BIOMOLECULAR NETWORKS BIOMOLECULAR NETWORKS Methods and Applications in Systems Biology LUONAN CHEN Osaka Sangyo University, Japan RUI-SHENG WANG Renmin University of China, China XIANG-SUN ZHANG Chinese Academy of Science, China Copyright # 2009 by John Wiley & Sons, Inc All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com Requests to the Publisher for permission should be 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and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002 Wiley also publishes its books in variety of electronic formats Some content that appears in print may not be available in electronic formats For more information about Wiley products, visit our web site at www.wiley.com Library of Congress Cataloging-in-Publication Data: Chen, Luonan, 1962Biomolecular networks : methods and applications in systems biology / Luonan Chen, Rui-Sheng Wang, Xiang-Sun Zhang p cm Includes bibliographical references and index ISBN 978-0-470-24373-2 (cloth) Molecular biology– Data processing Computational biology Bioinformatics Biological systems– Research–Data processing I Wang, Rui-Sheng II Zhang, Xiang-Sun, 1943- III Title QH506.C48 2009 572.80285—dc22 2009005776 Printed in the United States of America 10 We Dedicate This Book to Our Colleagues and Our Families CONTENTS PREFACE xiii ACKNOWLEDGMENTS xv LIST OF ILLUSTRATIONS xvii ACRONYMS xxiii Introduction 1.1 Basic Concepts in Molecular Biology / 1.1.1 Genomes, Genes, and DNA Replication Process / 1.1.2 Transcription Process for RNA Synthesis / 1.1.3 Translation Process for Protein Synthesis / 1.2 Biomolecular Networks in Cells / 1.3 Network Systems Biology / 13 1.4 About This Book / 18 I GENE NETWORKS 23 Transcription Regulation: Networks and Models 25 2.1 Transcription Regulation and Gene Expression / 25 2.1.1 Transcription and Gene Regulation / 25 2.1.2 Microarray Experiments and Databases / 28 2.1.3 ChIP-Chip Technology and Transcription Factor Databases / 30 2.2 2.3 2.4 2.5 Networks in Transcription Regulation / 32 Nonlinear Models Based on Biochemical Reactions / 36 Integrated Models for Regulatory Networks / 43 Summary / 44 vii viii CONTENTS Reconstruction of Gene Regulatory Networks 3.1 Mathematical Models of Gene Regulatory Network / 47 3.1.1 3.1.2 3.1.3 3.1.4 3.2 47 Boolean Networks / 48 Bayesian Networks / 49 Markov Networks / 52 Differential Equations / 53 Reconstructing Gene Regulatory Networks / 55 3.2.1 Singular Value Decomposition / 56 3.2.2 Model-Based Optimization / 58 3.3 Inferring Gene Networks from Multiple Datasets / 61 3.3.1 General Solutions and a Particular Solution of Network Structures for Multiple Datasets / 63 3.3.2 Decomposition Algorithm / 65 3.3.3 Numerical Validation / 67 3.4 Gene Network-Based Drug Target Identification / 72 3.4.1 Network Identification Methods / 73 3.4.2 Linear Programming Framework / 77 3.5 Summary / 87 Inference of Transcriptional Regulatory Networks 4.1 Predicting TF Binding Sites and Promoters / 89 4.2 Inference of Transcriptional Interactions / 92 4.2.1 Differential Equation Methods / 93 4.2.2 Bayesian Approaches / 96 4.2.3 Data Mining and Other Methods / 98 4.3 4.4 Identifying Combinatorial Regulations of TFs / 99 Inferring Cooperative Regulatory Networks / 105 4.4.1 4.4.2 4.4.3 4.4.4 4.5 Mathematical Models / 105 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Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data, Bioinformatics 21:71–79 (2005) INDEX S-system, 49, 55, 59, 60, 298 Z-score, 245 a-spectrum, 291 x 2-like score, 251 k-core, 236 k-means, 195, 322 n-neighborhood, 250 p-value, 242 s-similar neighborhood, 213 t-test, 98, 132, 218 activation, 50, 56, 68 activator, 35, 40, 43, 103 Adenosine triphosphate (ATP), 282 affymetrix chip, 69 alternative path, 242 amino acid, 2, 7, Analysis of Variance, 102 APMM, 151, 157 appearance probability matrix, 151 