M e t h o d s i n M o l e c u l a r B i o l o g y ™

Series EditorJohn M. Walker

School of Life SciencesUniversity of Hertfordshire

Hatfield, Hertfordshire, AL10 9AB, UK

For further volumes: http://www.springer.com/series/7651

Network Biology

Methods and Applications

Edited by

Gerard Cagney

Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland

Andrew Emili

Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada and

Department of Molecular Genetics and Microbiology, University of Toronto, Toronto, ON, Canada

EditorsGerard Cagney, Ph.D.Conway Institute of Biomolecular and Biomedical Research University College Dublin Dublin, Ireland gcagney@gmail.com

Andrew Emili, Ph.D.Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research University of Toronto, Toronto ON, CanadaandDepartment of Molecular Genetics and Microbiology, University of Toronto, Toronto ON, Canadaandrew.emili@utoronto.ca

ISSN 1064-3745 e-ISSN 1940-6029ISBN 978-1-61779-275-5 e-ISBN 978-1-61779-276-2DOI 10.1007/978-1-61779-276-2Springer New York Dordrecht Heidelberg London

Library of Congress Control Number: 2011934479

© Springer Science+Business Media, LLC 2011All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden.The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.

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v

Preface

Researchers are all familiar with the spectacular success of reductionist approaches for elucidating biological mechanisms over the last century or so. Nevertheless, recent technological advances, particularly among the leading sub-specialities of molecular biology, present chal-lenges to reductionism on at least two fronts.

First, the explosive growth in the scale of data generated by modern, highly parallel, computerized, and increasingly automated lab methods has become a major impediment. For instance, next-generation sequencing technology is capable of producing terabytes of sequence information per day. It is also now mainstream to report global expression patterns for thousands of genes in multiple strains or cell lines subjected to different conditions. Similarly, phenotypic screens analyzing singly or multiply gene-disrupted cells and organisms have recently become prominent. But how will such data be analyzed, interpreted, and pre-sented when extended to patients where thousands of gene isoforms have unique functions in individual tissues? Secondly, it has become apparent that biological processes do not trace back to individual molecules, and that the discrete pathway diagrams of text books do not accurately reflect the more extensive interaction networks likely present in cells.

Yet, while extremely large datasets describing gene sequences, mRNA transcripts, pro-tein interactions, and metabolite concentrations are increasingly commonplace, these rep-resent only starting “parts lists” that are usually insufficient to unlock mechanistic insights on their own right. Notable examples include a marked increase in organism complexity that does not correspond to aggregate genome size (e.g. yeast versus fly versus human), the formation of individual proteins into macromolecular assemblies (i.e. protein complexes) in order to perform intricate biochemical tasks, and the combinatorial action of sequence-specific DNA-binding transcription factors, microRNAs, and chromatin regulators on tran-scriptional responses.

Fortunately, despite the clumsiness of our observations, nature herself has the clear objectives of survival and propagation in mind, so concepts emerging from the study of biological entities, such as networks (e.g. functional interactions linking genes, proteins, metabolites, etc.) suggest that order rather than chaos prevails. These principles include modular and hierarchical organization, reactive information-driven causal-response behav-iours, systems robustness, co-evolution, and self-organization. Moreover, the experience of the last decade argues that continued success in the field of network biology will rely increas-ingly on accurate high-throughput methods for generating quantitative “omic” datasets in combination with innovative integrative analytical tools designed to discover organizing patterns and principles underlying the myriad data.

This book attempts to bring both approaches together in a single volume. It includes practical descriptions of the experimental and computational approaches currently preva-lent in network biology.

Among the 10 experimental methods, three of the major protein interaction mapping approaches are described over three chapters. Seesandra Rajagopala and Peter Uetz describe how different versions of the yeast two hybrid assay serve as complementary protein interac-tion mapping tools (Chapter 1) while Zuyao Ni and co-workers provide detailed instructions

vi Preface

on mapping mammalian protein interactions using a lentiviral affinity tagging and expression system (Chapter 2). In a description of the protein arrays methodology, Mikael Bauer and co-workers highlight the flexibility and power of this technique (Chapter 3). Next, Oliver Schilling and co-workers (Chapter 4) describe a quantitative mass spectrometry-based method for mapping proteome networks through C-termini; Mihaela Sardiu and Michael Washburn describe a set of procedures for quantifying probabilistic protein interaction net-works using label-free proteomics (Chapter 5); Haiming Huang and Sachdev Sidhu describe approaches for mapping interactions between peptide recognition modules and short linear motifs to build protein interaction networks (Chapter 6). Mohan Babu and colleagues pres-ent methodology for carrying out large-scale genetic interaction (epistasis) screens in E. coli (Chapter 7); Yifat Cohen and Maya Schuldiner show how integrated use of high-content microscopy and gene disruption libraries provide unprecedented visual descriptions of dynamic cell processes (Chapter 8); Kim Blakely and co-workers describe the application of related gene knockdown approaches to mammalian cells based on shRNA libraries (Chapter 9). Finally, Susana Neves and Laura Forrest provide an in-depth overview of DNA sequence analysis technologies for molecular phylogenetics (Chapter 10).

