Издательство InTech, 2011, -456 pp.
Nowadays it is difficult to imagine an area of knowledge that can continue developing without the use of computers and informatics. It is not different with biology, that has seen an unpredictable growth in recent decades, with the rise of a new discipline, bioinformatics, bringing together molecular biology, biotechnology and information technology. More recently, the development of high throughput techniques, such as microarray, mass spectrometry and DNA sequencing, has increased the need of computational support to collect, store, retrieve, analyze, and correlate huge data sets of complex information. On the other hand, the growth of the computational power for processing and storage has also increased the necessity for deeper knowledge in the field. The development of bioinformatics has allowed now the emergence of systems biology, the study of the interactions between the components of a biological system, and how these interactions give rise to the function and behavior of a living being.
Bioinformatics is a cross-disciplinary field and its birth in the sixties and seventies depended on discoveries and developments in different fields, such as: the proposed double helix model of DNA by Watson and Crick from X-ray data obtained by Franklin and Wilkins in 1953; the development of a method to solve the phase problem in protein crystallography by Perutz's group in 1954; the sequencing of the first protein by Sanger in 1955; the creation of the ARPANET in 1969 at Stanford UCLA; the publishing of the Needleman-Wunsch algorithm for sequence comparison in 1970; the first recombinant DNA molecule created by Paul Berg and his group in 1972; the announcement of the Brookhaven Protein DataBank in 1973; the establishment of the Etheet by Robert Metcalfe in the same year; the concept of computers network and the development of the Transmission Control Protocol (TCP) by Vint Cerf and Robert Khan in 1974, just to cite some of the landmarks that allowed the rise of bioinformatics. Later, the Human Genome Project (HGP), started in 1990, was also very important for pushing the development of bioinformatics and related methods of analysis of large amount of data.
This book presents some theoretical issues, reviews, and a variety of bioinformatics applications. For better understanding, the chapters were grouped in two parts. It was not an easy task to select chapters for these parts, since most chapters provide a mix of review and case study. From another point of view, all chapters also have extensive biological and computational information. Therefore, the book is divided into two parts. In Part I, the chapters are more oriented towards literature review and theoretical issues. Part II consists of application-oriented chapters that report case studies in which a specific biological problem is treated with bioinformatics tools. Molecular phylogeny analysis has become a routine technique not only to understand the sequence-structure-function relationship of biomolecules but also to assist in their classification. The first chapter of Part I, by Kolekar et al., presents the theoretical basis, discusses the fundamental of phylogenetic analysis, and a particular view of steps and methods used in the analysis.
Part 1 Reviews 1
Molecular Evolution & Phylogeny: What, When, Why & How?
Understanding Protein Function - The Disparity Between Bioinformatics and Molecular Methods
In Silico Identification of Regulatory Elements in Promoters
In Silico Analysis of Golgi Glycosyltransferases: A Case Study on the LARGE-Like Protein Family
MicroArray Technology - Expression Profiling of MRNA and MicroRNA in Breast Cancer
Computational Tools for Identification of microRNAs in Deep Sequencing Data Sets
Computational Methods in Mass Spectrometry-Based Protein 3D Studies
Synthetic Biology & Bioinformatics Prospects in the Cancer Arena
An Overview of Hardware-Based Acceleration of Biological Sequence Alignment
Part 2 Case Studies
Retrieving and Categorizing Bioinformatics Publications through a MultiAgent System
GRID Computing and Computational Immunology
A Comparative Study of Machine Leaing and Evolutionary Computation Approaches for Protein Secondary Structure Classification
Functional Analysis of the Cervical Carcinoma Transcriptome: Networks and New Genes Associated to Cancer
Number Distribution of Transmembrane Helices in Prokaryote Genomes
Classifying TIM Barrel Protein Domain Structure by an Alignment Approach Using Best Hit Strategy and PSI-BLAST
Identification of Functional Diversity in the Enolase Superfamily Proteins
Contributions of Structure Comparison Methods to the Protein Structure Prediction Field
Functional Analysis of Intergenic Regions for Gene Discovery
Prediction of Transcriptional Regulatory Networks for Retinal Development
The Use of Functional Genomics in Synthetic Promoter Design
Analysis of Transcriptomic and Proteomic Data in Immune-Mediated Diseases
Emergence of the Diversified Short ORFeome by Mass Spectrometry-Based Proteomics
Acrylamide Binding to Its Cellular Targets: Insights from Computational Studies
Nowadays it is difficult to imagine an area of knowledge that can continue developing without the use of computers and informatics. It is not different with biology, that has seen an unpredictable growth in recent decades, with the rise of a new discipline, bioinformatics, bringing together molecular biology, biotechnology and information technology. More recently, the development of high throughput techniques, such as microarray, mass spectrometry and DNA sequencing, has increased the need of computational support to collect, store, retrieve, analyze, and correlate huge data sets of complex information. On the other hand, the growth of the computational power for processing and storage has also increased the necessity for deeper knowledge in the field. The development of bioinformatics has allowed now the emergence of systems biology, the study of the interactions between the components of a biological system, and how these interactions give rise to the function and behavior of a living being.
