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http://bioinformatics.biol.uoa.gr/PRED-TMBB/

A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops.

Proper citation: PRED-TMBB (RRID:SCR_006190) Copy   

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http://tardis.nibio.go.jp/homstrad/

A curated database of structure-based alignments for homologous protein families. All known protein structure are clustered into homologous families (i.e., common ancestry), and the sequences of representative members of each family are aligned on the basis of their 3D structures using the programs MNYFIT, STAMP and COMPARER. These structure-based alignments are annotated with JOY and examined individually.

Proper citation: HOMSTRAD - Homologous Structure Alignment Database (RRID:SCR_006544) Copy   

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http://athina.biol.uoa.gr/PRED-TMR2/

A web server that classifies proteins into two classes from their sequences alone: the membrane protein class and the non-membrane protein class. This may be important in the functional assignment and analysis of open reading frames (ORF''s) identified in complete genomes and, especially, those ORF''s that correspond to proteins with unknown function. The network has a simple hierarchical feed-forward topology and a limited number of neurons which makes it very fast. By using only information contained in 11 protein sequences, the method was able to identify, with 100% accuracy, all membrane proteins with reliable topologies collected from several papers in the literature. Applied to a test set of 995 globular, water-soluble proteins, the neural network classified falsely 23 of them in the membrane protein class (97.7% of correct assignment). The method was also applied to the complete SWISS-PROT database with considerable success and on ORF''s of several complete genomes. The neural network developed was associated with the PRED-TMR algorithm (Pasquier,C., Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a new application package called PRED-TMR2.

Proper citation: PRED-TMR2 (RRID:SCR_006205) Copy   

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http://amp.pharm.mssm.edu/l2n/upload/register.php

A web-based software system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system.

Proper citation: Lists2Networks (RRID:SCR_006323) Copy   

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http://athina.biol.uoa.gr/PRED-TMR/

A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35).

Proper citation: PRED-TMR (RRID:SCR_006203) Copy   

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http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

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http://chemistry.st-andrews.ac.uk/staff/jbom/group/databases.html

It is a publicly available web-based database that aims to provide further understanding of protein-ligand interactions. It''s a resource containing biomolecular data, including binding energies, Tanimoto ligand similarity scores and protein sequence similarities of protein-ligand complexes. The PLD contains biomolecular data including calculated binding energies, Tanimoto ligand similarity scores and protein percentage sequence similarities. The database has potential for application as a tool in molecular design.

Proper citation: Protein Ligand Database (RRID:SCR_006980) Copy   

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http://ekhidna.biocenter.helsinki.fi/dali/start

Resource out of service. Documented on May, 5th, 2021.The Dali Database is based on all-against-all 3D structure comparison of protein structures in the Protein Data Bank (PDB). The structural neighborhoods and alignments are automatically maintained and regularly updated using the Dali search engine. The Dali Database contains structural alignments of PDB90 versus the full PDB using DaliLite. The data can be viewed interactively here, or downloaded in its entirety Users may search by PDB identifier or keyword.

Proper citation: Dali database (RRID:SCR_006974) Copy   

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http://www.ncbi.nlm.nih.gov/CCDS/

Database (anonymous FTP) resulting from a collaborative effort to identify a core set of human and mouse protein coding regions that are consistently annotated and of high quality. The long term goal is to support convergence towards a standard set of gene annotations. Collaborators are EBI, NCBI, UCSC, WTSI and the initial results are also available from the participants'''' genome browser Web sites. In addition, CCDS identifiers are indicated on the relevant NCBI RefSeq and Entrez Gene records and in Map Viewer displays of RNA (RefSeq) and Gene annotations on the reference assembly.

Proper citation: Consensus CDS (RRID:SCR_006729) Copy   

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http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/

A database of interactions between HIV-1 and human proteins published in the peer-reviewed literature. The goal is to provide a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. For each HIV-1 human protein interaction the following information is provided: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * PubMed identification numbers (PMIDs) for all journal articles describing the interaction. In addition, all protein-protein interactions documented in the database are integrated into Entrez Gene records and listed in the ''HIV-1 protein interactions'' section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

Proper citation: HIV-1 Human Protein Interaction Database (RRID:SCR_006879) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://rkd.ucdavis.edu/interactome.shtml

It was created to host functional genomic information gathered as part of a large NSF funded rice kinase proteomics project. The goal is to integrate disparate data sets into a logical, user friendly format. To accomplish this, they have developed a platform to display user selected functional genomic data on a phylogenetic tree. The RKD also includes an interactive chromosomal map showing the positions of all rice kinases and an interactive protein-protein interaction maps.

