Index

a archetypes 246 action functional 244 artificial selection 262 activated complex 41 artificial siRNAs 371 activation energy 41 autonomous agents 17 activator–inhibitor model – linear stability analysis 140, 141 b actuarial aging rate 315 backup genes 219 adaptation and exploration strategies 229 backup pathways 219 – fold-change detection 230 BACs. see bacterial artificial chromosomes (BACs) – metabolic shifts and anticipation 233 bacterial artificial chromosomes (BACs) 360 – sensing and random switching 231 bacterial operons 160 – shannon information 232 bacterial promoter sequences 146 – signaling pathways, information transmission in 230 bacteriophages 358 – value of information 232 balance equations 24, 25 adaptation motif 157, 158 Bayesian conditioning 94 Advanced Search 451 Bayesian estimation 93 affine transformations, of probability density 395 Bayesian model selection 103, 104 agarose gel electrophoresis of DNA restriction Bayesian networks 93 fragments 359 – for gene expression 145 agent-based models 17, 133 Bayesian parameter estimation 92 agent-based systems 63 Bayesian statistics 88 aging process 11, 314 Bernoulli experiments 395 – actuarial aging rate 315 bifurcation analysis 210 – defined 314 binding constants 46, 48 – delay differential equations 323 binding of ligands to proteins 46 – environmental risk 315 Binomial distribution 394, 395 – evolution of 316 biochemical models 87 – intrinsic vulnerability 315 – simplification of 105 – mechanistic theories 315 biochemical reaction systems 40, 41, 127 ––graphical representation 315 – chemical master equation 128, 129 – stochastic simulations 318 – deterministic kinetic mode 128 aging rate 315 – networks 4 alcohol dehydrogenase 452 ––structure of 146 algebraic equations 30 – Poisson distribution, with average value and variance 128 algebro-differential equation system 30 biological environments 23 allosteric feedback 220 biological function 165 allosteric regulation 49 biological hypotheses 4 AmiGO 449 biological membranes amino acids 27, 76, 289, 343, 344, 375, 450 – structure and function of 347, 348 anaphase-promoting complex (APC) 309 biological modules 160 animal cell 347 biological molecules 334 ANOVA test 17, 402, 403 – forces important in 336–338 antagonistic pleiotropy theory 317 – major classes of 338 APC. see anaphase-promoting complex (APC) biological networks 145, 146

Systems Biology: A Textbook, Second Edition. Edda Klipp, Wolfram Liebermeister, Christoph Wierling, and Axel Kowald.  2016 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2016 by Wiley-VCH Verlag GmbH & Co. KGaA. 476 Index biological robustness properties 218 – differentiation 19 biological systems 3 – machinery 3 biological thermodynamics 417 – organization 3 biology 333 – pathways 9 biomarkers 9 – reprogramming with viral vectors 21 BioModels Database 81 – transcription networks 8 – annotations in models in 81 central limit theorem 396 BioNetGen language (BNGL) 459 centrifugation 364 BioNumbers 76, 445 Chapman–Kolmogorov equation 407 BioPAX 72, 74, 78 ChEBI database 79 15 chemical bonds 336 blotting techniques 362 chemical equilibrium states 50 Boltzmann distribution 418, 421 chemical Langevin equation 130, 131 Boltzmann picture 418 chemical noise 130, 131 Boltzmann’s gas constant 49 chemical potentials 32, 422 Boolean models 63 – difference 31 – of gene regulation 6 chemical reaction systems 422 Boolean networks 16, 122 – temperature and pressure as free variables 422 – advanced types of 123, 124 chemotaxis 234 – basic principles of 122 – model 223 – dynamics of, characterization 122 ChIP. see chromatin immunoprecipitation (ChIP) – model 121 ChIP-on-Chip method 372, 373 Boolean rules (truth table) for systems – limitation 373 – with one input 122 ChIP-PET technique 372 – with two inputs 122 chromatin immunoprecipitation (ChIP) 153, 372 Boolean transitions 122 CKI. see cyclin-dependent kinase inhibitors (CKI) bootstrapping 88, 91 classification methods 438, 439 – cross-validation 91, 92 – boosting, algorithms based on 441 – used for estimating a mean value 91 – clustering-based classification 441 Box, George 5 – k-nearest neighbor method 440 box plot 397 – practical problems underlying classification of patients Brownian motion, as a random process 407 to 439 budding yeast cell cycle 311 – support vector machines (SVMs) 439, 440 – schematic representation 312 – unsupervised/supervised methods 439 – self-oscillating network 313 cloning vectors 359 closed-loop linear control system 417 c clustered regular interspaced palindromic repeats Caenorhabditis elegans 10, 451 (CRISPR) 371 calcium homeostasis 319 clustering algorithms 430 canalization 218 clustering coefficient 149 canonical ensemble 418, 421 cluster validation 435 carbohydrates 339, 340 – average compactness- (isolation-) values 435 Cartesian products 395 – external validation measures 435 βcatenin 302 – internal validation measures 435 causal interactions 115, 116 – Silhouette index 435 13C-based metabolic flux analysis 458 – visualization of cluster quality 436 CDKs. see cyclin-dependent kinases (CDKs) coding sequences (CDS) 448 CDS. see coding sequences (CDS) coefficient of relatedness 277 cell cycle 307 coefficient of variation 397 – budding yeast models 311 coefficients of control analysis 51 – mitotic oscillator, minimal cascade model of 