Ebook: Bioinformatics for Systems Biology

The biological sciences are now in the midst of a true life sciences revolution akin to what physics experienced just after the turn of the last century. We are now in a phase of unparalleled growth that is reflected by the amount of data generated from each experiment. At the time of this writing, the rate of data acquisition was approaching 2 terabytes over the course of 5 days with first pass analysis proceeding over the following 2-3 week period. This fundamental shift has provided unprecedented opportunities that for the first time afford us the ability, i.e., means, breadth, and depth of data, to truly address human biology at the systems level. This wealth of information from seemingly disparate datasets and its integration is being realized through bioinformatics. It is with this philosophy that the text Bioinformatics for Systems Biology was born. This revolution has spawned true personalized medicine that encompasses diagnostics and treatment through to cure.

For the physical and computer scientist, this text provides an introduction to the basic biological principles governing a cell. This quickly moves from the fundamentals to exploring the underlying genetic processes. While providing a rudimentary and necessary overview for the life scientist, the physical and computer scientist will be apprised of various nuances within the field reflecting the reality of "wet-bench" science. For those in the life sciences, it I rapidly becoming appreciated that we now progressing from examining our favorite "pet" gene to the system. Statistics is now an essential component to understand the vast datasets and this is emphasized throughout the text.

The majority of the text is devoted to the common ground that these groups share. It provides rich examples of tools, databases, and strategies to mine the databases to reveal novel insights. A host of examples of parsing the data into a series of overlays that use various presentation systems are reviewed. The goal is to provide a representation most comfortable to the user to enable the user to thoroughly explore the data. The text concludes with examples of how the systems information is used to inform personalized medicine in a true "bench to bedside" manner.

Bioinformatics for Systems Biology bridges and unifies many disciplines. It presents the life scientist, computational biologist, and mathematician with a common framework. Only by linking the groups together may the true life sciences revolution move forward in the mostly uncharted and emerging field of Systems Biology.

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The biological sciences are now in the midst of a true life sciences revolution akin to what physics experienced just after the turn of the last century. We are now in a phase of unparalleled growth that is reflected by the amount of data generated from each experiment. At the time of this writing, the rate of data acquisition was approaching 2 terabytes over the course of 5 days with first pass analysis proceeding over the following 2-3 week period. This fundamental shift has provided unprecedented opportunities that for the first time afford us the ability, i.e., means, breadth, and depth of data, to truly address human biology at the systems level. This wealth of information from seemingly disparate datasets and its integration is being realized through bioinformatics. It is with this philosophy that the text Bioinformatics for Systems Biology was born. This revolution has spawned true personalized medicine that encompasses diagnostics and treatment through to cure.

For the physical and computer scientist, this text provides an introduction to the basic biological principles governing a cell. This quickly moves from the fundamentals to exploring the underlying genetic processes. While providing a rudimentary and necessary overview for the life scientist, the physical and computer scientist will be apprised of various nuances within the field reflecting the reality of "wet-bench" science. For those in the life sciences, it I rapidly becoming appreciated that we now progressing from examining our favorite "pet" gene to the system. Statistics is now an essential component to understand the vast datasets and this is emphasized throughout the text.

The majority of the text is devoted to the common ground that these groups share. It provides rich examples of tools, databases, and strategies to mine the databases to reveal novel insights. A host of examples of parsing the data into a series of overlays that use various presentation systems are reviewed. The goal is to provide a representation most comfortable to the user to enable the user to thoroughly explore the data. The text concludes with examples of how the systems information is used to inform personalized medicine in a true "bench to bedside" manner.

Bioinformatics for Systems Biology bridges and unifies many disciplines. It presents the life scientist, computational biologist, and mathematician with a common framework. Only by linking the groups together may the true life sciences revolution move forward in the mostly uncharted and emerging field of Systems Biology.

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The biological sciences are now in the midst of a true life sciences revolution akin to what physics experienced just after the turn of the last century. We are now in a phase of unparalleled growth that is reflected by the amount of data generated from each experiment. At the time of this writing, the rate of data acquisition was approaching 2 terabytes over the course of 5 days with first pass analysis proceeding over the following 2-3 week period. This fundamental shift has provided unprecedented opportunities that for the first time afford us the ability, i.e., means, breadth, and depth of data, to truly address human biology at the systems level. This wealth of information from seemingly disparate datasets and its integration is being realized through bioinformatics. It is with this philosophy that the text Bioinformatics for Systems Biology was born. This revolution has spawned true personalized medicine that encompasses diagnostics and treatment through to cure.