Arabidopsis thaliana, 71 association method, 127 association numerical method, 129 association probabilistic method, 130 ATGenExpress database, 69 auto-regulation loop, 178 average degree, 169 average motif correlation, 182 average path length, 169 bait protein, 123 basis vector, 287 Bayesian classifier, 98 Bayesian network, 49 binary interaction, 123, 129, 146, 155 biochemical equation, 38, 96 biochemical reaction, 25, 36, 281 endergonic reactions, 283 exergonic reaction, 283 fast reaction, 39 slow reaction, 39 BioCyc, 285 BioGRID, 124, 258 bioinformatics, 18 biological process, 233 biomass production, 288 biomolecular interaction, 17, 344 biomolecular network, 8, 10, 13 alignment, 14 dynamical modeling, 14 query, 14 topological properties, 14 bistable switch, 318 Boltzmann machine, 239 Bonferroni correction, 329 boolean directed graph, 301 Boolean function, 48 Boolean network, 48, 317 dynamic attractor, 48 bottleneck node, 176 branch-and-bound, 301 BRENDA, 285 CDD, 125, 265 cell cycle, 6, 69, 109 cellular component, 233 cellular function, 231 cellular localization, 126, 180 cellular metabolism, 281 anabolism, 281 catabolism, 281 central dogma, 3, 10 Biomolecular Networks By Luonan Chen, Rui-Sheng Wang, and Xiang-Sun Zhang Copyright # 2009 John Wiley & Sons, Inc 381 382 INDEX centrality measure, 174 betweenness centrality, 174 closeness centrality, 174 degree centrality, 174 CFinder method, 237 ChIP-chip technology, 30, 88, 100, 106 chromosome, cis-regulatory module, 89 clique, 178 Clique Percolation Method, 237 clustering coefficient, 169 coexpression, 77, 100 coding region, 25 codon, start codon, stop codon, color coding, 208, 324 combinatorial control, 99 combinatorial optimization, 139, 143, 148 combinatorial regulation, 99 community structure, 194 community detection, 194 comparative genomics, 234 compartmental model, 319 competitive binding, 94, 99 compound, 285, 294 conjugate gradient method, 118 connection matrix, 57, 68, 74 continuous optimization, 148 convex analysis, 287, 289 convex programming, 59 cooperation mechanism, 99, 102, 105 cooperative binding, 102, 150 cooperative domains, 151, 152 cooperative-domain interaction, 152 cooperative-domain pair, 152 cooperativity, 99 cross-species data, 205 cross-validation, 131, 157, 261 cumulative hypergeometric probability, 322 cytoplasm, 7, 8, 314 Czekanowski-Dice distance, 101, 236, 258 damage, 301 degradation, 28, 97, 108, 114 degree distribution, 169, 170 depth-first search, 331 diffusion kernel, 242, 243, 255 diffusion-reaction equation, 319 dimerization, 37 directed acyclic graph, 49 directed bipartite graph, 320 DNA, 2, chromosomal DNA, junk DNA, mitochondrial DNA, DNA chip, 28 DNA double helix, 2, 28 DNA strand, 2, coding strand, template strand, DNA-binding domain, 89, 122 domain, 122, 124, 127 InterPro domain, 127, 267 Pfam domain, 165 domain combination, 151 domain deletion, 151 domain function prediction, 265 domain fusion, 125, 151, 166 domain interaction prediction, 127, 163 domain merge, 151 domain pair exclusion analysis, 152 domain rearrangement, 151 domain-domain interaction, 127, 150, 163 drug target, 72, 300 non-target compound, 301 target compound, 301 drug target detection, 301 dynamic Bayesian network, 50 dynamic coexpression, 79 dynamic programming, 79, 208, 325 dynamic system, 54, 106 dynamics, 13 edge-betweenness, 236 eigenarray, 56 eigengene, 56 elementary mode, 288 energy, 282 free energy, 282 potential energy, 282 energy function, 241 entropy, 282 enzyme, 282, 283, 300 Enzyme Commission, 232, 283 enzyme essentiality, 304 enzyme–ligand interactions, 13 INDEX equilibrium probability, 102 eukaryote, 1, exon, Expectation Maximization, 137 expression coherence, 99 extracellular factor, 313 extreme pathway, 288 F-measure, 242, 261 factor analysis, 98, 117 false negative, 133 false negative rate, 135, 155 false