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http://compbio.charite.de/phenomizer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 31,2026. Phenomizer offers three different approaches to find the appropriate term for a phenotypic abnormality, indicated by the three tabs on the left hand side: Feature, Disease and Ontology. The Phenomizer is intended to be used by qualified and licensed physicians in order to provide assistance in reaching the correct diagnosis in patients with hereditary diseases and for use as a teaching aid. The Phenomizer does not make diagnoses. Rather, it produces a ranked list of possibilities that can be used by physicians as a part of the diagnostic workup. The Phenomizer does not contain information about all possible diagnoses or even all possible hereditary diseases. The Phenomizer should not be used to make medical decisions without the advice of a physician.

Proper citation: Phenomizer (RRID:SCR_006157) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://biobankireland.com/

Biobank Ireland Trust promotes the development of an Irish Hospital Biobank Network to coordinate collection of small samples of cancer and normal tissue and coded patient data from those having a cancer operation. This will facilitate international molecular research collaborations, which may help identify the best treatment for each individual patient - personalized medicine. Biobank Ireland is promoting the development of a Hospital Biobank Network throughout the island of Ireland as a bridge between cancer research and care. This new infrastructure will facilitate large national and international translational research collaborations that will raise Ireland''s research profile and benefit those with cancer. Researchers will have online access to samples and to restricted patient data from participating hospitals and an equitable withdrawal process for scientifically and ethically approved projects. Important research results will be explained to the public. Other Objectives: * To facilitate (inter)national translational research collaborations that may lead to new tests and better, less toxic treatments for those with cancer * To enable molecular research on cancer tissue from clinical trials patients identify the best treatment for each individual patient ������??personalized medicine������?? * Researchers will have online access to samples and restricted patient data from participating hospitals, and a fair release process for scientifically and ethically approved projects * Biobank Ireland recognizes the need to have harmonization in biobanking around the world * Important research results will be explained to the public * Biobank Ireland will seek to have the hospital-based Biobank Network funded by government as standard of care

Proper citation: Biobank Ireland Trust (RRID:SCR_006430) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/geo/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.

Proper citation: NCBI Epigenomics (RRID:SCR_006151) Copy   

•   Source: SciCrunch Registry

http://www.neuralconnections.net/

Blog is first and foremost dedicated to circuitry, all the way from a small cluster of connections in a small brain area to wide-spread circuitry between several brain areas (local, regional and functional connectivity). My Philosophy (on neuroscience): I do not think that functions of the brain (and/or mind) can be localized to certain areas (modular zones). This is a distributed, interactive function in a neural network. Second, there is usually an underlying tone that relates to the hippocampus, and/or the post has a systems-level approach to it. Postings will most likely be in a review-esque fashion. This is really meant to be an information resource. I hope to get more opinion pieces in there sometime. Posts are usually what I am currently researching, interested in, or what I have previously done research on at one time. I also want to build a community of professionals and others interested in neuroscience and/or psychology (philosophy of mind, too!). The blog, in general, helps everything (the information) stay fresh in my mind.

