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Bioinformatics uses biology, chemistry, physics, computer science, data science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The process of analyzing and interpreting data can sometimes be referred to as computational biology , however this distinction between the two terms ...
The concept of biological computation proposes that living organisms perform computations, and that as such, abstract ideas of information and computation may be key to understanding biology.
Biological data has also been difficult to define, as bioinformatics is a wide-encompassing field. Further, the question of what constitutes as being a living organism has been contentious, as "alive" represents a nebulous term that encompasses molecular evolution, biological modeling, biophysics, and systems biology.
Bioinformatics and computational biology are interdisciplinary fields of research, development and application of algorithms, computational and statistical methods for management and analysis of biological data, and for solving basic biological problems.
Biodiversity informatics is the application of informatics techniques to biodiversity information, such as taxonomy, biogeography or ecology.It is defined as the application of Information technology technologies to management, algorithmic exploration, analysis and interpretation of primary data regarding life, particularly at the species level organization. [1]
Institute of Bioinformatics (IOB), Bangalore, India: One source claims 15000 [17] proteins. But it is unclear how many of these are unique Pfam: Sanger Institute: protein families database of alignments and HMMs Protein sequence databases Human Proteinpedia: Institute of Bioinformatics (IOB), Bangalore and Johns Hopkins University,
Bioimage informatics is a subfield of bioinformatics and computational biology. [1] It focuses on the use of computational techniques to analyze bioimages, especially cellular and molecular images, at large scale and high throughput. The goal is to obtain useful knowledge out of complicated and heterogeneous image and related metadata.
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.