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Principles of Computational Cell Biology

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Computational cell biology courses are increasingly obligatory for biology students around the world but of course also a must for... Weiterlesen
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Beschreibung

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.

Volkhard Helms is a full professor for bioinformatics at Saarland University since 2003. Having obtained his PhD degree from EMBL Heidelberg, he did postdoctoral work at UC San Diego and was head of an independent junior research group at the MPI of biophysics in Frankfurt/Germany. He has authored more than 100 scientific publications and received the EMBO Young Investigator Award in 2001.

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.

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

4.4 Dijkstra's Algorithm 95

4.4.1 Description of the Algorithm 96

4.4.2 Pseudocode 100

4.4.3 Running Time 101

4.5 Minimum Spanning Tree 101

4.5.1 Kruskal's Algorithm 102

4.6 Graph Drawing 102

4.7 Summary 104

4.8 Problems 105

4.8.1 Force Directed Layout of Graphs 107

Bibliography 110

5 ProteinProtein Interaction Networks Pairwise Connectivity 111

5.1 Experimental High-Throughput Methods for Detecting ProteinProtein Interactions 111

5.1.1 Gel Electrophoresis 112

5.1.2 Two-Dimensional Gel Electrophoresis 112

5.1.3 Affinity Chromatography 113

5.1.4 Yeast Two-hybrid Screening 114

5.1.5 Synthetic Lethality 115

5.1.6 Gene Coexpression 116

5.1.7 Databases for Interaction Networks 116

5.1.8 Overlap of Interactions 116

5.1.9 Criteria to Judge the Reliability of Interaction Data 118

5.2 Bioinformatic Prediction of ProteinProtein Interactions 120

5.2.1 Analysis of Gene Order 121

5.2.2 Phylogenetic Profiling/Coevolutionary Profiling 121

5.2.2.1 Coevolution 122

Produktinformationen

Titel: Principles of Computational Cell Biology
Untertitel: From Protein Complexes to Cellular Networks
Autor:
EAN: 9783527810338
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (pdf)
Hersteller: Wiley-VCH
Genre: Mikrobiologie
Anzahl Seiten: 461
Veröffentlichung: 10.12.2018
Dateigrösse: 16.3 MB