Interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex.- Bioinformatics
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Interdisciplinary field of biology focusing on the structure, function, evolution, mapping, and editing of genomes.
Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes.
Interdisciplinarity or interdisciplinary studies involves the combination of two or more academic disciplines into one activity (e.g., a research project).
Examples include quantum information processing, an amalgamation of quantum physics and computer science, and bioinformatics, combining molecular biology with computer science.
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences.
Automated recognition of patterns and regularities in data.
It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.
Computational and mathematical analysis and modeling of complex biological systems.
Indeed, the focus on the dynamics of the studied systems is the main conceptual difference between systems biology and bioinformatics.
Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modelling and computational simulation techniques to the study of biological, ecological, behavioral, and social systems.
Computational biology, which includes many aspects of bioinformatics and much more, is the science of using biological data to develop algorithms or models in order to understand biological systems and relationships.
Application of principles of biology and the tools of engineering to create usable, tangible, economically-viable products.
Biological engineering employs knowledge and expertise from a number of pure and applied sciences, such as mass and heat transfer, kinetics, biocatalysts, biomechanics, bioinformatics, separation and purification processes, bioreactor design, surface science, fluid mechanics, thermodynamics, and polymer science.
Engineering discipline that deals with the generation, distribution, analysis, and use of information, data, and knowledge in systems.
The components of information engineering include more theoretical fields such as machine learning, artificial intelligence, control theory, signal processing, and information theory, and more applied fields such as computer vision, natural language processing, bioinformatics, medical image computing, cheminformatics, autonomous robotics, mobile robotics, and telecommunications.
Task of grouping a set of objects in such a way that objects in the same group are more similar (in some sense) to each other than to those in other groups (clusters).
It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.
Branch of molecular biology, biochemistry, and biophysics concerned with the molecular structure of biological macromolecules , how they acquire the structures they have, and how alterations in their structures affect their function.
A third approach that structural biologists take to understanding structure is bioinformatics to look for patterns among the diverse sequences that give rise to particular shapes.