Proper citation: Neural Connections (RRID:SCR_006986) Copy   

•   Source: SciCrunch Registry

http://commonfund.nih.gov/molecularlibraries/ipdc/index.aspx

A core synthesis facility dedicated to the preparation of imaging probes, initially for intramural NIH scientists, and later, for the extramural scientific community. The IPDC provides a mechanism for the production of sensitive probes for use by imaging scientists who cannot obtain such probes commercially. The probes to be made will encompass all major imaging modalities including radionuclide, magnetic resonance, and optical. Nearly all of these imaging probes are not commercially available, nor are they viable commercial products, and most are new compositions-of-matter (http://nihlibrary.ors.nih.gov/ipdcdb/IPDCDB_Search.asp). The IPDC was born from the realization that imaging technologies will be crucial in basic, translational, and clinical research in the 21st century, and that the synthetic chemistry required to reliably produce imaging probes lies at the heart of research within imaging technologies. To this end, the IPDC has recruited the equipment and expertise to concurrently synthesize multiple types of imaging probes for bioscientists with diverse research interests, encompassing all imaging modalities, including optical, radionuclide, ultrasound, and magnetic resonance. The IPDC embodies an exciting new approach to apply and combine chemistry and imaging sciences toward specific problems in biology and medical sciences, and will be a truly interdisciplinary effort aimed at maximizing returns from the revolutionary new discoveries being described in modern imaging. A significant part of the IPDC will also be directed, independently, to the discovery of new imaging approaches and compositions. The IPDC houses scientific staff, mostly chemists, who have interests and expertise in one or more aspects of molecular imaging. The IPDC is generating known and novel imaging probes for targeting receptors, cells, and tissues, and for preclinical in vivo evaluations by its intramural collaborators. Many such interesting agents have been described in the scientific literature, but are often not explored further due to lack of a reliable supply of reagent. One aspect of the IPDC''s mission is to rectify this situation. IPDC-supplied reagents will not be limited to one imaging modality, but will include the flexible application of diverse technologies. Also, the IPDC will seek to develop novel state-of-the-art imaging probes in collaboration with biological and biomedical intramural scientists who can provide or suggest suitable targeting agent/receptor pairs. The Imaging Probe Development Center (IPDC) was initiated in the incubator space of the Common Fund and has transitioned to the intramural program of the National Heart, Lung, and Blood Institute.

Proper citation: Imaging Probe Development Center (IPDC) (RRID:SCR_006744) Copy   

•   Source: SciCrunch Registry

http://www.bioinsilico.org/cgi-bin/CAPSDB/staticHTML/home

It is a structural classification of helix-cappings or caps compiled from protein structures. Caps extracted from protein structures have been structurally classified based on geometry and conformation and organized in a tree-like hierarchical classification where the different levels correspond to different properties of the caps. CASP-DB is fully browsable and searchable and is regularly updated. The regions of the polypeptide chain immediately preceding or following a helix are known as Nt- and Ct cappings, respectively. Cappings play a central role stabilizing helices due to lack of intrahelical hydrogen bonds in the first and last turn. Sequence patterns of amino acid type preferences have been derived for cappings but the structural motifs associated to them are still unclassified. CAPS-DB is a database of clusters of structural patterns of different capping types. The clustering algorithm is based in the geometry and the space conformation of these regions. CAPS-DB is a relational database that allows the user to search, browse, inspect and retrieve structural data associated to cappings. The contents of CAPS-DB might be of interest to a wide range of scientist covering different areas such as protein design and engineering, structural biology and bioinformatics. CapsDB v4.0 * PDB structures: 4591 * Number of clusters: 859 * Number of caps: 31452

Proper citation: CAPS Database (RRID:SCR_006862) Copy   

•   Source: SciCrunch Registry

http://scop.mrc-lmb.cam.ac.uk/scop/

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases.

Proper citation: SCOP: Structural Classification of Proteins (RRID:SCR_007039) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.physionet.org/physiobank/database/gaitndd/

Database of records from patients with Parkinson's disease (n = 15), Huntington's disease (n = 20), or amyotrophic lateral sclerosis (n = 13). Records from 16 healthy control subjects are also included here. The raw data were obtained using force-sensitive resistors, with the output roughly proportional to the force under the foot. Stride-to-stride measures of footfall contact times were derived from these signals.

Proper citation: Gait Dynamics in Neuro-Degenerative Disease Data Base (RRID:SCR_006979) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://zork.wustl.edu/nida/neurosnp.html

The goal of this project is to aid genetic association studies of addiction by creating a resource of biologically relevant genes, pathways and single nucleotide polymorphisms (SNPs). The primary users of the NeuroSNP resource are investigators conducting genome-wide association studies (GWASs) of addiction-related phenotypes. NeuroSNP will allow investigators to identify biologically relevant genes for addiction based on curated expert knowledge, and assess the coverage of these genes provided by commercial SNP microarrays. If investigators wish to ensure the coverage of certain addiction-related genes is optimal, NeuroSNP provides a mechanism for supplementation. While commercial SNP microarrays offer affordable and comprehensive coverage of the human genome, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is believed to be influenced by complex interactions involving several genes and pathways. NIDA has assembled a number of investigators specializing in fields such as genetics, pharmacogenetics, bioinformatics and neurobiology through a Request for Information. These investigators have pooled their expert knowledge to produce a database of addiction-related genes and SNPs. Commercial SNP microarrays, such as those offered by Affymetrix and Illumina, are then analyzed to determine how well certain addiction-related genes are covered. When the coverage is less than optimal, a SNP prioritization scheme is used to supplement the commercial array with the most biologically informative markers. For example, SNPs in coding regions, promoters, and evolutionary conserved regions are selected first.

