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http://human.brain-map.org/static/brainexplorer

Multi modal atlas of human brain that integrates anatomic and genomic information, coupled with suite of visualization and mining tools to create open public resource for brain researchers and other scientists. Data include magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), histology and gene expression data derived from both microarray and in situ hybridization (ISH) approaches. Brain Explorer 2 is desktop software application for viewing human brain anatomy and gene expression data in 3D.

Proper citation: Allen Human Brain Atlas (RRID:SCR_007416) Copy   

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http://www.idars.org/

IDARS is an international scientific organization that promotes and fosters the research and collaboration of scientists around the world in the area of substances of abuse and addiction. Our focus is to foster research in molecular, cellular and systems biology and includes neuropharmacological, neurobehavioral, neurochemical and neuroanatomical themes. The purposes of IDARS are scientific, educational and charitable. We strive to promote excellence in: advancing the understanding of drug abuse, substance abuse and addictions, including the part they play in behaviors of humans and in animal models bringing together scientists of varying backgrounds and disciplines within the field of drug abuse research integrating drug abuse research directed at all levels of biological organization and its translation to improvement in clinical prevention and treatment efforts promoting education in the addiction sciences informing the general public on the results and implications of current research in the addiction sciences promoting other activities that will contribute to the development of addiction sciences IDARS is a 501c3 nonprofit organization.

Proper citation: International Drug Abuse Research Society (RRID:SCR_007411) Copy   

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http://nsr.bioeng.washington.edu/

Database of physiological, pharmacological, and pathological information on humans and other organisms and integration through computational modeling. Models include everything from diagrammatic schema, suggesting relationships among elements composing a system, to fully quantitative, computational models describing the behavior of physiological systems and an organism''s response to environmental change. Each mathematical model is an internally self-consistent summary of available information, and thereby defines a working hypothesis about how a system operates. Predictions from such models are subject to test, with new results leading to new models.BR /> A Tool developed for the NSR Physiome project is JSim, an open source, free software. JSim is a Java-based simulation system for building quantitative numeric models and analyzing them with respect to experimental reference data. JSim''s primary focus is in physiology and biomedicine, however its computational engine is quite general and applicable to a wide range of scientific domains. JSim models may intermix ODEs, PDEs, implicit equations, integrals, summations, discrete events and procedural code as appropriate. JSim''s model compiler can automatically insert conversion factors for compatible physical units as well as detect and reject unit unbalanced equations. JSim also imports the SBML and CellML model archival formats. All JSim models are open source. Goals of the Physiome Project: - To develop and database observations of physiological phenomenon and interpret these in terms of mechanism (a fundamentally reductionist goal). - To integrate experimental information into quantitative descriptions of the functioning of humans and other organisms (modern integrative biology glued together via modeling). - To disseminate experimental data and integrative models for teaching and research. - To foster collaboration amongst investigators worldwide, to speed up the discovery of how biological systems work. - To determine the most effective targets (molecules or systems) for therapy, either pharmaceutic or genomic. - To provide information for the design of tissue-engineered, biocompatible implants.

Proper citation: NSR Physiome Project (RRID:SCR_007379) Copy   

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http://dblab.duhs.duke.edu/modules/dblabs_topcat/index.php

TOPPCAT stands for T-One weighted Perfusion imaging Parameter CAlculation Toolkit. TOPPCAT creates quantitative maps of Ktrans (volume transfer constant between blood plasma and the extravascular extracellular space) and fPV (fractional plasma volume) from dynamic T1-weighted perfusion images. At the current time, analysis using the method of Patlak plots (most appropriate for first pass dynamic contrast-enhanced MR imaging) is supported. As a preliminary step for the parameter calculation, TOPPCAT also creates maps of T1 and S0 (equilibrium magnetization) from multi-flip angle T1-weighted SPGR (or FLASH) sequences.Daniel P. Barboriak, James R. MacFall, Anthony O. Padua,Gerald E. York, Benjamin L. Viglianti, and Mark W. Dewhirst. Standardized software for calculation of Ktrans and vp from dynamic T1-weighted MR images. Presented at the International Society for Magnetic Resonance in Medicine Workshop on MR in Drug Development: From Discovery to Clinical Therapeutic Trials, McLean VA, April 2004.

