Bioinformatics

Bioinformatics involves the use of a range of techniques in computational biology to solve biological problems on a molecular level. It uses methods of applied mathematics, chemistry, biochemistry, informatics, statistics, computer science, and artificial intelligence. Bioinformatics has led to major advances in a range of fields, such as the modeling of evolution and the measuring of biodiversity, and medical advances including gene finding, genome assembly, the prediction of gene expression, analysis of protein–protein interactions, modeling [Page 231]of protein structure alignment and prediction, and sequence alignment.

The use of bioinformatics in the prediction of protein structure has been important and has led to protein threading. Homology and homology modeling are used to determine which parts of proteins are the important sections of their structures and how they interact with other proteins.

With its successful use in work on protein structure, bioinformatics has been used to assist with recent advances in the finding of genes and the genome assembly, which in turn have been particularly useful in a number of separate fields. With the core of comparative genome analysis of humans being orthography analysis, involving the establishment of the correspondence between genes, as well as integrating information from genomic features in different organizations, has led medical researchers to investigate new areas such as the analysis of mutations in cancer.

One of the main problems with cancer research has been that for any analysis of individual cancers, there has to be a massive sequencing effort to identify point mutations in a variety of cancer genes. This has meant that vast amounts of data have needed to be stored, and automated systems developed to process sequence data. Similarities and differences in cancers have been found, however, and this work has allowed researchers to develop a further understanding of the problems that reoccur in similar forms of cancer.

Bioinformatics is increasingly important because more data is being collected by researchers, and faster computers running better software, such as Perl as well as the previous algorithms using BLAST, can analyze information much more quickly than before. Medical researchers have also been able to share gathered data more easily and this, in turn, has allowed researchers to achieve better modeling from their computations.