of Random, Scale-Free, and Small-World
Networks. By Yunchen Gong and Zhaolei Zhang 82
Reverse Engineering Algorithms
The Five-Gene-Network Data Analysis with Local Causal Discovery Algorithm
Using Causal Bayesian Networks. By Changwon Yoo and Erik M. Brilz 93
Combining Multiple Results of a Reverse-Engineering Algorithm: Application to
the DREAM Five-Gene Network Challenge. By Daniel Marbach, Claudio
Mattiussi, and Dario Floreano 102
Network Inference by Combining Biologically Motivated Regulatory Constraints
with Penalized Regression. By Fabio Parisi, Heinz Koeppl, and Felix Naef . 114
Computation Tools for Reverse Engineering
A Gene Network Simulator to Assess Reverse Engineering Algorithms. By
Barbara Di Camillo, Gianna Toffolo, and Claudio Cobelli 125
A Network Inference Workflow Applied to Virulence-Related Processes in
Salmonella typhimurium. By Ronald C. Taylor, Mudita Singhal, Jennifer Weller,
Saeed Khoshnevis, Liang Shi, and Jason McDermott 143
Part II.
Best Performer Papers from the DREAM2 Challenges
Overview of the DREAM2 Challenges
Lessons from the DREAM2 Challenges: A Community Effort to Assess Biological
Network Inference. By Gustavo Stolovitzky, Robert J. Prill, and Andrea
Califano 159
The BCL6 Target Discovery Challenge Best Performer Papers
DREAM2 Challenge: Integrated Multi-Array Supervised Learning Algorithm for
BCL6 Transcriptional Targets Prediction. By W.H. Lee, V Narang, H. Xu,
F. Lin, K.C. Chin, and W.K. Sung 196
A Data Integration Framework for Prediction of Transcription Factor Targets: A
BCL6 Case Study. By Matti Nykter, Harri Lahdesmaki, Alistair Rust,
Vesteinn Thorsson, and Ilya Shmulevich 205
Contents vii
Inferring Direct Regulatory Targets of a Transcription Factor in the DREAM2
Challenge. By Vinsensius B. Vega, Xing Yi Woo, Habib Hamidi, Hock
Chuan Yeo, Zhen Xuan Yeo, Guillaume Bourque, and Neil D. Clarke 215
The Protein—Protein Interaction Challenge Best Performer Paper
A Probabilistic Graph-Theoretic Approach to Integrate Multiple Predictions for
the Protein-Protein Subnetwork Prediction Challenge. By Hon Nian Chua,
Willy Hugo, Guimei Liu, Xiaoli Li, Limsoon Wong, and See-Kiong Ng . 224
The Five Gene Network Challenges Best Performer Papers
Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene
Networks. By Daniel Marbach, Claudio Mattiussi, and Dario Floreano 234
Inferring Gene Networks: Dream or Nightmare? Part 1: Challenges 1 and 3. By
Angela Baralla, Wieslawa I. Mentzen, and Alberto de la Fuentc 246
The in Silico Network Challenges Best Performer Papers
NIRest: A Tool for Gene Network and Mode of Action Inference. By Mario
Lauria, Francesco Iorio, and Diego di Bernardo 257
Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis
Functions. By Mika Gustafsson, Michael Hornquist, Jesper Lundstrom, Johan
Bjorkegren, and Jesper Tegner 265
Prediction of Pairwise Gene Interaction Using Threshold Logic. By Tejaswi
Gowda, Sarma Vrudhula, and Seungchan Kim 276
Inferring Gene Networks: Dream or Nightmare? Part 2: Challenges 4 and 5. By
Alan Scheinine, Wieslawa I. Mentzen, Giorgio Fotia, Enrico Pieroni, Fabio
Maggio, Gianmaria Mancosu, and Alberto de la Fuente 287
The Genome Scale Challenge Best Performer Paper
Inference of Regulatory Gene Interactions from Expression Data Using
Three-Way Mutual Information. 2?yjohn Watkinson, Kuo-ching Liang,
Xiadong Wang, Tian Zheng, and Dimitris Anastassiou 302
Index of Contributors 315
The New York Academy of Sciences believes it has a responsibility to provide an open Ibruni for
discussion of scientific questions. The positions taken by the participants in the reported conferences are
their own and not necessarily those of the Academy- The Academy has no intent to influence legislation
by providing such forums. |
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| title | The challenges of systems biology community efforts to harness biological complexity |
| title_auth | The challenges of systems biology community efforts to harness biological complexity |
| title_exact_search | The challenges of systems biology community efforts to harness biological complexity |
| title_full | The challenges of systems biology community efforts to harness biological complexity ed. by Gustavo Stolovitzky ... |
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