Proper citation: NeuroSNP Project (RRID:SCR_007029) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/bipolardatabase/

Database of 141 studies which have investigated brain structure (using MRI and CT scans) in patients with bipolar disorder compared to a control group. Ninety-eight studies and 47 brain structures are included in the meta-analysis. The database and meta-analysis are contained in an Excel spreadsheet file which may be freely downloaded from this website.

Proper citation: Bipolar Disorder Neuroimaging Database (RRID:SCR_007025) Copy   

•   Source: SciCrunch Registry

http://www.genome.ad.jp/ligand/

KEGG LIGAND contains knowledge of chemical substances and reactions that are relevant to life. It is a composite database consisting of COMPOUND, GLYCAN, REACTION, RPAIR, and ENZYME databases, whose entries are identified by C, G, R, RP, and EC numbers, respectively. ENZYME is derived from the IUBMB/IUPAC Enzyme Nomenclature, but the others are internally developed and maintained. The primary database of KEGG LIGAND is a relational database with the KegDraw interface, which is used to generated the secondary (flat file) database for DBGET.

Proper citation: Database of Chemical Compounds and Reactions in Biological Pathways (RRID:SCR_006851) Copy   

•   Source: SciCrunch Registry

http://rapdb.dna.affrc.go.jp/

Database that provides the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. RAP-DB contains clone positions, structures and functions of genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison.

Proper citation: RAP-DB (RRID:SCR_006610) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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://tmbeta-genome.cbrc.jp/TMFunction/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Database of functional residues in alpha-helical and beta-barrel membrane proteins. Each protein is identified with its name and source alongwith the Uniprot code. The protein data bank (PDB) codes are also given for available proteins. Different methods and experimental parameters, for example, affinity, dissociation constant, IC50, activity etc. are given in the database. Further, the database provides the numerical experimental value for each residue (or mutant) in a protein. The experimental data are collected from the literature both by searching the journals as well as with the keyword search at PUBMED. In addition, complete reference is given with journal citation and PMID number. TNFunction is cross-linked with the sequence database, Uniprot, structural database, PDB, and literature database, PubMed. The WWW interface enables users to search data based on various terms with different display options for outputs.

Proper citation: TM Function Database (RRID:SCR_007058) Copy   

•   Source: SciCrunch Registry

http://epgd.biosino.org/SysZNF/

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 2, 2016. SysZNF is an information resource for C2H2 Zinc Finger genes in humans and mice. C2H2 Zinc Finger genes (C2H2-ZNF) constitute the largest class of transcription factors in humans and mouse. C2H2 zinc finger proteins primarily bind to DNA. In most cases, they attach to regions near certain genes and turn the genes on and off as needed. The researches on these genes show light on the evolution of gene regulation systems and development. Therefore, we develop SysZNF (Systematical information resource of Zinc Finger genes) to collect the information related to C2H2 Zinc Finger genes. The aim of SysZNF was to provide a user-friendly interface for rendering the information (DNA, Expression, Protein, Reference and so on) of each C2H2-ZNF (e.g., ZNF10) and to enable a comprehensive analysis of C2H2-ZNF. This project was supported by the Proteome-Center at Rostock University (PCRU) who conceives the concept of the database and Key laboratory of Systems biology at the Shanghai Institute for Biological Sciences (SIBS) who implemented the database. It is maintained jointly by PCRU and SIBS.

Proper citation: SysZNF - C2H2 Zinc Finger genes (RRID:SCR_007056) 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