A variety of cutting-edge computational approaches currently used in network biology are then surveyed over the next 11 chapters. Gregory Clark and co-workers describe the use of co-evolutionary methods for predicting protein interactions that rival alternative approaches, such as abundance based methods (Chapter 11); Daniele Merico and col-leagues describe a method for finding functionally coherent sets of genes using a Plugin for the Cytoscape network visualization application applicable for many different data types (Chapter 12); Alexei Vazquez and co-workers outline statistical methods for determining error rates in protein interaction networks (Chapter 13) while a complementing method by Gabriel Musso and co-workers reports on methods for evaluating the quality of published datasets (Chapter 14); David Fung and co-workers tackle the widespread problem of clas-sifying network data from clinical samples based on pathway and network topology analysis (Chapter 15); Jennifer Smith and co-workers describe methods for mapping transcriptional regulatory networks from chromatin immunoprecipitation data using models of gene regu-lation with combinatorial DNA binding activity (Chapter 16); Colm Ryan and colleagues describe a method for predicting epistatic interactions based on nearest neighbour imputa-tion (Chapter 17); Iain Wallace, Corey Nislow and coworkers highlight an application of the widely used Cytoscape application for displaying chemogenomic protein networks (Chapter 18); One of the aims of studying protein networks is to gain a better understand-ing of the coordinated role of protein assemblies, or complexes, in the biology of the cell; Benjamin Webb, Andrej Sali, and co-workers (Chapter 19) show how combining such net-work data with constraints for biophysical experiments, sophisticated integrated models of protein complexes may be assembled. Sara Mostafavi and co-workers describe new algo-rithms for characterizing node attributes and assigning function based on annotated data as a core set of tools applicable to many networks (Chapter 20). In a key final chapter, Alexander Ratushny and colleagues discuss building models of biomolecular network pro-cesses based on reaction kinetics and other parameters (Chapter 21).

This book emphasizes the practical application of these approaches – protocols along with troubleshooting guides and benchmarking criteria – and allows for a more compre-hensive description than is typically encountered in primary research papers. We are indebted to all the many contributing authors who have strived to make the procedures in this volume

viiPreface

concise and accessible, and hope the ensemble will be of value to a broad assortment of readers, ranging from graduate students new to the art to seasoned professionals looking to polish their skill sets. We also encourage the emerging systems biology community to apply these methods regularly in the lab or at the computer. After all, the limitation of past reduc-tionist approaches demand that we cast the net more widely.

Dublin, Ireland Gerard Cagney, Ph.D.Toronto, ON, Canada Andrew Emili, Ph.D.

ix

Contents

Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vContributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

1 Analysis of Protein–Protein Interactions Using High-Throughput Yeast Two-Hybrid Screens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Seesandra V. Rajagopala and Peter Uetz

2 Identification of Mammalian Protein Complexes by Lentiviral-Based Affinity Purification and Mass Spectrometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Zuyao Ni, Jonathan B. Olsen, Andrew Emili, and Jack F. Greenblatt

3 Protein Networks Involved in Vesicle Fusion, Transport, and Storage Revealed by Array-Based Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . 47Mikael Bauer, Magdalena Maj, Ludwig Wagner, Dolores J. Cahill, Sara Linse, and David J. O’Connell

4 Identification and Relative Quantification of Native and Proteolytically Generated Protein C-Termini from Complex Proteomes: C-Terminome Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Oliver Schilling, Pitter F. Huesgen, Olivier Barré, and Christopher M. Overall

5 Construction of Protein Interaction Networks Based on the Label-Free Quantitative Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Mihaela E. Sardiu and Michael P. Washburn

6 Studying Binding Specificities of Peptide Recognition Modules by High-Throughput Phage Display Selections . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Haiming Huang and Sachdev S. Sidhu

7 Array-Based Synthetic Genetic Screens to Map Bacterial Pathways and Functional Networks in Escherichia coli. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Mohan Babu, Alla Gagarinova, and Andrew Emili

