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http://www.lasige.di.fc.ul.pt/webtools/proteinon/

ProteInOn calculates semantic similarity between GO terms or proteins annotated with GO terms. It also calculates term enrichment of protein sets, by applying a term representativity score, and gives additional information on protein interactions. The query compute protein semantic similarity returns the semantic similarity scores between all proteins entered, in matrix format. The option Measure allows users to choose one of several semantic similarity measures: Resnik, Lin, or Jiang & Conrath's measures with or without the DCA approach, plus the graph-based simUI and simGIC measures. These measures are listed by order of performance as evaluated with protein sequence similarity. The option GO type allows users to choose one of the aspects of GO: molecular function, biological process and cellular component. The option Ignore IEA limits the query to non-electronic annotations, excluding evidence types: IEA, NAS, ND, NR.

Proper citation: ProteInOn (RRID:SCR_005740) Copy   

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http://knots.mit.edu/

The knot server allows the user to check PDB entries or uploaded structures for knots and to visualize them. The size of a knot is determined by deleting amino acids from both ends. This procedure is, however, not perfect and the resulting size should only be treated as a guideline. Mathematically, knots are only well defined in closed (circular) loops. However, both the N- and C-termini of open proteins are typically located close to the surface of the protein and can be connected unambiguously: We reduce the protein to its backbone and draw two lines outward starting at the termini in the direction of the connection line between the center of mass of the backbone and the respective ends. The two lines are joined by a big loop, and the structure is topologically classified by the determination of its Alexander polynomial. To determine an estimate for the size of the knotted core, we successively delete amino acids from the N-terminus until the protein becomes unknotted. The procedure is repeated at the C-terminus starting with the last N-terminal deletion structure that contained the original knot. For each deletion, the outward-pointing line through the new termini is parallel to the respective lines computed for the full structure. Unfortunately, the size of a knot is not always precisely determined by this procedure, so reported sizes should therefore only be treated as approximate. Sponsors: Knots is funded by MIT.

Proper citation: Protein Knots (RRID:SCR_008353) Copy   

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http://probeexplorer.cicancer.org/principal.php

Probe Explorer is an open access web-based bioinformatics application designed to show the association between microarray oligonucleotide probes and transcripts in the genomic context, but flexible enough to serve as a simplified genome and transcriptome browser. Coordinates and sequences of the genomic entities (loci, exons, transcripts), including vector graphics outputs, are provided for fifteen metazoa organisms and two yeasts. Alignment tools are used to built the associations between Affymetrix microarrays probe sequences and the transcriptomes (for human, mouse, rat and yeasts). Search by keywords is available and user searches and alignments on the genomes can also be done using any DNA or protein sequence query. Platform: Online tool

Proper citation: ProbeExplorer (RRID:SCR_007116) Copy   

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http://www.imtech.res.in/raghava/bhairpred/

Bhairpred server is based on machine learning technique SVM using single sequence information, evolutionary profile, predicted and observed secondary structure (as obtained using Psipred and DSSP), predicted and observed accessibility values (as obtainned from Netasa and DSSP). The methods were trained and tested on dataset of 2880 proteins and their performance was evaluated on dataset of 534 proteins used by Thornton (PNAS, 2002). Best prediction results were obtained with hybrid approach that combined prediction results from evolutionary profile, predicted secondary structure and accessibility.

Proper citation: SVM based method for predicting beta hairpin structures in proteins (RRID:SCR_008349) Copy   

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http://funspec.med.utoronto.ca/

FunSpec is a web-based tool for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations, including GO terms. FunSpec (an acronym for Functional Specification) inputs a list of yeast gene names, and outputs a summary of functional classes, cellular localizations, protein complexes, etc. that are enriched in the list. The classes and categories evaluated were downloaded from the MIPS Database and the GO Database . In addition, many published datasets have been compiled to evaluate enrichment against. Hypertext links to the publications are given. The p-values, calculated using the hypergeometric distribution, represent the probability that the intersection of given list with any given functional category occurs by chance. The Bonferroni-correction divides the p-value threshold, that would be deemed significant for an individual test, by the number of tests conducted and thus accounts for spurious significance due to multiple testing over the categories of a database. After the Bonferroni correction, only those categories are displayed for which the chance probability of enrichment is lower than: p-value/#CD where #CD is the number of categories in the selected database. Without the Bonferroni Correction, all categories are displayed for which the same probability of enrichment is lower than: p-value threshold in an individual test Note that many genes are contained in many categories, especially in the MIPS database (which are hierarchical) and that this can create biases for which FunSpec currently makes no compensation. Also the databases are treated as independent from one another, which is really not the case, and each is searched seperately, which may not be optimal for statistical calculations. Nonetheless, we find it useful for sifting through the results of clustering analysis, TAP pulldowns, etc. Platform: Online tool

Proper citation: FunSpec (RRID:SCR_006952) Copy   

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http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=tblastn&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome

Tool to search translated nucleotide databases using a protein query.

Proper citation: TBLASTN (RRID:SCR_011822) Copy   

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http://www.imtech.res.in/raghava/hslpred/

A support vector machine (SVM)-based method for the prediction of 4 major subcellular localization (cytoplasm, mitochondrial, nuclear and plasma membrane) of human proteins using various features such as i) amino acid composition, ii) dipeptide composition and iii) evolutionary information of proteins.

Proper citation: HSLPred (RRID:SCR_011972) Copy   

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http://jci-bioinfo.cn/iLoc-Plant

Data analysis service for predicting subcellular localization of plant proteins with single and multiple sites.

Proper citation: iLoc-Plant (RRID:SCR_011973) Copy   

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http://bio-cluster.iis.sinica.edu.tw/kbloc/index.html

A knowledge-based data analysis service to predict the localization site(s) of both single-localized and multi-localized proteins.