Proper citation: T-One weighted Perfusion imaging Parameter CAlculation Toolkit (RRID:SCR_007376) Copy   

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http://www.neurolens.org/NeuroLens/

An integrated environment for the analysis and visualization of functional neuroimages. It is intended to provide extremely fast and flexible image processing, via an intuitive user interface that encourages experimentation with analysis parameters and detailed inspection of both raw image data and processing results. All processing operations in NeuroLens are built around a Plugin architecture, making it easy to extend its functionality. NeuroLens runs on Apple computers based on the G4, G5, or Intel chipsets and running MacOSX 10.4 (Tiger) or later. It is available free for academic and non-profit research use. * Operating System: MacOS * Programming Language: Objective C * Supported Data Format: AFNI BRIK, ANALYZE, COR, DICOM, MGH/MGZ, MINC, Other Format

Proper citation: NeuroLens (RRID:SCR_007372) Copy   

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http://www.mediacy.com/imageproplus

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18,2023. Software package to capture, process, measure, analyze and share images and data.

Proper citation: Image Pro Plus (RRID:SCR_007369) Copy   

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http://zmf.umm.uni-heidelberg.de/apps/zmf/argonaute/single.php

A database is a of mammalian miRNAs and their known or predicted regulatory targets. It provides information on origin of miRNAs, tissue specificity of their expressions and their known or proposed functions, their potential target genes as well as data on miRNA families based on their co-expression and proteins known to be involved in miRNA processing. This database also contains three other navigation tools that can be used to find information relating to miRNA: 1.) Gene Annotations is an information retrieval system for miRNA target genes. It provides comprehensive information from sequence databases and allows to simultaneously search PubMed with all synonyms of a given gene. 2.) miRNA Motif Finder - Argonaute predicts miRNA motifs binding to the gene sequence of the user. The miRNA mature sequences are taken from Agronaute 2 database. miRNA Motif Finder - Custom predicts miRNA motifs binding to the gene sequence, both the gene sequence and miRNA mature sequences provided by the user. 3.) miRNA Statistics provides statistics for the mature miRNA sequences from Argonaute 2 as well as for the miRNA sequences uploaded by the user. It provides statitics on the individual nucleotide as well as pattern of nucleotides apperaing in the sequence.

Proper citation: ARGONAUTE 2 - A database on mammalian microRNAs and their function in gene and pathway regulation (RRID:SCR_007553) Copy   

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http://ekhidna.biocenter.helsinki.fi/sqgraph/pairsdb

This is a web interface for ADDA, an automatic algorithm for domain decomposition and clustering of all protein domain families. We use alignments derived from an all-on-all sequence comparison to define domains within protein sequences based on a global maximum likelihood model. ADDA is downloadable. There are three ways in which you can retrieve a protein sequence and its domains from ADDA. Sequences can be located using sequence identifiers and/or accession numbers, using a identical fragment lookup, or by running BLAST against all sequences in ADDA. ADDA is a protein sequence clustering algorithm. It takes a set of sequences and returns domain families. ADDA has two steps corresponding to the two aspects of the protein sequence clustering domain. First, ADDA splits protein sequences into domains. The idea behind ADDA is in principle the application of Occam''s razor; the goal is to describe the diversity of protein sequences with a minimal set of protein domains. The algorithm behind ADDA approximates this minimal set. In practice ADDA works by looking at where BLAST alignments are located on the sequence and splits the sequences, so that as few as possible alignments are cut by domain boundaries and that as many alignments as possible stretch over complete domains. Secondly, ADDA takes all the domains and then arranges them in a minimum spanning tree, where the similarity between two domains is determined by their relative overlap given a BLAST alignment. Each link in the tree is then checked by a pairwise profile-profile comparison and links below a threshold are removed. The remaining connected components are then taken to represent protein domain families.

