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Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes. Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.
An example of a hierarchical clustering algorithm is BIRCH, which is particularly good on bioinformatics for its nearly linear time complexity given generally large datasets. [27] Partitioning algorithms are based on specifying an initial number of groups, and iteratively reallocating objects among groups to convergence.
An example of data integration is the use of decision support systems (DSS) based on translational bioinformatics. DSS used in this regard identify correlations in patient electronic medical records (EMR) and other clinical information systems to assist clinicians in their diagnoses.
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.
In structural bioinformatics, de novo modeling, also known as ab initio modeling, refers to approaches for obtaining three-dimensional structures from sequences without the necessity of a homologous known 3D structure. Despite the new algorithms and methods proposed in the last years, de novo protein structure prediction is still considered one ...
Pages in category "Bioinformatics algorithms" The following 38 pages are in this category, out of 38 total. This list may not reflect recent changes. 0–9.
The properties of snoRNAs have enabled the development of programs to detect new examples of snoRNAs, including those that might be only distantly related to previously known examples. Computer programs implementing such approaches include snoscan and snoReport. Similarly, several algorithms have been developed to detect microRNAs.
New approaches There is study investigates the use of two-photon microscopy, a technique capable of imaging depths up to 800 μm through two-photon absorption, for visualizing microrobotic agents beneath biological tissue, demonstrating its transformative potential for both in vitro and in vivo microrobotics applications.