Proper citation: KnowPredsite (RRID:SCR_011974) Copy   

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http://bleoberis.bioc.cam.ac.uk/mcsm

Data analysis service to the study of missense mutations which relies on graph-based signatures.

Proper citation: mCSM (RRID:SCR_010776) Copy   

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http://gpcr.biocomp.unibo.it/bacello/

A predictor for the subcellular localization of proteins in eukaryotes that is based on a decision tree of several support vector machines (SVMs). It classifies up to four localizations for Fungi and Metazoan proteins and five localizations for Plant ones. BaCelLo's predictions are balanced among different classes and all the localizations are considered as equiprobable.

Proper citation: BaCelLo (RRID:SCR_011965) Copy   

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http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc/

A package of web-servers for predicting subcellular localization of proteins in different organisms.

Proper citation: Cell-PLoc (RRID:SCR_011966) Copy   

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http://cello.life.nctu.edu.tw/

A subCELlular LOcalization predictor based on a multi-class support vector machine (SVM) classification system. CELLO uses 4 types of sequence coding schemes: the amino acid composition, the di-peptide composition, the partitioned amino acid composition and the sequence composition based on the physico-chemical properties of amino acids. They combine votes from these classifiers and use the jury votes to determine the final assignment.

Proper citation: CELLO (RRID:SCR_011968) Copy   

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http://www.glycosciences.de/glycocd/

Manually curated, comprehensive repository of clusters of differentiation (CDs) which are a) defined as distinct oligosaccharide sequences as part of either glycoproteins and/or glycosphingolipids and b) defined as proteins which have carbohydrate recognition sites (CRDs) or as carbohydrate binding lectins. The data base is generated by exhaustive search of literature and other online data banks related to carbohydrates and proteins. This data bank is the beginning of an effort to provide concise, relevant information of carbohydrate-related CDs in a user- friendly manner. For users convenience the data bank under menu browse of GlycoCD is arranged in two section namely carbohydrate recognition CDs (CRD CD) and glycan CD. The carbohydrate recognition CD part is the collection of proteins which recognize glycan structures by means of the CRDs. Glycan CD is the part in which CDs are summarized which characterize specific oligosaccharide structures. The GlycoCD databank has been developed with the aim to assist the immunologist, cell biologist as well as the clinician who wants to keep up with the present knowledge in this field of glycobiology.

Proper citation: Glyco-CD (RRID:SCR_001574) Copy   

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https://circinteractome.nia.nih.gov/

Web tool for exploring circular RNAs and their interacting proteins and microRNAs. Predicts the miRNAs which can potentially target the circRNA.

Proper citation: Circular RNA Interactome (RRID:SCR_016304) Copy   

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http://sbcb.bioch.ox.ac.uk/cgdb/

A database of membrane protein/lipid interactions by coarse-grained molecular dynamics simulations.

Proper citation: CGDB (RRID:SCR_011959) Copy   

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https://pathoman.mskcc.org/

Web application to automate germline genomic variant curation from clinical sequencing based on ACMG guidelines. Aggregates multiple tracks of genomic, protein and disease specific information from public sources.

Proper citation: PathoMAN (RRID:SCR_026552) Copy   

•   Source: SciCrunch Registry

http://blanco.biomol.uci.edu/membrane_proteins_xtal.html

Table providing information about integral membrane proteins whose crystallographic, or sometimes NMR, structures have been determined to a resolution sufficient to identify TM helices of helix-bundle membrane proteins (typically 4 - 4.5 angstroms). It is based upon Preusch et al. (1998) as revised by White & Wimley (1999). Reference is made to all of the protein types whose structures have been determined. They have attempted to make the database as inclusive as possible.

Proper citation: Mpstruct (RRID:SCR_013284) Copy   

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http://www.uniprot.org/program/Chordata

Data set of manually annotated chordata-specific proteins as well as those that are widely conserved. The program keeps existing human entries up-to-date and broadens the manual annotation to other vertebrate species, especially model organisms, including great apes, cow, mouse, rat, chicken, zebrafish, as well as Xenopus laevis and Xenopus tropicalis. A draft of the complete human proteome is available in UniProtKB/Swiss-Prot and one of the current priorities of the Chordata protein annotation program is to improve the quality of human sequences provided. To this aim, they are updating sequences which show discrepancies with those predicted from the genome sequence. Dubious isoforms, sequences based on experimental artifacts and protein products derived from erroneous gene model predictions are also revisited. This work is in part done in collaboration with the Hinxton Sequence Forum (HSF), which allows active exchange between UniProt, HAVANA, Ensembl and HGNC groups, as well as with RefSeq database. UniProt is a member of the Consensus CDS project and thye are in the process of reviewing their records to support convergence towards a standard set of protein annotation. They also continuously update human entries with functional annotation, including novel structural, post-translational modification, interaction and enzymatic activity data. In order to identify candidates for re-annotation, they use, among others, information extraction tools such as the STRING database. In addition, they regularly add new sequence variants and maintain disease information. Indeed, this annotation program includes the Variation Annotation Program, the goal of which is to annotate all known human genetic diseases and disease-linked protein variants, as well as neutral polymorphisms.

Proper citation: UniProt Chordata protein annotation program (RRID:SCR_007071) Copy   

•   Source: SciCrunch Registry

http://www.Ablynx.com

A biopharmaceutical company engaged in the discovery and development of Nanobodies, a novel class of antibody-derived therapeutic proteins based on single-domain antibody fragments, for a range of serious life-threatening human diseases including inflammation, hematology, oncology and pulmonary disease.

Proper citation: Ablynx (RRID:SCR_002940) Copy   

•   Source: SciCrunch Registry