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http://www.tanpaku.org/autophagy/

Database that provides basic, up-to-date information on relevant literature, and a list of autophagy-related proteins and their homologs in eukaryotes.

Proper citation: Autophagy Database (RRID:SCR_002671) Copy   

•   Source: SciCrunch Registry

http://domine.utdallas.edu

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. Database of known and predicted protein domain (domain-domain) interactions containing interactions inferred from PDB entries, and those that are predicted by 8 different computational approaches using Pfam domain definitions. DOMINE contains a total of 26,219 domain-domain interactions (among 5,410 domains) out of which 6,634 are inferred from PDB entries, and 21,620 are predicted by at least one computational approach. Of the 21,620 computational predictions, 2,989 interactions are high-confidence predictions (HCPs), 2,537 interactions are medium-confidence predictions (MCPs), and the remaining 16,094 are low-confidence predictions (LCPs). (May 2014)

Proper citation: DOMINE: Database of Protein Interactions (RRID:SCR_002399) Copy   

•   Source: SciCrunch Registry

http://bioinf-apache.charite.de/supertarget_v2/

Database for analyzing drug-target interactions, it integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present (May 2013), the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range.

Proper citation: SuperTarget (RRID:SCR_002696) Copy   

•   Source: SciCrunch Registry

http://www.bindingmoad.org/

Database of protein-ligand crystal structures that is a subset of the Protein Data Bank (PDB), containing every high-quality example of ligand-protein binding. The resolved protein crystal structures with clearly identified biologically relevant ligands are annotated with experimentally determined binding data extracted from literature. A viewer is provided to examine the protein-ligand structures. Ligands have additional chemical data, allowing for cheminformatics mining. The binding-affinity data ranges 13 orders of magnitude. The issue of redundancy in the data has also been addressed. To create a nonredundant dataset, one protein from each of the 1780 protein families was chosen as a representative. Representatives were chosen by tightest binding, best resolution, etc. For the 1780 best complexes that comprise the nonredundant version of Binding MOAD, 475 (27%) have binding data. This collection of protein-ligand complexes will be useful in elucidating the biophysical patterns of molecular recognition and enzymatic regulation. The complexes with binding-affinity data will help in the development of improved scoring functions and structure-based drug discovery techniques.

Proper citation: Binding MOAD (RRID:SCR_002294) Copy   

•   Source: SciCrunch Registry

http://edas2.bioinf.fbb.msu.ru/

Databases of alternatively spliced genes with data on the alignment of proteins, mRNAs, and EST. It contains information on all exons and introns observed, as well as elementary alternatives formed from them. The database makes it possible to filter the output data by changing the cut-off threshold by the significance level. It contains splicing information on human, mouse, dog (not yet functional) and rat (not yet functional). For each database, users can search by keyword or by overall gene expression. They can also view genes based on chromosomal arrangement or other position in genome (exon, intron, acceptor site, donor site), functionality, position, conservation, and EST coverage. Also offered is an online Fisher test.

Proper citation: EDAS - EST-Derived Alternative Splicing Database (RRID:SCR_002449) Copy   

•   Source: SciCrunch Registry

http://bioinf.gen.tcd.ie/casbah/

Database which contains information pertaining to all currently known caspase substrates.

Proper citation: CASBAH (RRID:SCR_002728) Copy   

•   Source: SciCrunch Registry

http://www.gensat.org/retina.jsp

Collection of images from cell type-specific protein expression in retina using BAC transgenic mice. Images from cell type-specific protein expression in retina using BAC transgenic mice from GENSAT project.

Proper citation: Retina Project (RRID:SCR_002884) Copy   

•   Source: SciCrunch Registry

http://www.genscript.com/psort/wolf_psort.html

Data analysis service for protein subcellular localization prediction.

