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UCLUST
A clustering method that exploits USEARCH to assign sequences to clusters. UCLUST is superior to CD-HIT. It is usually significantly faster, uses significantly less memory, can cluster at lower identities and is more sensitive. While CD-HIT often fails to identify the closest cluster, or overlooks that a match is possible (false negative), UCLUST rarely misses a match and in most cases finds the best possible match. UCLUST also enables rapid clustering of much larger numbers of sequences.
ModClus
Clusters protein structures based on their sequence and structure similarities. ModClus consist of the following steps: (i) the first chain in the list seeds the first cluster; (ii) the next chain is compared by sequence and/or structure to all chains in each of the existing clusters and either joins the first sufficiently similar cluster or seeds a new cluster. The clustering depends on user-defined thresholds for structure and sequence similarities. ModClus allows clustering both a list of chains or from a chain.
DACE / DP-means Algorithm for Clustering Extremely large sequencing data
Permits to efficiently cluster extremely large sequencing data for de novo operational taxonomic units (OTUs) picking. DACE is a scalable parallel DP-means algorithm with a distance preserving random projection (LSH) method for data partitioning. DACE is able to outperformed most state-of-the-art programs in terms of both accuracy and efficiency and, could be an ideal tool for clustering very large sequencing data.
evoclust3d
Detects spatially clustered substitution in protein phylogenies. evoclust3d combines the P3D measure of spatial substitution clustering with ancestral sequence reconstruction to identify substitution clustering at specific branches of phylogenetic trees. To assess the utility of this approach, a large-scale screen of vertebrate protein families was performed in order to detect branch-specific substitution clustering, and compared results to predictions of positive selection by the branch-site test.
Gc / Granular clustering
A clustering algorithm to obtain partial protein models which is based on the granular clustering paradigm. The general principles of GC are as follows: primitive information granules are created from the input data elements; clustering is carried out by growing information granules; clustering is stopped when enough data condensation is achieved. Gc is especially useful in applications where partial models covering different fragments of the protein sequence, possibly providing alternative conformations, are sufficient. The GC approach operates in a much larger search space, since the decoy data are initially granulated down to the level of a single residue.
DASP3
Identifies sequences from databases that share motifs similar to a query active site profile. DASP3 is a modification of previously published software, Deacon Active Site Profiler (DASP). DASP3 is significantly more efficient and versatile than DASP, a requirement for the iterative processes used to cluster proteins into functionally relevant groups. It produces better separation between true positives and false positives and shows improved ability to accurately and efficiently cluster the Peroxire-doxin (Prx) superfamily into functionally relevant groups using two recently developed iterative processes. As an automated algorithm, DASP3 identifies functional groups better than previous versions of the software and rivals expert manual curation in the Structure-Function Linkage Database (SFLD).
VSEARCH
Processes and prepares metagenomics, genomics and population genomics nucleotide sequence data.. VSEARCH is an alternative to the USEARCH tool. It includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching, clustering by similarity, chimera detection, dereplication, pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication.
CABRA / Cluster and Annotate Blast Results Algorithm
Provides a shortcut to the evaluation of a BLAST result where its clustering of hits allows a quick classification. CABRA integrates the advantages of a BLAST search and FastaHerder clustering algorithm into a single pipeline by annotating BLAST results clusters. Simplification and annotation of the results of a typical similarity search, as well as its ease of use and speed, provide an appropriate method of one-dimensional similarity search. The ability to set the identity threshold to group together query-like sequences is also an improvement over current clustering approaches.
Family-Companion
Offers a platform for computing, investigating and sharing of homology groups. Family Companion allows the following features (i) homology cluster computation and automatic analyses, including inference of homology clusters, and generation of core, pan proteomes and species-specific proteins; (ii) visualization solutions, allowing users to display charts, Venn diagrams as well as phylogenic profiles. The application also permits the building of specific queries and possibility to share analysis between multiples users.
Arion 4 Omics
A high performance, ‘end-to-end’ analysis pipeline for the classification of omics profiles. Incorporating highly parallel architecture and sophisticated database technologies to overcome inherent technology based bottlenecks, currently faced in the Life Science research path. Arion is a scalable platform providing rapid exploratory analysis via machine learning, visualisation and statistical modules with topology planned for a future release. Integrated quality checks with result traceability provide data safeguarding and ensure the accuracy of delivered results.
MACSIMS / Multiple Alignment of Complete Sequences Information Management System
Obsolete
Allows management of all the information related to a protein family. MACSIMS is a multiple alignment-based information management system that combines knowledge-based methods with complementary ab initio sequence-based predictions for protein family analysis. The software can be used to integrate information from different domains, such as genetics, structural biology, proteomics or interactomics experiment. It incorporates the JalView alignment editor for graphically displaying the results.
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