At a microscopic level, organisms are ruled by interacting systems of biomolecules. Historically, scientists painstakingly elucidated chains of molecular events using experiments that reveal individual interactions, although they recognized that members of different pathways frequently interact. In recent years, researchers have built richer, interconnected networks to mathematically summarize their knowledge of these interactions. This systems biology enterprise, largely stimulated by high-throughput tools like microarrays that measure mRNA levels as an indicator of gene expression, is a…mehr
At a microscopic level, organisms are ruled by interacting systems of biomolecules. Historically, scientists painstakingly elucidated chains of molecular events using experiments that reveal individual interactions, although they recognized that members of different pathways frequently interact. In recent years, researchers have built richer, interconnected networks to mathematically summarize their knowledge of these interactions. This systems biology enterprise, largely stimulated by high-throughput tools like microarrays that measure mRNA levels as an indicator of gene expression, is a vital and increasingly important activity in both basic biology and in medicine. A nagging concern, however, is how accurately these networks represent the biology. For complex systems like biological networks, there are practical limits on how well even massive amounts of data can uniquely define the underlying structure and yield useful predictions of measurable events. Indeed, although its advocates call this process "reverse engineering," the topology and the detailed molecular interactions of the "inferred" networks will likely never be known with precision. This volume captures the ongoing process to assess the ability of scientists--and their computer servants--to infer networks from experimental data, by comparing their predictions to "gold-standard" networks whose structure is thought to be known. 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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Gustavo Stolovitzky is the editor of The Challenges of Systems Biology: Community Efforts to Harness Biological Complexity, Volume 1158, published by Wiley. Pascal Kahlem is the editor of The Challenges of Systems Biology: Community Efforts to Harness Biological Complexity, Volume 1158, published by Wiley.
Inhaltsangabe
Preface: Gustavo Stolovitzky Pascal Kahlem and Andrea Califano Part I: Selected Papers from the ENFIN-DREAM Joint Conference 1. Ranking genes by their co-expression to subsets of pathway members: Priit Adler Hedi Peterson Phaedra Agius Jüri Reimand and Jaak Vilo 2. Creating reference datasets for Systems Biology applications using text mining: Martin Krallinger Ana Maria Rojas and Alfonso Valencia Selected Papers from the DREAM2 Conference Transcriptional Modules and Regulatory Networks 3. Condition-dependent combinatorial regulation in Escherichia coli: Karen Lemmens Tijl De Bie Thomas Dhollander Pieter Monsieurs Bart De Moor Julio Collado-Vides Kristof Engelen and Kathleen Marchal 4. Reverse-engineering transcriptional modules from gene expression data: Tom Michoel Riet De Smet Anagha Joshi Kathleen Marchal and Yves Van de Peer Signaling and Metabolic Networks 5. Specification of spatial relationships in directed graphs of cell signaling networks: Azi Lipshtat Susana R. Neves and Ravi Iyengar 6. Uncovering metabolic objectives pursued by changes of enzyme levels: Sabrina Hoffmann and Hermann-Georg Holzhütter. Biological Network Models 7. Modeling of Gene Regulatory Network Dynamics Using Threshold Logic: Tejaswi Gowda Sarma Vrudhula and Seungchan Kim 8. Global robustness and identifiability of random scale-free and small-world networks: Yunchen Gong and Zhaolei Zhang Reverse Engineering