Bioinformatics is a cross-disciplinary field and its birth in the sixties and seventies depended on discoveries and developments in different fields, such as: the proposed double helix model of DNA by Watson and Crick from X-ray data obtained by Franklin and Wilkins in 1953; the development of a method to solve the phase problem in protein crystallography by Perutz's group in 1954; the sequencing of the first protein by Sanger in 1955; the creation of the ARPANET in 1969 at Stanford UCLA; the publishing of the Needleman-Wunsch algorithm for sequence comparison in 1970; the first recombinant DNA molecule created by Paul Berg and his group in 1972; the announcement of the Brookhaven Protein DataBank in 1973; the establishment of the Etheet by Robert Metcalfe in the same year; the concept of computers network and the development of the Transmission Control Protocol (TCP) by Vint Cerf and Robert Khan in 1974, just to cite some of the landmarks that allowed the rise of bioinformatics. Later, the Human Genome Project (HGP), started in 1990, was also very important for pushing the development of bioinformatics and related methods of analysis of large amount of data.
This book presents some theoretical issues, reviews, and a variety of bioinformatics applications. For better understanding, the chapters were grouped in two parts. It was not an easy task to select chapters for these parts, since most chapters provide a mix of review and case study. From another point of view, all chapters also have extensive biological and computational information. Therefore, the book is divided into two parts. In Part I, the chapters are more oriented towards literature review and theoretical issues. Part II consists of application-oriented chapters that report case studies in which a specific biological problem is treated with bioinformatics tools. Molecular phylogeny analysis has become a routine technique not only to understand the sequence-structure-function relationship of biomolecules but also to assist in their classification. The first chapter of Part I, by Kolekar et al., presents the theoretical basis, discusses the fundamental of phylogenetic analysis, and a particular view of steps and methods used in the analysis.
Part 1 Reviews 1
Molecular Evolution & Phylogeny: What, When, Why & How?
Understanding Protein Function - The Disparity Between Bioinformatics and Molecular Methods
In Silico Identification of Regulatory Elements in Promoters
In Silico Analysis of Golgi Glycosyltransferases: A Case Study on the LARGE-Like Protein Family
MicroArray Technology - Expression Profiling of MRNA and MicroRNA in Breast Cancer
Computational Tools for Identification of microRNAs in Deep Sequencing Data Sets
Computational Methods in Mass Spectrometry-Based Protein 3D Studies
Synthetic Biology & Bioinformatics Prospects in the Cancer Arena
An Overview of Hardware-Based Acceleration of Biological Sequence Alignment
Part 2 Case Studies
Retrieving and Categorizing Bioinformatics Publications through a MultiAgent System
GRID Computing and Computational Immunology
A Comparative Study of Machine Leaing and Evolutionary Computation Approaches for Protein Secondary Structure Classification
Functional Analysis of the Cervical Carcinoma Transcriptome: Networks and New Genes Associated to Cancer
Number Distribution of Transmembrane Helices in Prokaryote Genomes
Classifying TIM Barrel Protein Domain Structure by an Alignment Approach Using Best Hit Strategy and PSI-BLAST
Identification of Functional Diversity in the Enolase Superfamily Proteins
Contributions of Structure Comparison Methods to the Protein Structure Prediction Field
Functional Analysis of Intergenic Regions for Gene Discovery
Prediction of Transcriptional Regulatory Networks for Retinal Development
The Use of Functional Genomics in Synthetic Promoter Design
Analysis of Transcriptomic and Proteomic Data in Immune-Mediated Diseases
Emergence of the Diversified Short ORFeome by Mass Spectrometry-Based Proteomics
Acrylamide Binding to Its Cellular Targets: Insights from Computational Studies