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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.
Starting in 1990, by 1999, chromosome 22 became the first human chromosome to be completely sequenced. Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. [1] An intersection of computer science, biology, and big data, the field also ...
Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology. It relates to connectionism, social behavior, and emergence. Within computer science, bio-inspired computing relates to artificial intelligence and machine learning.
Biological computing. Biological computers use biologically derived molecules — such as DNA and/or proteins — to perform digital or real computations . The development of biocomputers has been made possible by the expanding new science of nanobiotechnology. The term nanobiotechnology can be defined in multiple ways; in a more general sense ...
Network science. A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [ 1] In general, networks or graphs are used to capture relationships between entities or objects. [ 1]
Neural network (biology) A neural network, also called a neuronal network, is an interconnected population of neurons (typically containing multiple neural circuits ). [1] Biological neural networks are studied to understand the organization and functioning of nervous systems . Closely related are artificial neural networks, machine learning ...
Modelling biological systems is a significant task of systems biology and mathematical biology. [a] Computational systems biology [b] [1] aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems. It involves the use of computer simulations of ...
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 ...