positive, 133 false positive rate, 135, 155 feed-forward loop, 178 feedback loop, 51 filtered human interactome, 187 filtered yeast interactome, 180 finite state machine, 87 flow, 286 signal flow, 286 substance flow, 286 Floyd-Warshall algorithm, 244 flux balance analysis, 286 flux balance equation, 287 four-node motif, 178 FS-Weight measure, 251 FunCat, 232, 257 function annotation, 238 function prediction, 233 functional divergence, 173 functional enrichment, 329 functional homogeneity, 238 functional linkage, 234, 239 functional linkage establishment, 249 functional linkage network, 239 functional module, 234 functional module detection, 14, 234 G protein, 314, 315 G-protein-coupled receptor, 315 gene, gene duplication, 173 gene expression, 7, 27 gene fusion, 126 Gene Ontology, 232 gene regulatory network, 9, 33, 47 gene-gene interactions, 55 genetic code, 383 genetic interaction, 33 genetic materials, GenMultiCut, 252 genome, genome-wide location, 30, 95 global alignment graph, 208, 218 global network alignment, 208 GO Identification, 247 GO INDEX, 240, 247, 267 GO term, 233, 246 graph clustering, 236 graph comparison, 207 graph cut, 251 graph matching, 208, 212, 227 graph partition, 199 graphical gaussian model, 62 GraphMatch, 227 Grælin, 223 heterogeneous network, 347 heterotrimer, 315 hierarchical clustering, 235 hierarchical organization, 171 histone, hitting set problem, 143 Hopfield network, 241 hub, 171, 175 date hub, 175 party hub, 175 human disease, 350 human disease network, 351 hypergeometric distribution, 238 multivariate hypergeometric distribution, 100 independent component analysis, 115 integer linear programming, 140, 164, 216, 252, 303, 326 integer quadratic programming, 214 Interaction Sequence Tag, 129 IST hit number, 133 interactome, 10, 12, 351 InterPro2go, 265 intron, ion channel, 315 iPfam, 125, 144, 268 Jacobian matrix, 55, 78, 106 384 INDEX KEGG, 284 kernel method, 256 Laplacian matrix, 255 least square, 55, 59, 98, 115 ligand-receptor interaction, 316 linear differential equation, 59, 106 linear programming, 62, 77, 108, 146, 288 local graph alignment, 208 local matching, 212 localizome, 10 log-likelihood function, 117 log-linear model, 96, 102 logistic regression, 167, 266, 273 loopy belief propagation, 255 LPM, 151, 156 majority-rule method, 251, 266 Mann-Whitney U-test, 101, 186 MAPK signaling pathway, 316, 329 Markov clustering algorithm, 237 Markov network, 52 Markov process, 51 Markov random field, 254 mass action law, 38, 49, 107, 292 mass balance law, 287 mass spectrometry, 161, 233 matrix factorization, 98, 114 max-flow min-cut, 253 maximum edge-weighted graph, 338 maximum edge-weighted path, 338 maximum likelihood estimation, 134 Maximum Specificity Set Cover, 149 maximum-weight connected graph, 338 maximum-weight subnetwork, 327 membrane receptor, 313 metabolic flux, 286, 294 metabolic network, 9, 12, 283 metabolic pathway, 283 amino acid metabolism, 283 citric acid cycle, 283 fatty acid metabolism, 283 glycogen metabolism, 283 glycolysis metabolism, 283 oxidative phosphorylation, 283 pentose phosphate, 283 metabolic pathway reconstruction, 295 metabolome, 10, 347 MetaPathwayHunter, 213, 226 MFGO, 253 Michaelis-Menten equation, 40, 117 Michaelis-Menten kinetics, 292 microarray, 28 cDNA microarray, 28 oligonucleotide microarray, 28 minimum cardinality, 149 minimum exact set-cover, 149 minimum multiway k-cut problem, 252 minimum set-cover, 149 minimum-weight colorful path, 325 minimum-weight simple path, 325 mixed integer linear programming, 58, 291, 338 mixed integer nonlinear programming, 60 MNAligner, 218 MCODE, 217 mode of action, 72 modular structure, 194 modularity, 194 modularity density D, 195 modularity function Q, 194 modularity optimization, 194 module, 177, 194 molecular biology, molecular function, 231, 233 motif cluster, 187 motif cluster