310 column chromatography 364, 365 – steps 309 COMBINE initiative 78 CellDesigner 66, 71, 472 combining rate laws, into models 113 CellML 78 compartment models 30, 135, 136 cell populations, random switching 231 competitive exclusion principle 276 cellular competitive inhibition 45 – composition 333 complementary DNA (cDNA) 361, 446 Index 477 complex ODE systems 64 CRAN. see comprehensive R archive network (CRAN) compound/drug databases 452 CRISPR. see clustered regular interspaced palindromic – ChEBI 453 repeats (CRISPR) – Guide to 453 CRISPR/Cas technique 371 comprehensive R archive network (CRAN) 468 CyberCell Database 10 computational accuracy 64 cyclin-dependent kinase inhibitors (CKI) 309 computational modeling 4, 5, 15, 16, 78 cyclin-dependent kinases (CDKs) 309 – advantages of 5, 6 cytochrome-c oxidase (COX) 319 – basic notions for 6 cytosol 349 computational systems biology 63 computer-assisted modeling. see computational modeling d computer chips 164 DAG. see directed acyclic graph (DAG) computer simulations 4 1D and 2D protein gels 361, 362 concentration control coefficient 52 databases 445 concentration response coefficient 52 – compound/drug (see compound/drug databases) conditional probability 392 – enzyme reaction kinetics (see enzyme reaction connectivity 149, 150 kinetics databases) ConsensusPathDB 76, 467 – general-purpose data resources 445 conservation relations 29, 30 ––BioNumbers 446 constant organization 264 ––PathGuide 445, 446 constants 6 – microarray/sequencing (see microarray/sequencing constitutive transcription 127 databases) constraint-based flux balance analysis 32 – model collections constraint-based flux optimization 23, 30 ––BioModels 452 constraint-based methods 32 ––JWS Online 452 – assumption of optimality 33 – National Center for Information 446 continuous model 7 – nucleotide sequence databases 446 continuous random processes 411 ––EMBL Nucleotide Database 447 – Fokker–Planck equation 411, 412 ––Ensembl 447 – Langevin equations 411 ––Entrez 447 continuous time axis 16 ––European Nucleotide Archive (ENA) 447 continuous values 16 ––GenBank/RefSeq/UniGene 446 control coefficients 51–53 – ontology (see ontology databases) convenience kinetics 49 – pathway (see Pathway databases) convolution rule, of normal distribution 395 – protein (see protein databases) cooperative behavior 276 – of protein modifications (RESID) 447 – group selection 277 – transcription factor (see transcription factor databases) – kin selection 277 data formats 63, 78, 457 – reciprocity 277 data for thermodynamic calculations 424 – spatial structure role 277 data integration 8, 9, 72, 461 cooperativity 47 data normalization 9 COPASI 66–69, 78 data resources 75 – CopasiSE version 68 – general-purpose 445, 446 – screenshot of COPASI’s GUI 69 defective mitochondria 316 correlation analysis 9 degree of heteroplasmy 319 correlation of samples 398 delay differential equations 323 correlation plots and performance of correlation densities 393 measures 399 – estimation 397 coupled systems 110 density function 202, 393, 395, 398, 415, 427 – emergent behavior in 114, 115 deoxynucleotide triphosphates (dNTPs) 307 – modeling of 111 deoxyribonucleic acid (DNA) 345 ––coupling of submodels 111, 112 dependence scheme ––hierarchical regulation analysis 112 – for model parameters 95 ––modeling the system boundary 111 – for rate constants and metabolic state 95 ––supply–demand analysis 112 dephosphorylation 292 covariance matrix 394 descriptive statistics 396 COX. see cytochrome-c oxidase (COX) deterministic models 7, 133 478 Index deterministic replicator equation 274 e DICER pathway for maturation 372 Eadie–Hofstee graphical representation 44 Dictyostelium discoideum 138 EBI Ontology Lookup Service (OLS) 79 differential equation ECTree browser 451 – system 30 elasticities 48, 49, 112, 115, 209, 213, 463 differential equations 63 elasticity coefficients 49, 51, 52 differential evolution (DE) 462 elasticity sampling 213 diffusion equation, solutions of 136, 137 – under thermodynamic constraints 213 – cosine profile 137 electrochemical potentials 423 – Gaussian profile 137 electrophoresis 358 – stationary profile 137 elementary flux modes 27, 29 DIGE (difference gel electrophoresis) 362 embryonic development, robust pattern formation in 138 dimeric protein 47 – bicoid gradient in fly embryo 138, 139 direct binding modular rate law 50 embryonic stem cells (ES cells) 370 directed acyclic graph (DAG) 449 empirical distribution function 398 direct fitness advantage 229 endergonic reactions 41 direct method 65 endoplasmic reticulum 350 discrete models 121, 122 energy balance analysis 32 discrete random walk 406 Ensembl ContigView 447 discrete time steps 16 Ensembl Genome Browser 12 discrete value 16 enthalpy 32, 41 disease-relevant data 9 entropy 189, 230, 247, 419, 420, 422, 426 disposable soma theory 317 environmental risk 315 distribution functions 393 enzymatic rate constants DNA chips 367 – from the Brenda database, distribution of 94 DNA Database of Japan (DDBJ) 447 – distributions of 94 DNA libraries 359, 360, 361 enzymatic reactions 8 DNA ligase 359 enzyme activity by effectors, regulation of 44 DNA methylation 19 enzyme-catalyzed reactions 4, 145, 422 DNA microarrays 357 enzyme investments 250 DNA microinjection 370 enzyme kinetics 43 DNA polymerases 308, 309 – parameters 94 DNA–protein interactions 16 – standard 43 DNA replication 308 enzyme mechanisms 42 DNA sequences 3, 4 enzyme reaction kinetics databases DNA synthesis 315 – BRENDA 451, 452 dNTPs. see deoxynucleotide triphosphates (dNTPs) – SABIO-RK 452 double-strand break (DSB) 370 enzyme–substrate complex 42, 45 Drosophila melanogaster 138, 372 epigenetic regulation 20 3D structure of a protein 5 epistasis 163 dynamical behavior 15 – epistatic interactions 164 dynamical system 6 The Epsilon Group, (TEG) 468 dynamic behavior of feed-forward loops (FFLs) 159 equilibrium constant 421, 423 dynamic behavior of network 4 – and energies 421 dynamic equilibrium 15 equilibrium thermodynamics, in reaction systems 42 dynamic FBA 34 Erdös–Rényi random graphs 147, 148 dynamic fluctuations 132, 133 error distribution 90 dynamic model of feed-forward loops 158 ESS. see evolution, stable strategies (ESS) dynamic networks 16 estimators 89 dynamic systems 161, 162, 386 ESTs. see expressed sequence tags (ESTs) – describing with ordinary differential equation 386 eukaryotes 335 ––notations 386 eukaryotic cells 350 – global stability of steady states 390 Euler–Lotka equation 317 – limit cycles 390, 391 European Institute (EMBL-EBI) 446 – linearization of autonomous systems 388 European Nucleotide Archive (ENA) 447 – solution of linear ODE systems 388 evaluating system of ODEs 64 – stability of steady states 388, 389 evolution 241, 261 Index 479

– of analogous traits 164 – coefficient 52 – biological macromolecules, selection equations for 263 flux distributions 163 – control of 243 flux–force relation, consequences of 425 – cost 247 flux modes 27, 28, 162 – effort 248 flux optimization 250 – evolution strategies (ES) 462 – paradigm 32 – hypercycle model 267 ––applications and tests of 32 – of modularity 164 flux ratio 104, 424, 425 – neutral theory of molecular evolution 270 flux response coefficient 52 – optimization 263 flux sampling 212 – Quasispecies model 265 flux variability analysis 34 – as search strategy 242 FlyBase 449 – spin glass model 269 force-dependent modular rate law 50 – stable strategies (ESS) 276 formats 72. see also data formats evolutionary game theory 271 fourth-order Runge–Kutta algorithms 64 – cooperative behavior 276 FOXN1 gene 12 – evolutionarily stable strategies 275 free energy 32, 41, 189, 419, 422 – game theory 273 free energy differences – metabolic yield and efficiency, compromises – biochemical reactions 42 between 278 FreeFem++ 467 – population dynamics, replicator equation for 274 frequency response function 414 – rock–scissors–paper game, dynamical behavior 276 functional groups, in biological molecules 338 – social interactions 272 fundamental cellular structures 334 evolvability 229 experimental techniques 357 g exploration strategies 234 GA. see genetic algorithms (GA) – chemotaxis 234 game theory 273 – infotaxis 235 – hawk–dove game 273 – stress-induced mutagenesis 234 – Nash equilibrium 274 exponential distribution 394 – payoff matrix 273 expressed sequence tags (ESTs) 446 – prisoner’s dilemma 273 expression of genes 351 – repeated games 274 eXtensible Markup Language 72 Gauss algorithm 26, 29 external metabolites 24 Gaussian distribution 95, 398 extreme pathways 27 Gaussian elimination algorithm 383 Gaussian probability density 90 f Gauss–Markov random processes 415 FACS. see fluorescence-activated cell sorting (FACS) GEF. see guanine nucleotide exchange factor (GEF) failure tolerance 218 gel electrophoresis 358 false discovery rate (FDR) 429 gene cascades, temporal fluctuations 202 fatty acids 341 – linear model with two genes 202 FBA. see flux balance analysis (FBA) – time correlations in protein levels, measurement 203 FDR. see false discovery rate (FDR) gene-enrichment scores 437 feedback cycles 304 gene exchange and reuse 162 feedback regulation 157 gene expression 121, 171 feed-forward loop (FFL) 150, 158 – dynamic models of 180 – functions of 159 ––gene expression and regulation, basic model of 180 FFL. see feed-forward loop (FFL) ––natural and synthetic gene regulatory networks 183 fixed average energy 421 ––with Stochastic equations 186 fixed points 7 – in eukaryotic cells 352 fluorescence-activated cell sorting (FACS) 209 – fluctuations 196 flux balance analysis (FBA) 6, 8, 23, 29, 30 ––gene cascades, temporal fluctuations 202 – extensions of 33 ––intrinsic and extrinsic variability 200 ––minimization of metabolic adjustments 33 ––stochastic model of transcription and translation 197 – geometric interpretation of 31 – functions 187 flux cone 27 ––from equilibrium binding 188 flux control 425 ––inferring transcription factor activities 192 480 Index