Proper citation: Rice Kinase Database (RRID:SCR_006990) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/cuticleDB

A relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the five sequenced genomes where manual annotation has been applied to cuticular proteins: Anopheles gambiae, Apis mellifera, Bombyx mori, Drosophila melanogaster, and Nasonia vitripennis. Some sequences were confirmed as authentic cuticular proteins because protein sequencing revealed that they were present in cuticle; others were identified by sequence homology and other criteria. Entries provides information about whether sequences are putative or authentic cuticular proteins. CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

Proper citation: CuticleDB (RRID:SCR_007045) Copy   

•   Source: SciCrunch Registry

http://www.signaling-gateway.org/molecule/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Relational database of all significant published qualitative and quantitative information on cell signaling proteins. The Molecule Pages database was developed with the specific aim of allowing interactions, and indeed whole pathways, to be modeled. The goal is to filter the data to present only validated information. In addition, the Gateway is the home of Signaling Update, which provides a one-stop overview of the latest and hottest research in cell signaling for both the specialist and non-specialist alike.

Proper citation: UCSD-Nature Signaling Gateway Molecule Pages (RRID:SCR_006907) Copy   

•   Source: SciCrunch Registry

http://www.dddc.ac.cn/pdtd/

It is a dual function database that associates an informatics database to a structural database of known and potential drug targets. PDTD is a comprehensive, web-accessible database of drug targets, and focuses on those drug targets with known 3D-structures. PDTD contains 1207 entries covering 841 known and potential drug targets with structures from the Protein Data Bank (PDB). Drug targets of PDTD were categorized into 15 and 13 types according to two criteria: therapeutic areas and biochemical criteria. The database supports extensive searching function using PDB ID, target name and category, related disease.

Proper citation: Potential Drug Target Database (RRID:SCR_007069) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/COG

A database for phylogenetic classification for proteins encoded in complete genomes. Clusters of Orthologous Groups of proteins (COGs) were delineated by comparing protein sequences encoded in complete genomes, representing major phylogenetic lineages. Each COG consists of individual proteins or groups of paralogs from at least 3 lineages and thus corresponds to an ancient conserved domain. Please be aware that COGs hasn't been updated in many years and will not be.

Proper citation: COG (RRID:SCR_007139) Copy   

•   Source: SciCrunch Registry

http://murphylab.web.cmu.edu/services/SLIF/

SLIF finds fluorescence microscope images in on-line journal articles, and indexes them according to cell line, proteins visualized, and resolution. Images can be accessed via the SLIF Web database. SLIF takes on-line papers and scans them for figures that contain fluorescence microscope images (FMIs). Figures typically contain multiple FMIs, to SLIF must segment these images into individual FMIs. When the FMI images are extracted, annotations for the images (for instance, names of proteins and cell-lines) are also extracted from the accompanying caption text. Protein annotation are also used to link to external databases, such as the Gene Ontology DB. The more detailed process includes: segmentation of images into panels; panel classification, to find FMIs; segmentation of the caption, to find which portions of the caption apply to which panels; text-based entity extraction; matching of extracted entities to database entries; extraction of panel labels from text and figures; and alignment of the text segments to the panels. Extracted FMIs are processed to find subcellular location features (SLFs), and the resulting analyzed, annotated figures are stored in a database, which is accessible via SQL queries.

Proper citation: Subcellular Location Image Finder (RRID:SCR_006723) Copy   

•   Source: SciCrunch Registry

http://www.disprot.org/

The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Users can BLAST sequences, browse by protein name, or view by protein function and functional subclass.

Proper citation: DisProt - Database of Protein Disorder (RRID:SCR_007097) Copy   

•   Source: SciCrunch Registry

http://gbrowse.org/

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

Proper citation: GBrowse (RRID:SCR_006829) Copy   

•   Source: SciCrunch Registry