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DALEL

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Searches the linear information in proteins. DALEL utilizes a novel parallel and recursive algorithm that allows divide the exploding space of enumeration and degeneration into much smaller spaces that can be built and searched very fast and in parallel. First, it enumerates all possible motifs of variable length including any number and combination of wildcards. Then, it degenerates the motifs to discover conserved and flexible individual and correlated residues.

SLiMSearch / Short, Linear Motif Search

Allows motif consensus search, annotation and filtering. SLiMSearch is a web-based tool for the discovery of novel short linear motifs (SLiM) instances in a proteome. The framework searches characterized motif specificity determinants to identify putative novel motif instances which are annotated with accessibility information, evolutionary attributes and experimental information. The software can aid biologists in building hypotheses and designing experiments by simplifying the analysis of the functional and evolutionary features of motifs.

HH-MOTiF / HH-MOtif-TreeFinder

Combines hidden Markov model (HHM) comparisons with a hierarchical representation of identified SLiMs in motif trees. HH-MOTiF is a web-server that can find remotely conserved motifs in data sets with low-complexity regions or high redundancy. It makes use of evolutionary information by creating HMMs for each input sequence and its orthologs. Finally, this method can detect several independent motif trees that occur in independent, possibly overlapping subsets of the provided input sequences.

QSLiMFinder

A modification of the basic SLiMFinder tool to specifically look for SLiMs shared by a query sequence and one or more additional sequences. To do this, SLiMBuild first identifies all motifs that are present in the query sequences before removing it (and its UPC) from the dataset. The rest of the search and stats takes place using the remainder of the dataset but only using motifs found in the query. The final correction for multiple testing is made using a motif space defined by the original query sequence, rather than the full potential motif space used by the original SLiMFinder. This is offset against the increased probability of the observed motif support values due to the reduction of support that results from removing the query sequence but could potentially still identify SLiMs will increased significance.

iELM / interactions of Eukaryotic Linear Motif

Provides a resource for predicting the function and positional interface for a subset of interactions mediated by short linear motifs (SLiMs). The iELM prediction algorithm is based on the annotated SLiM classes from the Eukaryotic Linear Motif (ELM) resource and allows users to explore both annotated and user-generated PPI networks for SLiM-mediated interactions. By incorporating the annotated information from the ELM resource, iELM provides functional details of PPIs. This can be used in proteomic analysis, for example, to infer whether an interaction promotes complex formation or degradation.

DILIMOT / DIscovery of LInear MOTifs

A server for the prediction of these short linear motifs within a set of proteins. Given a set of sequences sharing a common functional feature (e.g. interaction partner or localization) the method finds statistically over-represented motifs likely to be responsible for it. The input sequences are first passed through a set of filters to remove regions unlikely to contain instances of linear motifs. Motifs are then found in the remaining sequence and ranked according to a statistic that measure over-representation and conservation across homologues in related species. The results are displayed via a visual interface for easy perusal.

seeMotif

Aims to visualize sequence motifs on 3D structures related to a given reference protein. seeMotif provides an easy-to-use interface for submitting motifs in different formats. Visualizing the spatial characteristics of motifs in an interactive way and exploring the relationships between motifs in different structures largely help to understand how a cluster of particular residues affects protein functions. seeMotif will be regularly updated based on the newest release of UniProt, PROSITE, ELM and PDB databases.

fuzztran

Searches for patterns in nucleic acid sequences that are first translated to protein in the specified frame with a specified genetic code. fuzztran uses patterns based on the format of pattern used in the PROSITE database, with the difference that the terminating dot '.' and the hyphens, '-', between the characters are optional. Patterns can specify a search for an exact sequence or they can allow various ambiguities, matches to variable lengths of sequence and repeated subsections of the sequence.

fuzzpro

Searches for patterns in protein sequences. Fuzzpro selects the optimum searching algorithm to use, depending on the complexity of the search pattern specified. It also searches for a specified PROSITE-style pattern in protein sequences. Such patterns are specifications of a (typically short) length of sequence to be found. They can specify a search for an exact sequence or they can allow various ambiguities, matches to variable lengths of sequence and repeated subsections of the sequence.