Bioinformatics is a rapidly emerging field in modern society. It involves bringing together biological data and software tools make it easier to understand. Let’s dig in and find out more.
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Bioinformatics refers to an interdisciplinary field responsible for developing methods and software tools used for understanding biological data. The term “Bioinformatics” was initially coined by Ben Hesper and Paulien Hogewen in 1970. As an interdisciplinary science field, bioinformatics combines statistics, mathematics, information engineering, biology, and computer science. The main purpose of bioinformatics is to analyze and interpret biological data. In silico analyses of biological queries has been done by informatics using statistical and mathematical techniques.
Bioinformatics involves biological studies that use computer programming as their methodology mainly in the field of genomics. Major uses of bioinformatics include the identification of candidates genes and single nucleotide polymorphisms (SNPs). Such identifications are often made with the aim of better understanding the genetic basis of unique adaptations, disease, desirable properties or differences between populations. In a less formal way, bioinformatics also attempts to understand the organizational principles within the protein and nucleic acid sequences known as proteomics.
Bioinformatics has become an important part of many biological areas. In experimental molecular biology, bioinformatics techniques like image and signal processing allow the extraction of useful results from large amounts of raw data. Bioinformatics helps in sequencing as well as annotating genomes and their observed mutations in the field of genetics. It also plays a role in the analysis of protein and gene expression and regulation. Tools of bioinformatics help in comparing, analyzing as well as interpreting genomic and genetic data, and more generally in the understanding of evolutionary aspects of molecular biology. In structural biology, it helps in simulation and modeling of DNA, RNA, proteins and biomolecular interactions.
In the early 1950s, Frederick Sanger determined the sequence of insulin. After this, protein sequences became widely available. It became impractical to manually compare several sequences. This increased the role of computers in molecular biology. Later, methods of sequence alignment and molecular evolution were released. In the 1970’s, new techniques for sequencing DNA were applied to bacteriophage MS2 and øX174, and the extended nucleotide sequences were then parsed with informational and statistical algorithms. These studies illustrated that well-known features, such as the coding segments and the triplet code, are revealed in straightforward statistical analyses and were thus proof of the concept that bioinformatics would be insightful.
To study the manner in which normal cellular activities are altered in different states of diseases, biological data must be combined to form a comprehensive picture of these activities. Therefore, bioinformatics has evolved such that the most pressing task now is the analysis and interpretation of different types of data. This includes protein structures, protein domains, amino acid, and nucleotide sequences.
Computational biology is the term given to the actual process of analyzing and interpreting biological data. Important sub-disciplines in bioinformatics and computational biology include;
The major goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches is its focus on developing as well as applying computationally intensive techniques to achieve this goal. Examples include visualization, machine learning algorithms, data mining, and pattern recognition. Major research efforts in the field include gene finding, sequence alignment, drug design, genome assembly, drug discovery, protein structure prediction, protein structure alignment, cell division or mitosis, and the modeling of evolution.