Algorithms 9. DREAM Project: The five-gene-network data analysis with Local Causal Discovery Algorithm using Causal Bayesian networks: Changwon Yoo and Erik Brilz 10. Combining multiple results of a network reverse engineering algorithm: Daniel Marbach Claudio Mattiussi and Dario Floreano 11. Network inference by combining biologically motivated regulatory constraints with penalized regression: Fabio Parisi Heinz Koeppl and Felix Naef.Computation Tools for Reverse Engineering 12. A Gene Network Simulator to Assess Reverse Engineering Algorithms: Barbara Di Camillo Gianna Toffolo and Claudio Cobelli 13. A Network Inference Workflow Applied to Virulence-related Processes in Salmonella typhimurium: Ronald C. Taylor Mudita Singhal Jennifer Weller Saeed Khoshnevis Liang Shi and Jason McDermott Part II: Best Performer Papers from the DREAM2 Challenges Overview of the DREAM2 Challenges 14. Lessons from the DREAM2 Challenges: a community effort to assess biological network inference: Gustavo Stolovitzky Robert J. Prill and Andrea Califano The BCL6 Target Discovery Challenge Best Performer Papers 15. DREAM2 Challenge: Integrated Multi-Array Supervised Learning Algorithm for BCL-6 Transcriptional Targets Prediction: W.H. Lee V. Narang H. Xu F. Lin K.C. Chin W.K. Sung 16. A data integration framework for prediction of transcription factor targets: a BCL6 case study: Matti Nykter Harri Lähdesmäki Alistair Rust Vesteinn Thorsson and Ilya Shmulevich 17. Inferring direct regulatory targets of a transcription factor in the DREAM2 Challenge: Vinsensius B. Vega Xing Yi Woo Habib Hamidi Hock Chuan Yeo Zhen Xuan Yeo Guillaume Bourque and Neil D. Clarke The Protein-Protein Interaction Challenge Best Performer Paper 18. A Probabilistic Graph-theoretic Approach to Integrate Multiple Predictions for the Protein-Protein Subnetwork Prediction Challenge: Chua Hon Nian Hugo Willy Liu Guimei Li Xiaoli Wong Limsoon Ng See-Kiong The Five Gene Network Challenges Best Performer Papers 19. Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene Networks: Daniel Marbach Claudio Mattiussi and Dario Floreano 20. Inferring Gene Networks: Dream or nightmare? Part 1: Challenges 1 and 3: Angela Baralla Wieslawa Mentzen Alberto de la Fuente The in Silico Network Challenges Best Performer Papers 21. NIRest: a tool for gene network and mode of action inference: Mario Lauria Francesco Iorioa and Diego di Bernardo 22. Reverse Engineering of Gene Networks with LASSO and Non-Linear Basis Functions: Mika Gustafsson Michael Hörnquist Jesper Lundström Johan Björkegren and Jesper Tegnér 23. Prediction of Pair-wise Gene Interaction Using Threshold Logic: Tejaswi Gowda Sarma Vrudhul and Seungchan Kim 24. Inferring Gene Networks: Dream or nightmare? Part 2: Challenges 4 and 5: Alan Scheinine Wieslawa Mentzen E. Pieroni F. Maggio G. Mancosu and Alberto de la Fuente The Genome Scale Challenge Best Performer Paper 25. Inference of regulatory gene interactions from expression data using three-way mutual information: John Watkinson Kuo-ching Liang Xiaodong Wang Tian Zheng and Dimitris Anastassiou Index of Contributors
Preface: Gustavo Stolovitzky Pascal Kahlem and Andrea Califano Part I: Selected Papers from the ENFIN-DREAM Joint Conference 1. Ranking genes by their co-expression to subsets of pathway members: Priit Adler Hedi Peterson Phaedra Agius Jüri Reimand and Jaak Vilo 2. Creating reference datasets for Systems Biology applications using text mining: Martin Krallinger Ana Maria Rojas and Alfonso Valencia Selected Papers from the DREAM2 Conference Transcriptional Modules and Regulatory Networks 3. Condition-dependent combinatorial regulation in Escherichia coli: Karen Lemmens Tijl De Bie Thomas Dhollander Pieter Monsieurs Bart De Moor Julio Collado-Vides Kristof Engelen and Kathleen Marchal 4. Reverse-engineering transcriptional