Tools   Select Another Resource Report Type

http://www.kegg.jp/

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

Proper citation: KEGG (RRID:SCR_012773) Copy   

•   Source: SciCrunch Registry

http://www.kegg.jp/kegg/download/kegtools.html

Freely available desktop applications including KegHier: Java application for browsing BRITE hierarchy files, KegArray: Java application for microarray data analysis, and KegDraw: Java application for drawing compound and glycan structures. They run on the Mac OS X, Windows, and Linux platforms.

Proper citation: KegTools (RRID:SCR_006432) 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.ebi.ac.uk/thornton-srv/databases/FunTree/

FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.

Proper citation: FunTree (RRID:SCR_006014) Copy   

•   Source: SciCrunch Registry

http://prodoric.tu-bs.de/

Database about gene regulation and gene expression in prokaryotes. It includes a manually curated and unique collection of transcription factor binding sites. A variety of bioinformatics tools for the prediction, analysis and visualization of regulons and gene reglulatory networks is included. The integrated approach provides information about molecular networks in prokaryotes with focus on pathogenic organisms. In detail this concerns: * transcriptional regulation (transcription factors and their DNA binding sites * signal transduction (two-component systems, phosphylation cascades) * protein interactions (complex formation, oligomerization) * biochemical pathways (chemical reactions) * other regulation events (e.g. codon usage, etc. ...) It aims to be a resource to model protein-host interactions and to be a suitable platform to analyze high-throughput data from proteomis and transcriptomics experiments (systems biology). Currently it mainly contains detailed information about operon and promoter structures including huge collections of transcription factor binding sites. If an appropriate number of regulatory binding sites is available, a position weight matrix (PWM) and a sequence logo is provided, which can be used to predict new binding sites. This data is collected manually by screening the original scientific literature. PRODORIC also handles protein-protein interactions and signal-transduction cascades that commonly occur in form of two-component systems in prokaryotes. Furthermore it contains metabolic network data imported from the KEGG database., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRODORIC (RRID:SCR_007074) Copy   

•   Source: SciCrunch Registry

http://metlin.scripps.edu/

A public repository of metabolite information as well as tandem mass spectrometry data is provided to facilitate metabolomics experiments. It contains structures and represents a data management system designed to assist in a broad array of metabolite research and metabolite identification. An annotated list of known metabolites and their mass, chemical formula, and structure are available. Each metabolite is linked to outside resources for further reference and inquiry. MS/MS data is also available on many of the metabolites.

Proper citation: METLIN (RRID:SCR_010500) Copy   

•   Source: SciCrunch Registry

http://neurowiki.alleninstitute.org/index.php/Main_Page

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 6, 2016. The Allen Institute Neurowiki is a joint project between Vulcan Inc. and the Allen Institute to build a Semantic Wiki mapping genetic instances. It is a finished prototype testing the import pipelines and display componenets for combining 5 major RDF datasets from 4 different sources. Current planning includes mapping complete datasets, curating a better ontology, and creating multiple ontology management for a user class. Biological Linked Data Map: * Open, public online access * Data from multiple RDF data stores * Complete import pipeline using LDIF framework * Outlines of each imported instance embedding inline wiki properties and providing views of imported properties from original RDF datasets * Charting tools that ''''pivot'''' SPARQL queries providing several views of each query * Navigation and composition tools for accessing and mining the data Where did we get the data? * KEGG: Kyoto Encyclopedia of Genes and Genomes: KEGG GENES is a collection of gene catalogs for all complete genomes generated from publicly available resources, mostly NCBI RefSeq * Diseasome: The Diseasome website is a disease / disorder relationships explorer and a sample of an innovative map-oriented scientific work. Built by a team of researchers and engineers, it uses the Human Disease Network dataset. * DrugBank: The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug data with comprehensive drug target information. * Sider: Sider contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. Every piece of content on every instance page is generated by Semantic Result Formatters interpreting SPARQL results.

Proper citation: Allen Institute Neurowiki (RRID:SCR_005042) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.charite.de/synsysnet/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. A curated database for synaptic proteins that provides adequate definitions of pre- and post-synaptic proteins, proteins present in sub-domains of the synapse, e.g. the synaptic vesicle and associated proteins, lipid rafts and postsynaptic density. In addition to data that was and will be gathered from the experiments conducted within SynSys - A European expertise Network on building the synapse, they have extracted and manually curated all relevant data on these proteins from other sources and provided an ontology for these. Novel splice forms are being identified that can be matched with proteomics data. Information on proteins, their 3D structure, binding small molecules Protein-Protein-Interactions (PPIs) and Compound-Protein-Interactions are integrated. Proteins or compounds can be searched and Interactive Networks can be visualized. The point Diseases present neurological diseases, to illustrate the role of SynSysNet in the medication.

Proper citation: SynSysNet (RRID:SCR_003180) Copy   

•   Source: SciCrunch Registry