––lac Operon in E. coli 187 group selection 277 ––of lac promoter 191 growth and reproduction 333 ––mRNA and protein levels, correspondences GSK3. see glycogen synthase kinase 3 (GSK3) between 196 gTOW. see genetic tug-of-war (gTOW) method ––network component analysis 194 GTPase activity 297 ––promoter occupancy, thermodynamic models of 189 guanine nucleotide exchange factor (GEF) 297 – mechanisms 171 GUI. see graphical user interface (GUI) ––general promoter structure 173 ––microRNAs, post transcriptional regulation through 176 h ––promoter elements, prediction and analysis of 174 Haldane relationships 44, 95, 423 – omnibus (GEO) 447 halobacteria 335 – regulation 171 Hamming distance 123, 264 – regulation of 355 Hanes–Woolf graphical representation 44 – transcription factor-initiated 171 Hankel singular values 416 gene functions 160 Hawk–Dove game 273 gene loss 219 Hayflick limit 316 gene network coordinating 160 Hessian matrices 254 gene ontology (GO) 9, 79, 448 heterogeneities 357 GeneOntology Consortium 436 heterogeneous data sets 72 general-purpose databases 75 hierarchical clustering 431–433 gene regulation 15, 33, 93, 183, 187, 190, 194, 419, 469 – parameters in 432 genes code 3, 12, 35, 183 hierarchical methods 430 genetic algorithms (GA) 462 high osmolarity glycerol (HOG) 297 genetically modified mouse, serve as a model 5 high-performance liquid chromatography (HPLC). 365 genetic network fluctuations 199 high-throughput methods 357, 358 334 – sequencing method 373 – code 353 high-yield fluxes 278 – programming 263 Hill equation 47 genetic sequence database (GenBank) 446 Hill function 20 genetic tug-of-war (gTOW) method 252 HOG. see high osmolarity glycerol (HOG) genome editing 370 Holm’s stepwise correction 429 genome-scale networks 23 Hox genes 12 genome sizes of organisms 335 Human Genome Project 8 GEO. see gene expression, omnibus (GEO) human mortality 314 geometric mean 397 hybridization techniques 362 geometric random graphs 148 GFP gene 375 i Gibbs free energies 31, 41, 422, 423, 424 identity matrix 29 – change of 41 IEF. see isoelectric focusing (IEF) Gibbs picture 418 implicit methods 64 global model reduction 108–110 impulse input 414 – linearization of biochemical models 108, 109 impulse response function 414 – linear relaxation modes 109 induced pluripotent stem cells (iPS cells) 20 glucose-6-phosphate (G6P) 18 inequality constraints 246 glycogen synthase kinase 3 (GSK3) 301 inferring transcription factor 192 Goldbeter’s minimal model 312 information encoded in stoichiometric matrix N 25 golgi complex 350 infotaxis 235 Gompertz–Makeham equation 314, 317 input-output relations 414 good models – of signaling systems 153 – defined 99 in situ hybridization 364 – possible requirements for 99 integral feedback 221 GPCR. see G proteincoupled receptors (GPCR) integrated metabolic, and regulatory network 35 G proteincoupled receptors (GPCR) 296 intelligent database systems 9 G protein cycles 295 Internet 10 Gramian matrices 415, 416 interquartile range 397 graphical user interface (GUI) 464 intrinsic and extrinsic variability 200 green fluorescent protein 374, 375 – calculation of 200 Index 481

– measurement of 200 linear dynamical systems 413 intrinsic vulnerability 315 – control of 412 invariant distribution 410 linear equations 49, 381–383 inverse problems 91 – system 26 isoelectric focusing (IEF) 361 linear filters 414 linearization 44 j linear models 401, 402 Java simulations 464 linear regression 17, 88, 89 JDesigner 472 linear systems, systematic solution of 383, 384 Jensen’s inequality 394 Lineweaver–Burk graphical representation 44 JMadonna 459 link matrix 29 joint probability density 395 lin-log kinetics 49 JSim’s model 463 lipids 340 jump processes in continuous time 410 local sensitivity analysis 210 – deriving master equation 410, 411 log-normal distribution, density function 395 low-yield fluxes 278 k lysosomes 351 Karhunen–Loève transform 416 KEGG. see Kyoto encyclopedia of genes and genomes m pathway (KEGG) macromolecules 127 kernel 26 macroscopic – matrix 26 – behavior 127 kinases transmit signals, by phosphorylating 82 – model 133 kinetic constants 41, 43, 52, 94 ––kinetic 197 kinetic modeling 7, 8, 39, 121, 421 Manhattan distance 430 – of enzymatic reactions 39 MAP kinase cascades 296 kinetic rate equation models 6 MAPKs. see mitogen-activated protein kinases (MAPKs) Kinetic Simulation Algorithm Ontology (KiSAO) 78 marginal density 395 kinetics of a simple decay 40 Markov chains 410 kin selection 277 Markov processes 127, 409 K-means algorithms 434, 435 mass action kinetics 48, 49 Knockout Mouse Project (KOMP) 12 mass action law 42 knockout mutations 23, 123 mass spectrometry (MS) 357, 369, 370 Kyoto encyclopedia of genes and genomes pathway master quasispecies distribution 266 (KEGG) 75, 286, 450 master sequence 265 – database 76, 437 master species 265 Mathematica 465 l mathematical description of biological systems 15 lac Operon, E. coli 187 mathematical graphs 147 lac permease activity 245 mathematical modeling 4, 8 lac promoter 191 – of a biological system 16 Lagrange multipliers 246 mathematical modeling language (MML) 463 Lambda 360 mathematical random processes 406 large numbers, strong law 396 mathematical robustness criteria 218 law of mass action 40 Matlab 465, 470 least-squares estimator 403 matrices 384 least-squares method 89, 403 – basic matrix operations 384, 385 Legendre transformation 422 – basic notions 384 length and time scales in biology 4 – dimension and rank 385, 386 length scales 3 – eigenvalues and eigenvectors of a square matrix 386 libAntimony 458 – linear dependency 384 ligases 357 matrix expressions for control coefficients 55–57 likelihood function 89 matrix representation of coefficients 53 likelihood ratio test maximal entropy, principle of 421 limit theorems 395 maximum likelihood 89 linear algebra 381 – estimation 92 linear degradation 127 MCA. see metabolic control analysis (MCA) 482 Index mean 396 minimum information about a microarray experiment median 396 (MIAME) 72, 454 median absolute deviation 397 minimum information about a proteomics experiment message parsing interface (MPI) protocol 469 (MIAPE) 72 metabolic capacity 23 minimum information about a simulation experiment metabolic control analysis (MCA) 50, 51, 461 (MIASE) 9 metabolic control theory, theorems of 53 minimum information about sequencing experiment – connectivity theorems 54, 55 (MINSEQE) 454 – summation theorems 54 Minimum Information for Biological and Biomedical metabolic efficiency 278 Investigations (MIBBI) Consortium 78 metabolic maps 27 minimum information requested in the annotation of metabolic modeling 19, 48 biochemical models (MIRIAM) 9 metabolic networks 23, 24, 146, 150 – MIRIAM Registry 79 – Escherichia coli 146 missing values 430 metabolic or regulatory network model mitochondria 350 – basic elements 23 mitochondrial damage study 318 metabolic pathways 162 – delay differential equations 323 – represented by graphs 150 – stochastic simulations 318 metabolic shifts, and anticipation 233 mitochondrial DNA (mtDNA) 375 – adaptation, indirect cues based 234 mitogen-activated protein kinases (MAPKs) 298 – metabolic shifts 233 – cascades 82 – transient state, management of 233 mitophagy 323 metabolic systems 285 mitotic oscillator 310 – metabolic modeling, basic elements 286 mixed inhibition 46 – threonine synthesis pathway model 289 MML. see mathematical modeling language (MML) – upper glycolysis, toy model 286 model databases 77 metabolic yield 278 – BioModels 77 metabolism 163 – JWS Online 78 metabolites 4 modeling approaches, for biochemical systems 15–17 metabolite–transcript correlations 9 modeling framework 16 Metropolis–Hastings algorithm 93 model organisms 9 Michaelis constants 43, 50, 94 – Caenorhabditis elegans 11 Michaelis–Menten equation 44 – Drosophila melanogaster 11, 12 – linearization 44 – Escherichia coli 9–11 – parameter estimation 44 – Mus musculus 12 – for reversible reactions 44 – Saccharomyces cerevisiae 11 Michaelis-Menten kinetics 5, 42, 43, 311 models 5 – different approaches for linearization of 44 – adequateness 5 – general scheme of inhibition 45 – alignment 79 – types of inhibition for irreversible and reversible 46 – assignment 7 Michaelis–Mentenlike rate laws 95 – behavior 7 microarray 454 – classification 7 – experiment 72 – combination 80–82 microarray/sequencing databases – comparison 78 – ArrayExpress 454, 455 – concepts 15 – Gene Expression Omnibus 454 – merging 83 microcanonical ensemble 421 – parameterization 49 microinjection 370 – predictions 17, 88, 90, 91, 100, 103, 104, 372 microscopic stochastic model 198 – purpose 5 microstate 417 – reduction 104, 416 – ensembles of 418 – scope 6 microtubules 64 – selection 98 minimal cascade model 310 – semantics 78 minimal fluxes, principle of 250 – similarities 79 minimal information, principle of 211 – simplification 104 minimization of metabolic adjustments (MoMA) 33 – statements 6 – vs. FBA 33 – of upper part of glycolysis 29 Index 483

– validity 82, 83 ––definition of the network 151 model selection, problem of 99 ––material constraints 151 – likelihood and overfitting 100, 101 – network picture revisited 152 – methods for model selection 101 network with nodes 8 – problem of overfitting 101 neutral evolution 272 ––cross-validation 101 neutrality 275 ––selection criteria 101 neutral theory, mathematical models 270 ––statistical tests 101 next-generation sequencing (NGS) ––tests with artificial data 102 – data 454 modularity 160–163, 165 – techniques. 366, 367 – and biological function as conceptual abstractions 165 node distances 149 – on levels of structure, dynamics, regulation, noncatalyzed reaction 41 and genetics 161, 162 noncompetitive inhibition 45 – on various levels, exemplified by bacterial operons 162 nonequilibrium reactions 424 modular rate laws 49 nonlinear constraints 32 modular response analysis 113, 114 nonnested models 102 3, 333, 334 normal distribution 394 – of cell 336 normalization factor 51 molecular dynamics 417 Northern blotting 363 molecule interactions 145 nuclear localization sequence (NLS) 355 moment-generating functions 412 nuclear magnetic resonance (NMR) 448 Monod model 48 nucleic acids 345 Monod–Wyman–Changeux model 48 nucleus 349 Mouse Atlas Project 12 null hypotheses 151 mouse genome database (MGD) 449 null space 29 mRNA 3 numerical integration 64 – processing 353 numerical ODE solvers 64 MS. see mass spectrometry (MS) numerical optimization 245 multiple linear regression 403 numerical parameter optimization 91 multiple testing 428, 429 multivariate Gaussian distribution for logarithmic o parameters 95 Octave 470 multivariate statistics 9, 426 Oct4, Sox2, and Nanog (OSN) factors 20 mutation accumulation theory 317 ODE. see ordinary differential equations (ODE) mutations 146, 262 omics research 72 – clouds 266 OMIM (Online Mendelian Inheritance in Man) 447 Ontology databases n – gene ontology 449 NANOG–OCT4–SOX2 network 125 – Mouse Genome Database (MGD) 449 Nash equilibrium 274 – Saccharomyces Genome Database (SGD) 449 National Center for Biotechnology Information (NCBI) 446 optimal control 416 natural selection 262 optimal enzyme concentrations 255, 257 negative autoregulation 157 – catalytic properties of single enzymes, optimization negative decay rate 42 of 255 negative feedback 156, 157 – enzyme concentrations in a metabolic pathway, optimal – stabilization of protein levels by 165 distribution of 257 negative feedback loops 145 – temporal transcription programs 259 network 8 optimality 243 network-based models 16 – approaches in metabolic modeling 250 network component analysis 194 ––enzyme fitness functions, measurements of 252 network describing cell cycle dynamics ––enzyme levels, optimization of 251 – of Saccharomyces cerevisiae 126 ––flux optimization 250 network motifs 150, 152 – mathematical concepts 245 network structures 145, 146, 151 ––catalytic constants compromises 247 – groups of principles 151 ––cost–benefit models 245 ––analogous function and shaping for optimality 151 ––inequality constraints 246 ––common origin or similar growth processes 151 ––pareto optimality 246 484 Index