modules from gene expression data: Tom Michoel Riet De Smet Anagha Joshi Kathleen Marchal and Yves Van de Peer Signaling and Metabolic Networks 5. Specification of spatial relationships in directed graphs of cell signaling networks: Azi Lipshtat Susana R. Neves and Ravi Iyengar 6. Uncovering metabolic objectives pursued by changes of enzyme levels: Sabrina Hoffmann and Hermann-Georg Holzhütter. Biological Network Models 7. Modeling of Gene Regulatory Network Dynamics Using Threshold Logic: Tejaswi Gowda Sarma Vrudhula and Seungchan Kim 8. Global robustness and identifiability of random scale-free and small-world networks: Yunchen Gong and Zhaolei Zhang Reverse Engineering Algorithms 9. DREAM Project: The five-gene-network data analysis with Local Causal Discovery Algorithm using Causal Bayesian networks: Changwon Yoo and Erik Brilz 10. Combining multiple results of a network reverse engineering algorithm: Daniel Marbach Claudio Mattiussi and Dario Floreano 11. Network inference by combining biologically motivated regulatory constraints with penalized regression: Fabio Parisi Heinz Koeppl and Felix Naef.Computation Tools for Reverse Engineering 12. A Gene Network Simulator to Assess Reverse Engineering Algorithms: Barbara Di Camillo Gianna Toffolo and Claudio Cobelli 13. A Network Inference Workflow Applied to Virulence-related Processes in Salmonella typhimurium: Ronald C. Taylor Mudita Singhal Jennifer Weller Saeed Khoshnevis Liang Shi and Jason McDermott Part II: Best Performer Papers from the DREAM2 Challenges Overview of the DREAM2 Challenges 14. Lessons from the DREAM2 Challenges: a community effort to assess biological network inference: Gustavo Stolovitzky Robert J. Prill and Andrea Califano The BCL6 Target Discovery Challenge Best Performer Papers 15. DREAM2 Challenge: Integrated Multi-Array Supervised Learning Algorithm for BCL-6 Transcriptional Targets Prediction: W.H. Lee V. Narang H. Xu F. Lin K.C. Chin W.K. Sung 16. A data integration framework for prediction of transcription factor targets: a BCL6 case study: Matti Nykter Harri Lähdesmäki Alistair Rust Vesteinn Thorsson and Ilya Shmulevich 17. Inferring direct regulatory targets of a transcription factor in the DREAM2 Challenge: Vinsensius B. Vega Xing Yi Woo Habib Hamidi Hock Chuan Yeo Zhen Xuan Yeo Guillaume Bourque and Neil D. Clarke The Protein-Protein Interaction Challenge Best Performer Paper 18. A Probabilistic Graph-theoretic Approach to Integrate Multiple Predictions for the Protein-Protein Subnetwork Prediction Challenge: Chua Hon Nian Hugo Willy Liu Guimei Li Xiaoli Wong Limsoon Ng See-Kiong The Five Gene Network Challenges Best Performer Papers 19. Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene Networks: Daniel Marbach Claudio Mattiussi and Dario Floreano 20. Inferring Gene Networks: Dream or nightmare? Part 1: Challenges 1 and 3: Angela Baralla Wieslawa Mentzen Alberto de la Fuente The in Silico Network Challenges Best Performer Papers 21. NIRest: a tool for gene network and mode of action inference: Mario Lauria Francesco Iorioa and Diego di Bernardo 22. Reverse Engineering of Gene Networks with LASSO and Non-Linear Basis Functions: Mika Gustafsson Michael Hörnquist Jesper Lundström Johan Björkegren and Jesper Tegnér 23. Prediction of Pair-wise Gene Interaction Using Threshold Logic: Tejaswi Gowda Sarma Vrudhul and Seungchan Kim 24. Inferring Gene Networks: Dream or nightmare? Part 2: Challenges 4 and 5: Alan Scheinine Wieslawa Mentzen E. Pieroni F. Maggio G. Mancosu and Alberto de la Fuente The Genome Scale Challenge Best Performer Paper 25. Inference of regulatory gene interactions from expression data using three-way mutual information: John Watkinson Kuo-ching Liang Xiaodong Wang Tian Zheng and Dimitris Anastassiou Index of Contributors
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