the original mRNA. Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with a similarity over a...

statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem. The appropriate clustering algorithm and parameter...

k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which...

Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. At the beginning of the process, each element is in a cluster of its...

{\displaystyle j} . The general approach to spectral clustering is to use a standard clustering method (there are many such methods, k-means is discussed...

specifically in general topology and related branches, a net or Moore–Smith sequence is a function whose domain is a directed set. The codomain of this function...

are clustered de novo. Hierarchical clustering algorithms (HCA): uclust & cd-hit & ESPRIT Bayesian clustering: CROP Phylotype Amplicon sequence variant...

single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at...

50% sequence identity, respectively, to the longest sequence. Clustering sequences significantly reduces database size, enabling faster sequence searches...

computation Nanorod, in nanotechnology and materials science Non-redundant sequence clustering, in genetics and bioinformatics NR Vulpeculae, a red supergiant star...

§ Brackets and transcription delimiters. In linguistics, a consonant cluster, consonant sequence or consonant compound is a group of consonants which have no...

definition of a cluster or accumulation point of a sequence generalizes to nets and filters. The similarly named notion of a limit point of a sequence (respectively...

In computer science, data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data,...

a sequence that characterize the sequence. In Sequence analysis in social sciences, representative sequences are used to summarize sets of sequences describing...

various algorithms—Decision trees, clustering algorithm, Naive Bayes algorithm, time series analysis, sequence clustering algorithm, linear and logistic regression...

sequences using clustering. Cleaning then ensures the removal of any confounding elements. Next there is the discovery stage. In this phase sequences...

In astronomy, the main sequence is a classification of stars which appear on plots of stellar color versus brightness as a continuous and distinctive band...

in the cluster with comparable luminosity and thus differs from the main-sequence stars formed early in the cluster's existence. Some clusters have two...

a degree of belonging to clusters FLAME clustering (Fuzzy clustering by Local Approximation of MEmberships): define clusters in the dense parts of a dataset...

example: BLAST - DNA sequence similarity search BLASTp - Protein sequence similarity search OrthoFinder - Method for clustering proteins into families...

motivation behind social sequence analysts' use of optimal matching, clustering, and related methods to identify common "classes" of sequences at all levels of...

operational clustering units altogether. Therefore, ASVs represent a finer distinction between sequences. ASVs are also referred to as exact sequence variants...

Density-Based Clustering Validation (DBCV) is a metric designed to assess the quality of clustering solutions, particularly for density-based clustering algorithms...

simple clustering criteria, in regard to the requested similarity threshold T. The first criterion states that any given cluster's centroid sequence will...

Sequence homology is the biological homology between DNA, RNA, or protein sequences, defined in terms of shared ancestry in the evolutionary history of...

analysis in social sciences – Analysis of sets of categorical sequences Sequence clustering Sequence labeling Mabroukeh, N. R.; Ezeife, C. I. (2010). "A taxonomy...

identified in a stellar cluster, they have a higher effective temperature than the main sequence turnoff point for the cluster, where ordinary stars begin...

plotted for an open cluster, most stars lie on the main sequence. The most massive stars have begun to evolve away from the main sequence and are becoming...

embedded clusters may be home to various types of young stellar objects including protostars and pre-main-sequence stars. An example of an embedded cluster is...

CRISPR (/ˈkrɪspər/; acronym of clustered regularly interspaced short palindromic repeats) is a family of DNA sequences found in the genomes of prokaryotic...