– metabolic adaptation 253 – KEGG 76, 450 ––of enzyme activities 254 – Reactome 77, 450, 451 ––optimal control profiles 254 – WikiPathways 77, 451 – metabolic strategies 252 pathway-related data and information 76 ––fermentation 252 pBR322 circular plasmid 360 ––product yield and enzyme cost, trade-off 253 PCA. see principal component analysis (PCA) ––respiration 252 PDBe database 447 – metabolism modeling 248 Pearson’s correlation coefficient 398, 399 ––enzyme investments 250 peptide linkage 344 ––network structures 249 percentile 396 ––short pathways preference 249 per enzyme investment 250 ––thermodynamically feasible pathway 249 periodicity 7 ––yield efficiency 249 peroxisomes 351 optimization methods 97 Petri Net Markup Language (PNML) 461 – genetic algorithms 98 Petri nets 124–127 – global optimization 97 – model, simulation pusposes 126 – local optimization 97 – upper glycolysis represent as 126 – sampling methods 98 phenomenological thermodynamics 417 ordinary differential equation (ODE) phenotypical diversity, of organisms 335 – systems 16 phenotypic switching 232 ordinary differential equations (ODE) 17, 24, 63, 124, PHML (Physiological Hierarchy Markup Language) 324, 467 format 466 – -based models 64 phospholipids 341 – basic components of models 18 phosphorelay systems 297 – basic structure and properties of 63 phosphorylation 292 – illustrative examples of models 18 phosphotransfer 292 ––metabolic example 18, 19 phylogenetic relations between some major groups of ––regulatory network example 19–21 organism 335 – systems 25 phylogenetic tree 4 ––for biochemical networks 17 physical theories, chance in 405 ––for dynamics of reaction 42 – deterministic chaos 406 origin of life 334 – perturbations by the environment 406 oscillatory input 414 – quantum-mechanical effects 406 osmotic stress 314 – underlying microscopic dynamics 406 overrepresentation and enrichment analyses 436–438 333 oxygen radicals 316 PIR. see protein information resource (PIR) planning and designing experiments for case-control p studies 426, 427 pan-genome 10 Poincaré–Bendixson states 391 paradoxical regulation 159 Poisson distribution 17 parameters 6 polyacrylamide gels 359 – balancing 96 polymerase chain reaction (PCR) 357, 365, 366 – elasticity 52 polynomial regression model 402 – estimation 44, 88 polypeptides 342 – fluctuations 216 polytene chromosomes 12 – identifiability 90 population dynamics 274 pareto optimality 246 positive homotropic cooperativity 47 partial differential equations (PDEs) 63 posttranslational modifications 355 partial inhibition 46 power-law kinetics 49 particle swarm optimization (PSO) 462 power-law modular rate law 49 partition function 419 power of diagnostics 393 partitioning methods 430 practical nonidentifiability 90 PathGuide 76, 445 prediction of protein function 4 pathway crosstalk, with respect to the type-II diabetes preferential attachment model 149 mellitus candidate gene set 438 principal component analysis (PCA) 404, 405 pathway databases 76, 449 prisoner’s dilemma 273 – ConsensusPathDB 77, 451 probability distributions Index 485

– in discrete random walk 410 reaction–metabolite network 145 – for rate constants 94 reaction networks 25 probability spaces 391, 392 reaction pathways 30, 41 probability theory 392 reaction rate 42, 44 product experiments, and independence 395 reaction thermodynamics 40 product formation 42 reactome 75 product space 395 real-world networks prokaryotic and eukaryotic cells, comparison 334 – scale-free degree distributions in 148 prokaryotic archaebacteria 335 receptor–ligand interactions 293 promoter occupancy, thermodynamic models of 189 reciprocal altruism 274 promoter–operator concept 5 reciprocity 277 protein chips 357, 367, 368 reduced and conditional distributions 407 protein databases reduction, of fast processes 105 – iHOP 449 – relaxation time and other characteristic time – InterPro 448, 449 scales 106, 107 – PANTHER 448 – time scale separation 105 – Protein Data Bank 448 reference sequence database (RefSeq) 446 – UniProt/Swiss-Prot/TrEMBL 448 regression 88 protein degradation 42 regularization 91 protein information resource (PIR) 448 regulation edges and their steady-state protein investment, in different cell functions 161 response 156 protein–protein interaction networks 146 regulation networks 23, 152 protein–protein interactions 16, 292 regulatory FBA 34 proteins 127, 340 repeated games 274 proteins cross-linking 316 replicator equation 274 protein sorting 355 resource balance analysis (RBA) 251 proteomic