Proper citation: WoLF PSORT (RRID:SCR_002472) Copy   

•   Source: SciCrunch Registry

http://fullmal.hgc.jp/index_ajax.html

FULL-malaria is a database for a full-length-enriched cDNA library from the human malaria parasite Plasmodium falciparum. Because of its medical importance, this organism is the first target for genome sequencing of a eukaryotic pathogen; the sequences of two of its 14 chromosomes have already been determined. However, for the full exploitation of this rapidly accumulating information, correct identification of the genes and study of their expression are essential. Using the oligo-capping method, this database has produced a full-length-enriched cDNA library from erythrocytic stage parasites and performed one-pass reading. The database consists of nucleotide sequences of 2490 random clones that include 390 (16%) known malaria genes according to BLASTN analysis of the nr-nt database in GenBank; these represent 98 genes, and the clones for 48 of these genes contain the complete protein-coding sequence (49%). On the other hand, comparisons with the complete chromosome 2 sequence revealed that 35 of 210 predicted genes are expressed, and in addition led to detection of three new gene candidates that were not previously known. In total, 19 of these 38 clones (50%) were full-length. From these observations, it is expected that the database contains approximately 1000 genes, including 500 full-length clones. It should be an invaluable resource for the development of vaccines and novel drugs. Full-malaria has been updated in at least three points. (i) 8934 sequences generated from the addition of new libraries added so that the database collection of 11,424 full-length cDNAs covers 1375 (25%) of the estimated number of the entire 5409 parasite genes. (ii) All of its full-length cDNAs and GenBank EST sequences were mapped to genomic sequences together with publicly available annotated genes and other predictions. This precisely determined the gene structures and positions of the transcriptional start sites, which are indispensable for the identification of the promoter regions. (iii) A total of 4257 cDNA sequences were newly generated from murine malaria parasites, Plasmodium yoelii yoelii. The genome/cDNA sequences were compared at both nucleotide and amino acid levels, with those of P.falciparum, and the sequence alignment for each gene is presented graphically. This part of the database serves as a versatile platform to elucidate the function(s) of malaria genes by a comparative genomic approach. It should also be noted that all of the cDNAs represented in this database are supported by physical cDNA clones, which are publicly and freely available, and should serve as indispensable resources to explore functional analyses of malaria genomes. Sponsors: This database has been constructed and maintained by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science (JSPS). This work was also supported by a Special Coordination Funds for Promoting Science and Technology from the Science and Technology Agency of Japan (STA) and a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports and Culture of Japan.

Proper citation: Full-Malaria: Malaria Full-Length cDNA Database (RRID:SCR_002348) Copy   

•   Source: SciCrunch Registry

http://www.nextprot.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 15,2025. Human protein knowledge platform. Knowledge platform for human proteins selects and filters high throughput data pertinent to human proteins from UniProtKB. Extends UniProtKB/Swiss-Prot annotations for human proteins to include several new data types.

Proper citation: neXtProt (RRID:SCR_008911) Copy   

•   Source: SciCrunch Registry

http://harvester.fzk.de/harvester/

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy   

•   Source: SciCrunch Registry

http://hdbase.org/cgi-bin/welcome.cgi

A community website for Huntington''s Disease (HD) research that currently contains Y2H and Mass spectrometry protein-protein interaction data centered around the HD protein (huntingtin) and information on therapeutic studies in mouse. Also available are raw Human and Mouse Affymetrix Microarray data. The protein interaction data is from several sources, including interactions curated from the literature by ISB staff, experimentally determined interactions produced by Bob Hughes and colleagues at Prolexys (currently password protected), and interactions reported in a recent publication by Goehler et al from Eric Wanker''s lab. Content areas that may be covered by the site include the following: * Therapeutic studies in mouse, primarily drug screens. * HD mouse models with a focus on timelines of disease progression. * Antibodies used in HD research. * Microarray gene expression studies. * Genes and proteins relevant to HD research. This includes HD itself, the growing list of proteins thought to interact directly or indirectly with huntingtin (Htt), and other genes and proteins implicated in the disease process. * Molecular pathways thought to be involved in the disease process. * Timelines of disease for Mouse models