Proper citation: ADDA - Automatic Domain Decomposition Algorithm (RRID:SCR_007546) Copy   

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http://www.nmpdr.org/FIG/wiki/view.cgi

The National Microbial Pathogen Data Resource provides curated annotations in an environment for comparative analysis of genomes and biological subsystems, with an emphasis on the food-borne pathogens Campylobacter, Listeria, Staphylococcus, Streptococcus, and Vibrio; as well as the STD pathogens Chlamydiaceae, Haemophilus, Mycoplasma, Neisseria, Treponema, and Ureaplasma. This edition of the NMPDR includes 47 archaeal, 725 bacterial, and 29 eukaryal genomes with 3,257,100 genetic features, of which 1,338,895 are in FIGfams curated using 616 active subsystems. ''''''Notice to NMPDR Users'''''' - The NMPDR BRC contract ended in December 2009. At that time we ceased maintenance of the NMPDR web resource and data. Bacterial data from NMPDR has been transferred to PATRIC (http://www.patricbrc.org), a new consolidated BRC for all NIAID category A-C priority pathogenic bacteria. NMPDR was a collaboration among researchers from the Computation Institute of the University of Chicago, the Fellowship for Interpretation of Genomes (FIG), Argonne National Laboratory, and the National Center for Supercomputing Applications (NCSA) at the University of Illinois.

Proper citation: NMPDR (RRID:SCR_007821) Copy   

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http://www.gene-regulation.com/pub/programs.html

In an effort to strongly support the collaborative nature of scientific research, BIOBASE offers access to their tools. Programs that are available through this portal are: * AliBaba 2.1: AliBaba2 is a program for predicting binding sites of transcription factor binding sites in an unknown DNA sequence. Therefore it uses the binding sites collected in TRANSFAC. AliBaba2 is currently the most specific tool for predicting sites. * Boxshade 3.3.1: Pretty Printing and Shading of Multiple-Alignment files. * ClustalW 1.8: ClustalW Multiple Sequence Alignment Program. * Dialign2.0: Multiple Sequence Alignment Program. * F-Match 1.0: F-MATCH is a program for identifying statistically overrepresented Transcription Factor Binding Sites (TFBS) in a set of sequences compared against a control set, assuming a binomial distribution of TFBS frequency. The program reads MATCH output files for the query and control sets. F-Match uses a library of mononucleotide weight matrices from TRANSFAC 6.0 * Match 1.0 Public: Match is designed for searching potential binding sites for transcription factors (TF binding sites) nucleotide sequences. MatchTM uses a library of mononucleotide weight matrices from TRANSFAC 6.0 * molwSearch 1.0: Search for transcription factors with a certain molecular weight. * P-Match 1.0: P-Match is a new tool for identifying transcription factor binding sites (TF binding sites) in DNA sequences. It combines pattern matching and weight matrix approaches thus providing higher accuracy of recognition than each of the methods alone. P-Match uses a library of mononucleotide weight matrices from TRANSFAC 6.0 along with the site alignments associated with these matrices. * Patch 1.0: Search for potential transcription factor binding sites in your own sequences with the pattern search program using TRANSFAC 6.0 public sites. * m2transfac 1.0: m2transfac is a PWM-PWM alignment interface for the TRANSFAC(R) database. For given user motifs, m2transfac reports all non-overlapping pairwise alignments to a TRANSFAC(R) matrix which satisfy a specified threshold. * MatrixCatch 2.7: The MatrixCatch tool is designed for searching potential composite elements (CEs) for transcription factors (TFs) in any DNA sequence, which may be of interest. MatrixCatch uses a library of CE matrix models, which were compiled on a basis of experimentally identified CEs collected in TRANSCOMPEL database and mononucleotide weight matrices for single TF-binding sites collected in TRANSFAC 6.0 public database. * Composite Module Analyst (CMA) 1.0: CMA reads output of Match program and applies a genetic algorithm in order to define promoter models based on the composition of transcription factor binding sites and their pairs. * PolyA Scan 0.000707: Scanning a Sequence for potential Polyadenylation Sites. * ReadSeq 2.0: ReadSeq reads and writes nucleic/protein sequences in various formats. * SignalScan: Analysis of DNA Sequences for known Eukaryotic Signals * SbBlast 1.0: Search Tool for Sequence Search in the S/MARt Binder Database. SbBlast makes use of the BLAST Sequence Similarity Search Tool - Version 2.0.13 (May-26-2000). * SnpFind 0.3: SNPFIND is a tool for searches in the Database of Single Nucleotide Polymorphisms. The search algorithm used for the database search is the BLAST algorithm. * TfBlast 0.1: Search Tool for Sequence Search in the TRANSFAC Factor Table. SbBlast makes use of the BLAST Sequence Similarity Search Tool - Version 2.0.13 (May-26-2000).

