Principles of Computational Cell Biology

The second edition of the essential guide for biologists and bioinformaticians, expanded and improved. When it was first published in 2008, Principles of Computational Cell Biology was a groundbreaking book that offered an ideal introduction to a networked-based approach to the study of celluar systems. The revised and updated second edition includes an increased focus on RNA biology and epigenetics, and contains new topics such as intracellular trafficking, and more cellular programs such as circadian rhythms, apoptosis, and cell differentiation. Author Volkhard Helms, an expert with an extensive background in biology and informatics, has revised his classic work that covers the key points in an accessible and in-depth manner. The book contains problems and exercises for each chapter that show how to apply the concepts and methods presented. The author introduces the more complex aspects of the topic while keeping the mathematics to a minimum. This important guide: -Continues the success of the previous edition in teaching a network-based approach to cell biology -Covers new topics including microRNAs, epigenetics, and protein-DNA interactions -Includes problems and solution hints with each chapter -Highlights the practical aspects of cellular biology while keeping math at a minimum Written for biology students, students in biochemistry, cell biologists, biomathematicians, biochemists, and bioengineers, the revised and updated Principles of Computational Cell Biology, Second Edition provides an ideal introduction into the world of modeling biological processes on a cellular level.

Autorentext
Volkhard Helms, PhD is a full professor of bioinformatics at Saarland University. He has authored more than 100 scientific publications and received the EMBO Young Investigator Award in 2001.

Zusammenfassung
Computational cell biology courses are increasingly obligatory for biology students around the world but of course also a must for mathematics and informatics students specializing in bioinformatics. This book, now in its second edition is geared towards both audiences. The author, Volkhard Helms, has, in addition to extensive teaching experience, a strong background in biology and informatics and knows exactly what the key points are in making the book accessible for students while still conveying in depth knowledge of the subject.About 50% of new content has been added for the new edition. Much more room is now given to statistical methods, and several new chapters address protein-DNA interactions, epigenetic modifications, and microRNAs.

Inhalt

Preface of the First Edition xv

Preface of the Second Edition xvii

1 Networks in Biological Cells 1

1.1 Some Basics About Networks 1

1.1.1 Random Networks 2

1.1.2 Small-World Phenomenon 2

1.1.3 Scale-Free Networks 3

1.2 Biological Background 4

1.2.1 Transcriptional Regulation 5

1.2.2 Cellular Components 5

1.2.3 Spatial Organization of Eukaryotic Cells into Compartments 7

1.2.4 Considered Organisms 8

1.3 Cellular Pathways 8

1.3.1 Biochemical Pathways 8

1.3.2 Enzymatic Reactions 11

1.3.3 Signal Transduction 11

1.3.4 Cell Cycle 12

1.4 Ontologies and Databases 12

1.4.1 Ontologies 12

1.4.2 Gene Ontology 13

1.4.3 Kyoto Encyclopedia of Genes and Genomes 13

1.4.4 Reactome 13

1.4.5 Brenda 14

1.4.6 DAVID 14

1.4.7 Protein Data Bank 15

1.4.8 Systems Biology Markup Language 15

1.5 Methods for Cellular Modeling 17

1.6 Summary 17

1.7 Problems 17

Bibliography 18

2 Structures of Protein Complexes and Subcellular Structures 21

2.1 Examples of Protein Complexes 22

2.1.1 Principles of ProteinProtein Interactions 24

2.1.2 Categories of Protein Complexes 27

2.2 Complexome: The Ensemble of Protein Complexes 28

2.2.1 Complexome of Saccharomyces cerevisiae 28

2.2.2 Bacterial Protein Complexomes 30

2.2.3 Complexome of Human 31

2.3 Experimental Determination of Three-Dimensional Structures of Protein Complexes 31

2.3.1 X-ray Crystallography 32

2.3.2 NMR 34

2.3.3 Electron Crystallography/Electron Microscopy 34

2.3.4 Cryo-EM 34

2.3.5 Immunoelectron Microscopy 35

2.3.6 Fluorescence Resonance Energy Transfer 35

2.3.7 Mass Spectroscopy 36

2.4 Density Fitting 38

2.4.1 Correlation-Based Density Fitting 38

2.5 Fourier Transformation 40

2.5.1 Fourier Series 40

2.5.2 Continuous Fourier Transform 41

2.5.3 Discrete Fourier Transform 41

2.5.4 Convolution Theorem 41

2.5.5 Fast Fourier Transformation 42

2.6 Advanced Density Fitting 44

2.6.1 Laplacian Filter 45

2.7 FFT ProteinProtein Docking 46

2.8 ProteinProtein Docking Using Geometric Hashing 48

2.9 Prediction of Assemblies from Pairwise Docking 49

2.9.1 CombDock 49

2.9.2 Multi-LZerD 52

2.9.3 3D-MOSAIC 52

2.10 Electron Tomography 53

2.10.1 Reconstruction of Phantom Cell 55

2.10.2 Protein Complexes in Mycoplasma pneumoniae 55

2.11 Summary 56

2.12 Problems 57

2.12.1 Mapping of Crystal Structures into EM Maps 57

Bibliography 60

3 Analysis of ProteinProtein Binding 63

3.1 Modeling by Homology 63

3.2 Properties of ProteinProtein Interfaces 66

3.2.1 Size and Shape 66

3.2.2 Composition of Binding Interfaces 68

3.2.3 Hot Spots 69

3.2.4 Physicochemical Properties of Protein Interfaces 71

3.2.5 Predicting Binding Affinities of ProteinProtein Complexes 72

3.2.6 Forces Important for Biomolecular Association 73

3.3 Predicting ProteinProtein Interactions 75

3.3.1 Pairing Propensities 75

3.3.2 Statistical Potentials for Amino Acid Pairs 78

3.3.3 Conservation at Protein Interfaces 79

3.3.4 Correlated Mutations at Protein Interfaces 83

3.4 Summary 86

3.5 Problems 86

Bibliography 86

4 Algorithms on Mathematical Graphs 89

4.1 Primer on Mathematical Graphs 89

4.2 A Few Words About Algorithms and Computer Programs 90

4.2.1 Implementation of Algorithms 91

4.2.2 Classes of Algorithms 92

4.3 Data Structures for Graphs 93 &...