Proper citation: HDBase (RRID:SCR_007132) Copy   

•   Source: SciCrunch Registry

http://www.aniseed.cnrs.fr/

Database of ascidian embryonic development at the level of the genome (cis-regulatory sequences, gene expression, protein annotation), of the cell (morphology, fate, induction, lineage) or of the whole embryo (anatomy, morphogenesis). Currently, four organism models are described in Aniseed: Ciona intestinalis, Ciona savignyi, Halocynthia roretzi and Phallusia mammillata.
This version supports four sets of Ciona intestinalis transcript models: JGI v1.0, KyotoGrail 2005, KH and ENSEMBL, all functionally annotated, and grouped into Aniseedv3.0 gene models. Users can explore their expression profiles during normal or manipulated development, access validated cis-regulatory regions, get the molecular tools used to assay gene function, or all articles related to the function, or regulation of a given gene. Known transcriptional regulators and targets are listed for each gene, as are the gene regulatory networks acting in individual anatomical territories.
ANISEED is a community tool, and the direct involvement of external contributors is important to optimize the quality of the submitted data. Virtual embryo: The 3D Virtual embryo is available to download in the download section of the website.

Proper citation: Ascidian Network for InSitu Expression and Embryological Data (RRID:SCR_013030) Copy   

•   Source: SciCrunch Registry

https://github.com/davidemms/OrthoFinder

Software Python application for comparative genomics analysis. Finds orthogroups and orthologs, infers rooted gene trees for all orthogroups and identifies all of gene duplcation events in those gene trees, infers rooted species tree for species being analysed and maps gene duplication events from gene trees to branches in species tree, improves orthogroup inference accuracy. Runs set of protein sequence files, one per species, in FASTA format.

Proper citation: OrthoFinder (RRID:SCR_017118) Copy   

•   Source: SciCrunch Registry

https://signor.uniroma2.it/

Software application to organize and store in structured format signaling information published in scientific literature. Information is stored as binary causative relationships between biological entities and can be represented graphically as activity flow. Each relationship is linked to literature reporting experimental evidence. Each node is annotated with chemical inhibitors that modulate its activity. Signaling information is mapped to human proteome. SIGNOR 2.0 stores manually annotated causal relationships between proteins and other biologically relevant entities including chemicals, phenotypes, complexes, etc with compliance to FAIR data principles.

Proper citation: SIGNOR (RRID:SCR_018485) Copy   

•   Source: SciCrunch Registry

http://drugdesigndata.org

Project portal's database of protein-ligand data sets provided by pharmaceutical partners that provide atomic details of drug mechanisms that will be used to improve computer-aided drug-design methods and thus accelerate drug discovery. The project aims to help companies release the high-quality data they have generated, which has incredible value to researchers working to improve methods of computer-aided drug discovery. Everyone stands to benefit from the ability to develop new medications more quickly and inexpensively. What computational chemists globally are trying to do is to make faster, more accurate, more predictive programs to speed up the process. Part of their mission is to engage the community in these challenges to test newly developed predictive algorithms.

Proper citation: Drug Design Data Resource (RRID:SCR_000497) Copy   

•   Source: SciCrunch Registry

https://github.com/Sung-Huan/ANNOgesic

Software tool for bacterial/archaeal RNA-Seq based genome annotations. Used for integrating, detecting, predicting, and grouping RNA-Seq data.

Proper citation: ANNOgesic (RRID:SCR_016326) Copy   

•   Source: SciCrunch Registry

http://cajadb.neuro.ufrn.br

Software application as an integrated web resource of marmoset biological data. Used to find genomic, expression and alternative splicing data to facilitate the study of animal model for neuropsychiatric and social behavior research and to support biological analyses such as functional (ontology) enrichment analysis and protein-protein-network.

Proper citation: CajaDB (RRID:SCR_016506) Copy   

•   Source: SciCrunch Registry

https://www.genome.jp/tools/dinies/

Web server for predicting unknown drug-target interaction networks from various types of biological data in the framework of supervised network inference.

Proper citation: DINIES (RRID:SCR_016505) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/jpred/

Software tool for protein secondary structure prediction from the amino acid sequence by the JNet algorithm. Makes also predictions on Solvent Accessibility and Coiled-coil regions.

Proper citation: Jpred (RRID:SCR_016504) Copy   

•   Source: SciCrunch Registry