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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.
Whereas traditional bioinformatics is a wide subject it has a large focus on molecular biology, pharmaceutical bioinformatics more specifically targets chemical-biological interaction and exploratory focus of chemical and biological interactors using e.g. cheminformatics and chemometrics methods.
The main idea behind the field is to integrate different informatics branches (e.g. bioinformatics, chemoinformatics, immunoinformatics, etc.) into a single platform, resulting in a seamless process of drug discovery. The first reference of the term "Pharmacoinformatics" can be found in the year of 1993. [1]
Rosalind is an educational resource and web project for learning bioinformatics through problem solving and computer programming. [1] [2] [3] Rosalind users learn bioinformatics concepts through a problem tree that builds up biological, algorithmic, and programming knowledge concurrently or learn by topics, with the topic of Alignment, Combinatorics, Computational Mass Spectrometry, Heredity ...
Bioinformatics and computational biology are interdisciplinary fields of research, development and application of algorithms, computational and statistical methods for management and analysis of biological data, and for solving basic biological problems.
Other non-free, shareware programs include ICM-Browser, [23] MDL Chime, UCSF Chimera, Swiss-PDB Viewer, [24] StarBiochem [25] (a Java-based interactive molecular viewer with integrated search of protein databank), Sirius, and VisProt3DS [26] (a tool for Protein Visualization in 3D stereoscopic view in anaglyph and other modes), and Discovery ...
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 ]
The component programs of phylip use several different formats, all of which are relatively simple. Programs for the analysis of DNA sequence alignments, protein sequence alignments, or discrete characters (e.g., morphological data) can accept those data in sequential or interleaved format, as shown below.