technologies 8 response coefficients 53 PubMed 447 responsive switching 232 Python modules 471 restriction endonucleases 357 restriction enzymes 358 q – recognize short stretches of DNA 358 qualitative model 7 reversible processes 7 quality control 9 ribonucleic acid (RNA) 345 quantitative proteomics data 9 RNA–DNA hybrid 353 quasi-equilibrium 43, 107, 108 RNA interference (RNAi) 11, 371 quasispecies model 263 – mechanism of 372 quasi-steady-state 43, 107, 108 RNA polymerase 353 RNA primers 308 r RNA-Seq (RNA-sequencing) 368 random errors 90 RNA synthesis 352 random fluctuations 217, 415 robustness mechanisms 217 random graphs 147 – by backup elements 219 – with predefined degree sequence 148 – in biochemical systems 218 random processes describing particle motion 409 – against correlated expression changes 227 random variables 393 – feedback control 219 Ras activation cycle 297 – limits of 228 Ras proteins 295 – role in evolution 228 Ras protooncogenes 297 ––and modeling 228 rate equations 45 – scaling laws 224 – deriving 43–45 – by structure 222 RBA. see resource balance analysis (RBA) ––chemotaxis signaling pathway 223 reaction affinity 31 ––two-component system 222 reaction–diffusion – summation laws 227 – equation 137 – temperature compensation 228 – models 121, 136 – time scaling 227 reaction energetics 425 ROC curve analysis 429, 430 reaction kinetics 39 rock–scissors–paper game, dynamical behavior 276 486 Index rule-based models 16, 17 simultaneous binding modular rate law 49 Runge–Kutta–Fehlberg method 64 single-cell experiments 375 single-cell methods 357 s single nucleotide polymorphisms (SNPs) 447 Saccharomyces Genome Database (SGD) 11, 449 single-stranded DNA (ssDNA) 358 sample size 426 small-world networks 149, 150 SBML files 464 social interactions 272 SBML model 74 sodium dodecylsulfate (SDS) 361 SBMLsimulator 469 software tools SBML Software Matrix 72 – Antimony 458 SBOL ( Open Language) 78 – Berkeley Madonna 459 scale-free networks 148, 149 – BIOCHAM (Biochemical Abstract Machine) 459 scaling laws 217 – BioNetGen 459 – allometric scaling 225 – Biopython 459 – geometric scaling 224 – BioTapestry 460 – power laws 224 – BioUML 460 – scaling relations, within cells 225 – CellDesigner 460 SDS polyacrylamide gel electrophoresis (SDS-PAGE) – CellNetAnalyzer 460 361, 362 – 13C-FLUX2 458 second law of thermodynamics 32, 419, 420 – Copasi (Complex Pathway Simulator) 461 SED-ML (Simulation Experiment Description Markup – CPN Tools 461 Language) 78 – Cytoscape 461 selection criteria 102 – E-Cell 461 – Akaike information criterion 102 – EvA2 (Evolutionary Algorithms framework, revised – Bayesian information criterion 102 version 2) 461, 462 – calculated for 103 – FEniCS Project 462 selection equations 264 – Genetic Network Analyzer (GNA) 462 selection processes 263 – Jarnac 462, 463 selection threshold 265 – JDesigner 463 self-organization 261 – JSim 463 self-organizing maps (SOMs) 433, 434 – KNIME (Konstanz Information Miner) 463 semantic annotations 79 – libSBML 464 sensitivity analysis 210 – MASON 464 serine phosphorylation 295 – Mathematica 464 SGD. see Saccharomyces Genome Database (SGD) – MathSBML 465 Shannon entropy 420 – Matlab 465 sigmoid kinetics 48 – MesoRD (Mesoscopic Reaction Diffusion Simulator) 465 signaling cascade 26 – Octave 465, 466 signaling molecules 152 – Omix visualization 466 signaling networks 23 – OpenCOR 466 signaling pathways 291 – Oscill8 466 – crosstalk 306 – PhysioDesigner 466, 467 – dynamic and regulatory features analysis 304 – PottersWheel 467 – intra and intercellular communication, function – PyBioS 467 and structure of 292 – PySCeS (Python Simulator for Cellular Systems) 467, 468 – receptor–ligand interactions 293 – R language 468 – structural components 295 – SAAM II (Simulation Analysis and Modeling) 468 ––G protein cycles 295 – SBMLeditor 468 ––MAP kinase cascades 296 – SBML-PET-MPI 469 ––phosphorelay systems 295 – SBMLsimulator 469 ––Ras proteins 295 – SBMLsqueezer 469 signaling systems process information 152 – SBMLToolbox 470 signal-to-noise ratio 374 – SBML Validator 470 simple linear regression 403 – SBToolbox2 (Systems Biology Toolbox 2) 470 simulation – SemanticSBML 468, 469 – results of a VCell model 71 – SensA 470, 471 – techniques and tools 63 – SmartCell 471 – tools 65 – STELLA 471 Index 487

– STEPS (Stochastic Engine for Pathway Simulation) 471 stochastic simulations 64, 129, 133, 318, 407 – StochKit2 471, 472 – direct method 129 – SystemModeler 472 – explicit τ-leaping method 129 – Systems Biology Workbench (SBW) 472 – first-order reaction 65 – Taverna 472, 473 – second-order reaction 65 – VANTED 473 – stochastic and macroscopic rate constants 65 – Virtual Cell (VCell) 473 – stochastic simulation and spatial models 130 – xCellerator 473 StochKit2 user 472 – XPPAUT 473, 474 stoichiometric coefficients 24 Southern blotting 363 stoichiometric matrices 25, 26, 30, 214 spatial models 133, 134 stoichiometric models 121 – types of 134, 135 stress-induced mutagenesis 234 ––cellular automata 135 structural analysis, of biochemical systems 23, 24 ––compartment models 135 structural 345–347 ––reaction–diffusion systems 135 structural nonidentifiability 90 ––stochastic models 135 structure diagram 70 spatial structure 278 substrate elasticity 52 Spearman’s rank correlation 399 substrate inhibition 46, 47 