Chapter 2 Biological databases and bioinformatics tools
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Varruchi Sharma
Abstract
Modern genomic research has generated massive volumes of raw sequence data for which new computational approaches are needed to handle this enormous amount of data. Storage and effective management of such a massive amount of information have been the biggest challenges of today. However, current advancements in the field of bioinformatics have made it possible to overcome data management through the creation and utilization of computational databases. Data that is clearly defined can be accurately stored in specialized databases that adhere to ensuring rationality and consistency. Several data retrieval systems have been developed, such as Entrez, sequence retrieval system (SRS), and DBGET/LinkDB. These alignment systems not only help in providing the best and significant matches to a query but also offer valuable information from other related database sources. The genome-sequencing projects have led to the development of high-throughput technologies that generate sequence data at an incredibly fast rate. This has also resulted in the creation of computer programs that can efficiently handle and analyze huge amounts of data, extracting valuable information from it.
Abstract
Modern genomic research has generated massive volumes of raw sequence data for which new computational approaches are needed to handle this enormous amount of data. Storage and effective management of such a massive amount of information have been the biggest challenges of today. However, current advancements in the field of bioinformatics have made it possible to overcome data management through the creation and utilization of computational databases. Data that is clearly defined can be accurately stored in specialized databases that adhere to ensuring rationality and consistency. Several data retrieval systems have been developed, such as Entrez, sequence retrieval system (SRS), and DBGET/LinkDB. These alignment systems not only help in providing the best and significant matches to a query but also offer valuable information from other related database sources. The genome-sequencing projects have led to the development of high-throughput technologies that generate sequence data at an incredibly fast rate. This has also resulted in the creation of computer programs that can efficiently handle and analyze huge amounts of data, extracting valuable information from it.
Chapters in this book
- Frontmatter I
- Contents V
- Contributors VII
- Chapter 1 Introduction to bioinformatics 1
- Chapter 2 Biological databases and bioinformatics tools 13
- Chapter 3 Fundamentals of bioinformatics 41
- Chapter 4 Tools used in sequence alignment 61
- Chapter 5 Recent advances in the discovery of drug molecules: trends, scope, and relevance 83
- Chapter 6 Computer-aided drug design and drug discovery 103
- Chapter 7 Immunoinformatics: computational keys to immune system secrets 123
- Chapter 8 Phylogenetic analysis 141
- Chapter 9 Basic structure of proteins: current paradigms, trends, and perspective 151
- Index 171
Chapters in this book
- Frontmatter I
- Contents V
- Contributors VII
- Chapter 1 Introduction to bioinformatics 1
- Chapter 2 Biological databases and bioinformatics tools 13
- Chapter 3 Fundamentals of bioinformatics 41
- Chapter 4 Tools used in sequence alignment 61
- Chapter 5 Recent advances in the discovery of drug molecules: trends, scope, and relevance 83
- Chapter 6 Computer-aided drug design and drug discovery 103
- Chapter 7 Immunoinformatics: computational keys to immune system secrets 123
- Chapter 8 Phylogenetic analysis 141
- Chapter 9 Basic structure of proteins: current paradigms, trends, and perspective 151
- Index 171
