Search results
Results from the WOW.Com Content Network
Sequence databases: import, maintain, view, and export, and interact with a massive number of sequences. Homology finding: rapidly query sequences for homologous hits among a set of target sequences or genomes.
Significant increase in time to map reads with mismatches (or color errors). Uses an iterative version of the Rabin-Karp string search algorithm. Yes Free, GPL: SparkBWA Integrates the Burrows–Wheeler Aligner (BWA) on an Apache Spark framework running atop Hadoop. Version 0.2 of October 2016, supports the algorithms BWA-MEM, BWA-backtrack ...
DECIPHER is a web-based resource and database of genomic variation data from analysis of patient DNA. [ 1 ] [ 2 ] [ 3 ] It documents submicroscopic chromosome abnormalities ( microdeletions and duplications ) and pathogenic sequence variants (single nucleotide variants - SNVs, Insertions, Deletions, InDels), from over 25000 patients and maps ...
Filter algorithms are general preprocessing algorithms that do not assume the use of a specific classification method. Wrapper algorithms, in contrast, “wrap” the feature selection around a specific classifier and select a subset of features based on the classifier's accuracy using cross-validation.
A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.
The Smith-Waterman algorithm was an extension of a previous optimal method, the Needleman–Wunsch algorithm, which was the first sequence alignment algorithm that was guaranteed to find the best possible alignment. However, the time and space requirements of these optimal algorithms far exceed the requirements of BLAST.
The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. [1] More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access ...
EPIC-seq can also aid with the classification of cell-of-origin (COO) subtypes in DLBCL. By analyzing epigenetic and transcriptional signatures, EPIC-seq-derived classifiers provide valuable insights into tumor heterogeneity and molecular subtyping, providing valuable insights for tailored treatment strategies. [1]