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Basic Bioinformatics Algorithms

 This section contains commonly used bioinformatics algorithms.Sequence AlignmentNeedleman–Wunsch algorithm: find global alignment between two sequencesSmith–Waterman algorithm: find local sequence alignmentBasic Local Alignment Search Tool also known as BLAST: an algorithm for comparing primary biological sequence informationDynamic time warping: measure similarity between two sequences which may vary in time or speedHirschberg's algorithm: finds the least cost sequence alignment between two sequences, as measured by their Levenshtein distanceRNA / Protein Structure PredictionChou–Fasman method: The Chou–Fasman method are an empirical technique for the prediction of secondary structures in proteins, originally developed in the 1970s.Nussinov Algorithm: Nussinov algorithm is an algorithm to predict possible RNA secondary structure (folding), discovering parts that have complementary sequences. Example Of Nussinov Algorithm.Kabsch algorithm: calculate the optimal alignment of two sets of points in order to compute the root mean squared deviation between two protein structures.StatisticsMarkov ModelsMarkov ChainsHidden Markov modelBaum–Welch algorithm: compute maximum likelihood estimates and posterior mode estimates for the parameters of a hidden markov modelForward-backward algorithm a dynamic programming algorithm for computing the probability of a particular observation sequenceViterbi algorithm: find the most likely sequence of hidden states in a hidden markov modelOptimization AlgorithmsEvolutionary computation: optimization inspired by biological mechanisms of evolutionSimulated annealingMachine Learning And Statistical ClassificationUPGMA: UPGMA (Unweighted Pair Group Method with Arithmetic Mean) is a simple agglomerative or hierarchical clustering method used in bioinformatics for the creation of phenetic trees (phenograms). Neighbor Joining: In bioinformatics, neighbor joining is a bottom-up clustering method for the creation of phenetic trees (phenograms), created by Naruya Saitou and Masatoshi Nei.
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