8 Advanced Methods for High-Throughput Microscopy Screening of Genetically Modified Yeast Libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127Yifat Cohen and Maya Schuldiner

9 Pooled Lentiviral shRNA Screening for Functional Genomics in Mammalian Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161Kim Blakely, Troy Ketela, and Jason Moffat

10 Plant DNA Sequencing for Phylogenetic Analyses: From Plants to Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183Susana S. Neves and Laura L. Forrest

11 Using Coevolution to Predict Protein–Protein Interactions. . . . . . . . . . . . . . . . . . . 237Gregory W. Clark, Vaqaar-un-Nisa Dar, Alexandr Bezginov, Jinghao M. Yang, Robert L. Charlebois, and Elisabeth R.M. Tillier

x Contents

12 Visualizing Gene-Set Enrichment Results Using the Cytoscape Plug-in Enrichment Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257Daniele Merico, Ruth Isserlin, and Gary D. Bader

13 Quality Control Methodology for High-Throughput Protein–Protein Interaction Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279Alexei Vazquez, Jean-François Rual, and Kavitha Venkatesan

14 Filtering and Interpreting Large-Scale Experimental Protein–Protein Interaction Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295Gabriel Musso, Andrew Emili, and Zhaolei Zhang

15 Classification of Cancer Patients Using Pathway Analysis and Network Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311David C.Y. Fung, Amy Lo, Lucy Jankova, Stephan J. Clarke, Mark Molloy, Graham R. Robertson, and Marc R. Wilkins

16 Statistical Analysis of Dynamic Transcriptional Regulatory Network Structure . . . . . 337Jennifer J. Smith, Ramsey A. Saleem, and John D. Aitchison

17 Imputing and Predicting Quantitative Genetic Interactions in Epistatic MAPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353Colm Ryan, Gerard Cagney, Nevan Krogan, Pádraig Cunningham, and Derek Greene

18 Displaying Chemical Information on a Biological Network Using Cytoscape. . . . . . 363Iain M. Wallace, Gary D. Bader, Guri Giaever, and Corey Nislow

19 Modeling of Proteins and Their Assemblies with the Integrative Modeling Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377Benjamin Webb, Keren Lasker, Dina Schneidman-Duhovny, Elina Tjioe, Jeremy Phillips, Seung Joong Kim, Javier Velázquez-Muriel, Daniel Russel, and Andrej Sali

20 Predicting Node Characteristics from Molecular Networks . . . . . . . . . . . . . . . . . . . 399Sara Mostafavi, Anna Goldenberg, and Quaid Morris

21 Mathematical Modeling of Biomolecular Network Dynamics . . . . . . . . . . . . . . . . . 415Alexander V. Ratushny, Stephen A. Ramsey, and John D. Aitchison

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435

xi

Contributors

John D. Aitchison • Institute for Systems Biology, Seattle, WA, USAMohAn BABu • Banting and Best Department of Medical Research,

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada

GAry D. BADer • Banting and Best Department of Medical Research, Centre for Cellular and Biomolecular Research (CCBR), Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

oliver BArré • Department of Oral Biological and Medical Sciences, Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada

MikAel BAuer • Biophysical Chemistry and Biochemistry, Lund University, Lund, Sweden

AlexAnDr BezGinov • Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

kiM BlAkely • Donnelly Centre and Banting & Best Department of Medical Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

GerArD cAGney • Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland

Dolores J. cAhill • School of Medicine & Medical Science, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland

roBert l. chArleBois • Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

GreGory W. clArk • Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

stephAn J. clArke • Department of Medical Oncology, Sydney Cancer Centre, Sydney, NSW, Australia

yifAt cohen • Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel

páDrAiG cunninGhAM • School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

vAqAAr-un-nisA DAr • Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

xii Contributors

AnDreW eMili • Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics and Microbiology, University of Toronto, Toronto, ON, Canada

lAurA l. forrest • Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA

DAviD c.y. funG • School of Biotechnology and Biomolecular Sciences, New South Wales Systems Biology Initiative, The University of New South Wales, Sydney, NSW, Australia

AllA GAGArinovA • Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

Guri GiAever • Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Pharmaceutical Sciences, University of Toronto, Toronto, ON, Canada

AnnA GolDenBerG • Banting and Best Department of Medical Research, Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada

JAck f. GreenBlAtt • Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

Derek Greene • School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

hAiMinG huAnG • Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada

pitter f. huesGen • Department of Oral Biological and Medical Sciences, Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada

ruth isserlin • Banting and Best Department of Medical Research, Centre for Cellular and Biomolecular Research (CCBR), Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

lucy JAnkovA • Cancer Pharmacology Unit, ANZAC Research Institute, Concord Repatriation General Hospital, Sydney, NSW, Australia

troy ketelA • Donnelly Centre and Banting & Best Department of Medical Research, University of Toronto, Toronto, ON, Canada

seunG JoonG kiM • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

nevAn kroGAn • Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA, USA

xiiiContributors

keren lAsker • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

sArA linse • Biophysical Chemistry and Biochemistry, Lund University, Lund, SwedenAMy lo • School of Biotechnology and Biomolecular Sciences, New South Wales Systems

Biology Initiative, The University of New South Wales, Sydney, NSW, AustraliaMAGDAlenA MAJ • Department of Medicine III, Medical University of Vienna,

Vienna, AustriaDAniele Merico • Banting and Best Department of Medical Research,

Centre for Cellular and Biomolecular Research (CCBR), Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

JAson MoffAt • Donnelly Centre and Banting & Best Department of Medical Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

MArk Molloy • Australian Proteome Analysis Facility, Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW, Australia

quAiD Morris • Department of Computer Science, Banting and Best Department of Medical Research, Centre for Cellular and Biomolecular Research, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

sArA MostAfAvi • Department of Computer Science, Centre for Cellular and Biomolecular Research (CCBR), University of Toronto, Toronto, ON, Canada

GABriel Musso • Cardiovascular Division, Brigham & Women’s Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA

susAnA s. neves • Plant Cell Biotechnology Laboratory, ITQB Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal

zuyAo ni • Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada

corey nisloW • Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Pharmaceutical Sciences, University of Toronto, Toronto, ON, Canada

DAviD J. o’connell • School of Medicine & Medical Science, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland

JonAthAn B. olsen • Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

christopher M. overAll • Department of Biochemistry and Molecular Biology, Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada; Department of Oral Biological and Medical Sciences, Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada

xiv Contributors

JereMy phillips • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

seesAnDrA v. rAJAGopAlA • J. Craig Venter Institute, Rockville, MD, USAstephen A. rAMsey • Institute for Systems Biology, Seattle, WA, USAAlexAnDer v. rAtushny • Institute for Systems Biology, Seattle, WA, USAGrAhAM r. roBertson • Cancer Pharmacology Unit, ANZAC Research Institute,

Concord Repatriation General Hospital, Sydney, NSW, AustraliaJeAn-frAnçois ruAl • Department of Pathology, University of Michigan,

Ann Arbor, MI, USADAniel russel • Department of Bioengineering and Therapeutic Sciences,

California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

colM ryAn • School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

rAMsey A. sAleeM • Institute for Systems Biology, Seattle, WA, USAAnDreJ sAli • Department of Bioengineering and Therapeutic Sciences,

California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

MihAelA e. sArDiu • Stowers Institute for Medical Research, Kansas City, MO, USAoliver schillinG • Institute for Molecular Medicine and Cell Research,

University of Freiburg, Freiburg, GermanyDinA schneiDMAn-Duhovny • Department of Bioengineering and Therapeutic

Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

MAyA schulDiner • Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel

sAchDev s. siDhu • Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada

Jennifer J. sMith • Institute for Systems Biology, Seattle, WA, USAelisABeth r.M. tillier • Department of Medical Biophysics, University of Toronto,

Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

elinA tJioe • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

xvContributors

peter uetz • Proteros Biostructures, Martinsried, Germany and Gaithersburg, MD, USA

Alexei vAzquez • Department of Radiation Oncology, The Cancer Institute of New Jersey and UMDNJ-Robert Wood Johnson Medical School, New Brunswick, NJ, USA

JAvier velázquez-Muriel • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

kAvithA venkAtesAn • Novartis Institutes for Biomedical Research, Cambridge, MA, USA

luDWiG WAGner • Department of Medicine III, Medical University of Vienna, Vienna, Austria

iAin M. WAllAce • Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Pharmaceutical Sciences, University of Toronto, Toronto, ON, Canada

MichAel p. WAshBurn • Stowers Institute for Medical Research, Kansas City, MO, USA; Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, KS, USA

BenJAMin WeBB • Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA; Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA

MArc r. Wilkins • School of Biotechnology and Biomolecular Sciences, New South Wales Systems Biology Initiative, The University of New South Wales, Sydney, NSW, Australia

JinGhAo M. yAnG • Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

zhAolei zhAnG • Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics and Microbiology, University of Toronto, Toronto, ON, Canada