center, 187 motif degree, 187 motif detection, 178 motif hub, 181 motif date hub, 181 motif party hub, 181 mRNA abundance, 25 mRNA synthesis, 74, 97 multidomain cooperation, 151 multidomain interaction, 151, 153 multidomain pair, 152 multi-domain protein, 151 multiple linear regression, 74 multiple network alignment, 206, 223 multiple organism data, 139 multivariate regression analysis, 98 mutual information, 79, 265 ă nave Bayesian approach, 166 neighbor, 234 level-1 neighbor, 251 level-2 neighbor, 251 NetMatch, 227 NetSearch, 322 INDEX network, 13 flow-type metabolic network, 286 influence-type biological network, 286 network alignment, 206 duplication, 211 gap, 211 match, 211 mismatch, 211 network centrality, 174 network component analysis, 114 network diameter, 169 network evolution, 173 network growth model, 173 network identification, 73 network motif, 177 network querying, 207, 225 network reliability, 159 network synthesis, 341 binary transitive reduction, 342 pseudovertex collapse, 342 network systems biology, 9, 13 network flow, 253, 338 NetworkBLAST, 223 nitrogenous base, node centrality, 280 node similarity, 207 nonlinear differential equation, 42, 73, 106 NP-hard, 143, 195, 207, 253, 342 nucleotide, polynucleotide, numerical interaction, 129, 131, 145, 155 Occam’s Razor, 143 ordering signaling component, 323 ordinary differential equation, 34, 36, 54, 77, 93, 286, 317 ortholog, 216 p-value, 242 PageRank method, 208 pairwise network alignment, 207 paralog, 216 parsimony explanation, 164 parsimony principle, 140, 164 partial correlation, 53 partial differential equation, 317, 319 partial least square, 116 path matching, 208, 227 PathBLAST, 207 Pathfinder, 326 385 PathMatch, 227 pathogenesis pathway, 187 Pearson correlation coefficient, 98, 104, 133, 181, 247 peptide motif, 265 permutation test, 143 Petri net, 286, 293, 319 colored Petri net, 320 hierarchical Petri net, 320 hybrid functional Petri net, 320 stochastic Petri net, 320 timed petri net, 320 Pfam2GO, 265 phage library display, 122 phenotypic function, 232 phylogenetic footprinting, 90 phylogenetic profile, 126 physical interaction, 35, 36, 99, 121 piecewise-linear differential equations, 54 plasma membrane, 314 polymerase chain reaction, 29 position weight matrix, 90 positive-feedback loop, 318 power-law degree distribution, 169, 171 power-law model, 49 precision measure, 261, 331 preferential attachment, 173 prey protein, 123 principal-component analysis, 115 probe, 28 ProDom, 265 prokaryote, 1, promoter, 5, 25, 89 protein, 2, 3, 5, protein complex, 121, 124, 234 protein contact network, 346 protein function, 231 protein function prediction, 14, 234, 249 protein interaction network, 9, 11, 149, 171, 206, 234 protein interaction prediction, 126 protein kinase, 314 protein localization, 145 protein-protein interaction, 9, 121 permanent interaction, 121 transient interaction, 121 proteome, 9, 347 QNet, 227 QPath, 227 386 INDEX quadratic programming, 208 quasi steady-state, 97, 287 quasibipartite, 237 quasiclique, 237 quasiequilibrium, 96 Radial Basis Function, 262 random network, 165, 170, 242 random sampling, 325 ratio association, 199 ratio cut, 199 reaction, 281 reaction-rate equation, 54 recall measure, 261, 331 regulation matrix, 56, 78, 96, 108 regulatory motif abundance, 179 regulatory region, 25 relevance network, 53, 87 replication, 3, repression, 56, 68, 94, 110 repressor, 35, 103 residue network, 346 ribosome, 4, RNA, miRNA, 349 mRNA, 3, 5, ncRNA, 99, 349 tRNA, RNA polymerase, 26 RNA synthesis, 6, 27 ROC curve, 262 ROC score, 262 root mean square error, 131 SAGA, 227 sample imbalance, 256 scale-free property, 172 second messenger, 313 Selective Permissibility Algorithm, 326 sensitivity, 133 sequence alignment, 211, 213 sequence logo, 90 sequence signature, 127 set-cover problem, 148 short cycle, 178 shortest path, 