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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.
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 ...
Computational genomics. Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, [1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic ...
Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing 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.
Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, [1] including genomics, proteomics, microarrays, systems biology, evolution, and text mining. [2][3] Prior to the emergence of machine learning, bioinformatics algorithms had to be programmed by hand; for problems such as protein structure ...
Biological data visualization is a branch of bioinformatics concerned with the application of computer graphics, scientific visualization, and information visualization to different areas of the life sciences. This includes visualization of sequences, genomes, alignments, phylogenies, macromolecular structures, systems biology, microscopy, and ...
Analytics is the "extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions." It is a subset of business intelligence , which is a set of technologies and processes that uses data to understand and analyze business performance to drive decision-making .
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