For the physical and computer scientist, this text provides an introduction to the basic biological principles governing a cell. This quickly moves from the fundamentals to exploring the underlying genetic processes. While providing a rudimentary and necessary overview for the life scientist, the physical and computer scientist will be apprised of various nuances within the field reflecting the reality of "wet-bench" science. For those in the life sciences, it I rapidly becoming appreciated that we now progressing from examining our favorite "pet" gene to the system. Statistics is now an essential component to understand the vast datasets and this is emphasized throughout the text.

The majority of the text is devoted to the common ground that these groups share. It provides rich examples of tools, databases, and strategies to mine the databases to reveal novel insights. A host of examples of parsing the data into a series of overlays that use various presentation systems are reviewed. The goal is to provide a representation most comfortable to the user to enable the user to thoroughly explore the data. The text concludes with examples of how the systems information is used to inform personalized medicine in a true "bench to bedside" manner.

Bioinformatics for Systems Biology bridges and unifies many disciplines. It presents the life scientist, computational biologist, and mathematician with a common framework. Only by linking the groups together may the true life sciences revolution move forward in the mostly uncharted and emerging field of Systems Biology.

Content:
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Structure and Function of the Nucleus and Cell Organelles....Pages 3-31
Transcription and the Control of Gene Expression....Pages 33-49
RNA Processing and Translation....Pages 51-66
DNA Replication, Recombination, and Repair....Pages 67-87
Cell Signaling....Pages 89-104
Epigenetics of Spermiogenesis....Pages 105-117
Genomic Tools for Analyzing Transcriptional Regulatory Networks....Pages 119-136
Front Matter....Pages 137-137
Probability and Hypothesis Testing....Pages 139-150
Stochastic Models for Biological Patterns....Pages 151-162
Population Genetics....Pages 163-180
Statistical Tools for Gene Expression Analysis and Systems Biology and Related Web Resources....Pages 181-205
Front Matter....Pages 207-207
What Goes in is What Comes Out: How to Design and Implement a Successful Microarray Experiment....Pages 209-225
Tools and Approaches for an End-to-End Expression Array Analysis....Pages 227-265
Analysis of Alternative Splicing with Microarrays....Pages 267-279
Front Matter....Pages 281-281
An Introduction to Multiple Sequence Alignment — and the T-Coffee Shop. Beyond Just Aligning Sequences: How Good can you Make your Alignment, and so What?....Pages 283-313
A Spectrum of Phylogenetic-Based Approaches for Predicting Protein Functional Sites....Pages 315-337
The Role of Transcription Factor Binding Sites in Promoters and Their In Silico Detection....Pages 339-352
Front Matter....Pages 353-366
Mining the Research Literature in Systems Biology....Pages 367-367
GoPubMed: Exploring PubMed with Ontological Background Knowledge....Pages 369-383
Front Matter....Pages 385-399
BiblioSphere — Hypothesis Generation in Regulatory Network Analysis....Pages 367-367
Biological Knowledge Extraction....Pages 401-412
Front Matter....Pages 413-433
Using KEGG in the Transition from Genomics to Chemical Genomics....Pages 435-435
Ensembl....Pages 437-452
Management of Spatially Organized Biological Data using EMAGE....Pages 453-467
Equality of the Sexes? Parent-of-Origin Effects on Transcription and de novo Mutations....Pages 469-484
Front Matter....Pages 485-513
Methods for Structural Inference and Functional Module Identification in Intracellular Networks....Pages 515-515
Methods for Dynamical Inference in Intracellular Networks....Pages 517-539
ASIAN: Network Inference Web Server....Pages 541-561
Front Matter....Pages 563-577
Bioinformatics for Metabolomics....Pages 579-579
Virtual Reality Meets Functional Genomics....Pages 581-599
Systems Biology of Personalized Medicine....Pages 601-613
Back Matter....Pages 615-630
....Pages 631-639