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Biodata is the short form for biographical data, and in a biodata, the focus is on personal particulars like date of birth, religion, gender, race, nationality, passport details, permanent and temporary residence, marital status, hobbies, height, weight, and a photograph. The term biodata is mostly used in South Asian countries like India and ...
Biostatistics. Biostatistics (also known as biometry) is a branch of statistics that applies statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.
Biological data refers to a compound or information derived from living organisms and their products. A medicinal compound made from living organisms, such as a serum or a vaccine, could be characterized as biological data. Biological data is highly complex when compared with other forms of data. There are many forms of biological data ...
The include: DNA Data Bank of Japan (National Institute of Genetics) EMBL (European Bioinformatics Institute) GenBank (National Center for Biotechnology Information) DDBJ (Japan), GenBank (USA) and European Nucleotide Archive (Europe) are repositories for nucleotide sequence data from all organisms.
Biographical research is a qualitative research approach aligned to the social interpretive paradigm of research. The biographical research is concerned with the reconstruction of life histories and the constitution of meaning based on biographical narratives and documents. The material for analysis consists of interview protocols (memorandums ...
Biometrics are body measurements and calculations related to human characteristics and features. Biometric authentication (or realistic authentication) is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. [1]
Biomedical data science. Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data.
Bioinformatics tools aid in comparing, analyzing and interpreting genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology.