Bioinformatics

Introduction

The branch of science that inter-correlates fields of mathematical statistics, computer science and biology is referred as bioinformatics. The term Bioinformatics is proposed by Paulien Hogeweg in the year 1979. Bioinformatics found its own application in the field of genetics, proteomics and genomics for genetic material sequencing. This field of study helps in understanding of biological and molecular research development and technologies and to correlate the computing approach for research. It gives profound information by mapping, analyzing, aligning of genetic material like DNA and protein.

Main objective of bioinformatics is proper indepth understanding of biological process. The techniques such as data mining, pattern recognition, development of new algorithms, statistical approach and visualization are used to attain the established goal of this field. Sub-specialty of bioinformatics include

• Designing and discovery of drugs
• Prediction and alignment of proteins
• Aligning DNA sequence
• Finding and assembling of gene and genetic material
• Interaction of protein with protein
• Evolutionary understanding
• Associated studies

Genome organization and evolution

Evolutionary biology is a branch of science that is related to origin of species and their evolutionary changes. Computational evolutionary biology is incorporation of informatics for evolutionary changes in genetic material tracing. It helps in genome comparison studies by analyzing gene duplication and gene transfer. This results in derivation phylogenetic tree developments of life.

Analysis of gene information

Gene expression can be analyzed by measuring mRNA levels. The techniques such as micro arrays, SAGE (Serial Analysis of Gene Expression) tag sequencing method, multiplexed in situ hybridization, EST (Expressed cDNA sequence tagging) and MPSS (Massively parallel signature sequencing). Gene analysis techniques are sound prone and they are subjected to change during biological measurement. Computational evolutionary biology helps in separation of signal from noise while analyzing DNA sequence. Sequence motifs can be identified by promoter analysis. Gene expression regulation helps in comparison of micro array data and application of cluster algorithms to determine the co-expressed gene.

Analysis of protein informations

Proteins of biological materials can be analyzed by high thoroughput mass spectrometry (HT MS) and protein micro arrays. Protein micro array has target problem towards mRNA. However, HT MS has problem of comparing large amounts of data analyzed. Mutations can be inferred by analyzing protein informations. Structure of protein can be easily predicted as primary, secondary and tertiary proteins. By homology modeling, structure of homologous protein can de determined. Techniques such as protein threading, de novo based modeling are used for protein structure prediction.

Software for bioinformatics

Complex statistical approached biological informations can be seen on computer with the help of datas, algorithms and other related sources. Bioinformatics services are divided in to three types as follows.

• Sequence search service
• Multiple sequence alignment
• Biological sequence analysis