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BIOINFORMATICS AND ITS APPLICATIONS

BIOINFORMATICS AND ITS APPLICATIONS

BIOINFORMATICS

  • Bioinformatics is the application of computer science and information technology to the field of biology and medicine.
  • It deals with various fields such as algorithms, databases and information systems, web technologies, artificial intelligence and soft computing, information and computation theory, software engineering, data mining, image processing, modelling and simulation, signal processing, and statistics, for generating new knowledge of biology and medicine, and improving & discovering new models of computation.

INTRODUCTION

  • Bioinformatics was applied in the creation and maintenance of a database to store biological information at the beginning of the “genomic revolution”, such as nucleotide sequences and amino acid sequences.
  • Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data.
  • In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures.
  • The actual process of analyzing and interpreting data is referred to as computational biology.
  • Important sub-disciplines within bioinformatics and computational biology include:
  • the development and implementation of tools that enable efficient access to, and use and management of, various types of information.
  • the development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets, such as methods to locate a gene within a sequence, predict protein structure and/or function, and cluster protein sequences into families of related sequences.

The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g., pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal.

Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein—protein interactions, genome-wide association studies and the modelling of evolution.

There are two fundamental ways of modelling a Biological system (e.g. living cell) both coming under Bioinformatic approaches.

Static | BIOINFORMATICS AND ITS APPLICATIONS

  • Sequences — Proteins, Nucleic acids and Peptides
  • Structures — Proteins, Nucleic acids, Ligands (including metabolites and drugs) and Peptides
  • Interaction data among the above entities including microarray data and Networks of proteins, metabolites

Dynamic

  • Systems Biology comes under this category including reaction fluxes and variable concentrations of metabolites
  • Multi-Agent Based modelling approaches capturing cellular events such as signalling, transcription and reaction dynamics

APPLICATIONS OF BIOINFORMATICS

  • Protein structure prediction is an important application of bioinformatics. The amino acid sequence of a protein, the so-called primary structure, can be easily determined from the sequence on the gene that codes for it.
  • In the vast majority of cases, this primary structure uniquely determines a structure in its native environment. (Of course, there are exceptions, such as the bovine spongiform encephalopathy — also known as Mad Cow Disease). Knowledge of this structure is vital in understanding the function of the protein.
  • Another important idea in bioinformatics is the notion of homology. In the genomic branch of bioinformatics, homology is used to predict the function of a gene: if the sequence of gene A, whose function is known, is homologous to the sequence of gene B, whose function is unknown, one could infer that B may share A’s function.
  • In the structural branch of bioinformatics, homology is used to determine which parts of a protein are important in structure formation and interaction with other proteins.
  • In a technique called homology modelling, this information is used to predict the structure of a protein once the structure of a homologous protein is known. This currently remains the only way to predict protein structures reliably. BIOINFORMATICS AND ITS APPLICATIONS

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