spectral density matrix 415 Sulfolobus acidocaldarius 448 SPF. see S phase promoting factor (SPF) supermodels 8 S phase promoting factor (SPF) 309 support vector machines (SVMs) 439, 440 splicing 353 surface plasmon resonance (SPR) technique 376 spontaneous pattern formation 139 sustainable modeling 78 – Gierer–Meinhardt model 140 SVMs. see support vector machines (SVMs) – Turing instability 140 Swiss Institute of Bioinformatics (SIB) 448 S-systems approach 48 systematic single-gene knockout mutants 10 standard deviation 397 system equations 24 standard error system response 414 – of the mean 426 Systems Biology Graphical Notation (SBGN) 74, 75, 460 – of the ratio 426 – activity flow diagrams 75 standards 9, 72 – defining symbols 75 state variables 7 – entity relationship diagrams 75 stationary 407 – state transition diagrams 75 – fluxes 31 Systems Biology Markup Language (SBML) 9, 72 – metabolites 8 – element similarities 79 – states 7 – semantics annotations in 79 statistical entropy 420 systems biology models 4, 243 statistical framework 400 – optimality in 243 – error of first kind 400 – teleological modeling approaches 244 – error of second kind 400 Systems Biology Ontology (SBO) 469 statistical models 16, 17 Systems Biology Workbench (SBW) 460, 462, 463 statistical network analysis 8 system state 6 statistical relationships 145 statistical Shannon information, signaling systems 153 t Statistics 391 tacit assumption in pathway modeling 165 – for sample location 396 tags 72 – for sample variability 397 TALE (transcription activator like effector) 371 steady states 7, 26 TALENs (transcription activator like effector nucleases) 371 – assumption 23 TATA-box 356 – condition 27 tau-leaping method 472 – fluxes 26, 51 TaxTree search 451 “stiff” differential equations 64 TCA. see tricarboxylic acid (TCA) cycle stochastic modeling 6, 17, 127, 405 teleological modeling 244 – of biochemical reactions 127 telomere attrition 316 – of transcription and translation 197 telomere shortening theory 315 ––genetic network fluctuations 199 temporal change of response coefficients 59 ––macroscopic kinetic model 197 temporal evolution, of equation system 42 ––microscopic stochastic model 198 testing statistical hypotheses 399 488 Index tests for differential expression 427 two sample location tests 400 – DNA arrays 427, 428 – gamma function. 400 – next-generation sequencing 428 – unpaired Student’s t-test 400 theorem of Glivenko–Cantelli 396 – Wilcoxon test 401 theoretical model 17 typical abstraction steps, in mathematical modeling 5 thermodynamics 15, 39, 41 – of chemical reactions 4 u – constraints 31 unbeatable 275 ––on rate constants 94 uncertainty analysis 211 – equilibrium and detailed balance 418 – and principle of minimal information 211 ––kinetic rate laws 95 uncompetitive inhibition 45 – laws, practical consequences for biochemical models 425 upper glycolysis, as realistic model 58 ––chemical potentials 425 – flux and concentration control coefficients 58, 59 ––constraints on model parameters 425 urn models 392 ––equilibrium states 425 UV light fluoresces 359 ––partial fluxes 425 ––thermodynamic forces 425 v – in systems biology 425 validity criteria, for systems biology models 83 thermophilic bacteria 335 variability 210 threonine 289 – analysis 211 – synthesis pathway model 289 – and biochemical models 210 time-dependent flux response 60 ––elasticity sampling 213 time-dependent response coefficients 59 ––flux sampling 212 T lymphocytes 12 ––kinetic models, propagation of parameter total protein concentration 257 variability 214 transcription 4, 351 ––parameter fluctuations 216 transcriptional feedback 220 ––uncertainty analysis 210 transcriptional regulation networks 145, 164 – propagation of 214 transcription factor (TF) binding sites 357 variables 6, 16, 30 transcription factor databases variance 397 – JASPAR 453 variational principle, for flux states 424 – Transcription Factor Encyclopedia 454 VCML (Virtual Cell Markup Language) 473 – TRED (transcriptional regulatory element database) Virtual Cell (VCell) 70–72 453, 454 visualization transcription factors 153 – of sample characteristics by box plots 397 – -initiated gene regulation 171 – techniques 9 transcription networks 146, 153 – motifs 153 w – network motifs in transcription network Wegscheider conditions 423 of S. cerevisiae 155 Western blot 362, 363 – positive and negative regulation 153 Westfall and Young step-down correction 429 – potential regulation patterns with one, two, or Wiener process 408 three nodes 155 Wnt/β-catenin signaling pathway 301 – regulation network of transcription factors Wolfram SystemModeler Link (WSMLink) 472 in E. coli bacteria 154 – regulation structures and network motifs 155, 156 x – transcriptional regulation of sugar utilization genes xenografts 12 in E. coli bacteria 155 Xenopus laevis 334 transcriptome 9 XML-based native format 70 transcriptomics 8 XML-compliant format 72 transforming probability densities 395 XML-like language style 9 transgenic animals 370 transition probabilities 407, 409 y transition state theory 41 yeast artificial chromosomes (YACs) 360 translation 4, 353–355 Yeast two-hybrid (Y2H) system 368, 369 TrEMBL 447 trial-and-error process 262 z tricarboxylic acid (TCA) cycle 286 zinc finger nucleases (ZFN) 370 α-trimmed mean 396 zymomonas mobilis 253