Statistics and Bioinformatics Ethnicity

Abstract

th century with the joint development by Blaise Pascal and Pierre de Fermat in probability theory. The scope of statistics increased in the early 19 th century which included the collection and analysis of data in general. This probability theory aroused from the studies made in games of chance. Large-scale statistical computation is required in computation nowadays, and new methods that are tough to perform manually are done with the help of statistics. Biostatistics plays a critical importance in the foundation of modern biology theories. The rediscovery of Mendel's work created gaps in understanding between genetics and evolutionary Darwinism and led to debate between biometricians like, Walter Weldon, Karl Pearson, Charles Davenport, William Bateson and Wilhelm Johannsen. Models built on statistical reasoning had helped to solve these variances and to generate the neo-Darwinian modern evolutionary synthesis. Bioinformatics is a novel branch of science stands in-between biology and informatics, which is itself a new area of research. Therefore, bioinformatics is concerned with creation and application of information-based methodologies to analyze biological data sets and the contained information. The wide adoption of technologies like microarrays, genome sequencing projects has resulted in accumulation of large amount of data daily. Hence, to extract automatically extraction and analysis of these data sets is required. To fill this gap new tools are designed with the help of bioinformatics. Mathematical techniques and statistical methods are the natural solution to this problem. Statistics is helpful in predicting unknown system with the application of mathematical model to the observations obtained from the unknown system. Various fields and recent applications which received the boon of statistics in bioinformatics are depicted in this review article. Some examples like Abstract The outcome of the information by bioinformatics is enormous nowadays. Due to this rapid increment in information, collecting and analysing became a quite hard job. To reduce this encumbrance, various statistical methods are developed. This review paper contains how statistics helped in tool designing for finding genes in genomic DNA where biologists needed in plenty, in Phylogenetic trees, in microarrays, in alignment, in sequence analysis, in BLAST and various other implementations.