170, 174, 235, 243 shortest path distribution, 169 shortest-path distance, 235 shortest-path profile, 243 sigmoidal function, 94, 105 signal transduction, 313 signal transduction pathway, 313 signaling molecule, 314, 315 signaling network, 9, 12, 315, 321, 326, 341 signaling network detection, 326 similar length-p path, 213 simulated annealing, 239, 252 single-input motif, 117, 178 single organism data, 139 Singular Value Decomposition, 56, 256, 259, 290 sink compound, 295 small G protein, 314 small GTPase, 315 small RNA, 349 small-world property, 169, 172 socioaffinity score, 245 SOS network, 84 source compound, 295 spatial distribution, 180, 181 specificity, 133 splicing, 5, 8, 28 alternative splicing, steady state, 48, 55, 56, 73, 96, 287 stochastic differential equation, 55, 92, 95, 317 stoichiometric matrix, 286 stoichiometric reaction equation, 286 stoichiometry, 96, 286 strongly cooperative domain, 151 structure alignment, 227 subgraph distribution, 187 subgraph-isomorphism problem, 207 subtree comparison, 213 superdomain, 151, 152 superparamagnetic clustering, 236 Support Vector Machine, 98, 256, 267 one-class SVM, 259 two-class SVM, 260 system identification, 73, 102 tandem affinity purification, 12, 123, 161 TF binding site, 89, 90 thermodynamic equilibrium, 42 thermodynamic model, 102 three-domain pair, 151, 152 three-node motif, 178 time delay, 51, 54, 58 INDEX time-course data, 58, 62, 77, 294, 298 TopNet, 172 transcription, 3, 5, 6, 25, 89 post-transcription, 7, 349 transcription activation domain, 123 transcription complex, 37, 105, 106 transcription factor, 4, 8, 26, 30, 89, 111 transcription factor activity, 114 transcription initiation, 27, 28, 96 transcriptional regulatory network, 9, 11, 33, 89, 93 transcription start site, 89 transcriptional interaction, 92 387 transcriptome, 10, 350 transient transfection, 91 translation, 3, 7, 25 post-translation, 7, 8, 28, 95, 99, 106 two-dimensional gel electrophoresis, 11 two-domain pair, 151, 152 type I subgraph, 186, 187 type II subgraph, 187 variable deletion, 154 yeast two-hybrid, 12, 122 yeast one-hybrid, 32 Figure 2.7 Structural organization of transcription regulatory networks: (a) basic unit; (b) motifs; (c) modules; (d) transcriptional regulatory network (Reprinted from [Bab04], # 2004, with permission from Elsevier.) Figure 5.11 Cooperative domains in the complex crystal structure formed by proteins P02994 (with ORFs: YBR118W, YPR080W) and P32471 (with ORF: YAL003W) [WaR07c] Figure 5.14 Reconstruction of DNA-directed RNA polymerase complex: (a) RNA polymerase II-TFIIS complex (PDB ID 1y1v) with 13 subunits; (b) PfamA domain architecture for every protein; (c) cooperative domains with protein interaction pairs containing them; (d) the complex with twodomain interactions and multidomain interactions [WaR07c] Figure 7.9 Biomolecular network querying examples for multiple species and conditions: (a) endocytosis—a conserved complex identified between Plasmodium falciparum and Saccharomyces cerevisiae; (b) translation/invasion—a representative complex uncovered within the P falciparum network only; (c) a potential transcription module that appeared in five leukemia gene coexpression networks under different conditions [Zha08] ... students in systems biology and computational biology and practitioners in industry, (2) researchers and graduate students in computer science and mathematics who are interested in systems biology, and. .. protein interaction networks (protein – protein interactions), metabolic networks (enzyme– substrate interactions), and hybrid networks These biomolecular networks indispensably exist in cell systems. .. Domain –domain interaction Database of domain interactions and bindings Database of Interacting Proteins Dynamic programming Domain pair exclusion analysis European Bioinformatics Institute Enzyme