Proper citation: Gene Regulation Programs (RRID:SCR_007787) Copy   

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http://enhancer.lbl.gov/

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy   

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http://www.buzsakilab.com/

Lab interested in understanding how neuronal circuitries of the brain support its cognitive capacities. Its goal is to provide rational, mechanistic explanations of cognitive functions at a descriptive level. In the lab''s view, the most promising area of cognitive faculties for scientific inquiry is memory, since it is a well-circumscribed term, can be studied in animals and substantial knowledge has accumulated on the molecular mechanisms of synaptic plasticity. Available software: * NeuroScope: NeuroScope can display local field potentials (EEG), neuronal spikes, behavioral events, as well as the position of the animal in the environment. It also features limited editing capabilities. * Klusters: Klusters is a powerful and easy-to-use cluster cutting application designed to help neurophysiologists sort action potentials from multiple neurons on groups of electrodes (e.g., tetrodes or multisite silicon probes). * KlustaKwik: KlustaKwik is a program for automatic cluster analysis, specifically designed to run fast on large data sets. * MATLAB m-files: A selection of MATLAB files developed in the lab., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Buzsaki Lab (RRID:SCR_008020) Copy   

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http://www.hpid.org

Database that provides human protein interaction information and integrated interaction and also finds proteins from databases that can potentially react with proteins submitted by users. The human protein interaction information was pre-computed by a statistical method from existing structural and experimental data, while the integrated human protein interactions are derived from BIND, DIP and HPRD. A score composed of three parts is assigned to the predicted interaction data, and those interactions with high scores were found reliable. HPID allows the user to use the protein IDs in EMBL, Ensembl, MIM, RefSeq, HPRD and NCBI to search protein interactions of interest. A set of web-based software tools has also been developed so that users can visualize and analyze protein interaction networks.

Proper citation: HPID - Human Protein Interaction database (RRID:SCR_007724) Copy   

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https://www.har.mrc.ac.uk

UK’s national facility for mouse genetics and use of mouse models for preclinical study of human disease.Offers services to researchers around the world. Services include free archiving of mouse lines to protect them for future use, distribution of mouse lines from the Archive, breeding and phenotyping of genetically altered mice, and genome engineering services to generate new mouse models.Offers archiving and distribution of mouse lines to safeguard germplasm collected from unique strains and make it readily available to the scientific community.

Proper citation: Medical Research Council Harwell: An International Centre for Mouse Genetics (RRID:SCR_008013) Copy   

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http://www-bird.jst.go.jp/index_e.html

BIRD''s mission is to aid the progress of bioinformatics and promote creation of new biology, which has computational, deductive, predictive, and theoretical features. (most of this site is in Japanese) To carry out its responsibilities, BIRD: * Promotes appropriate development of bioinformatics research and development, such as what kinds of databases and analysis software should be developed and what kind of computer facilities are needed for that development. * Maintains the computer environment and network and functions as a funding agency to further promotion plans. * Develops basic databases: genome sequence database, protein 3D structure database, gene expression profile database, molecular interaction database, etc. * Conducts and coordinates integration, enhancement, and standardization of the basic databases. * Develops computing tools for analyzing various kinds of biological and experimental data, data mining from databases, computer simulation of living systems and so on. * Develops ontologies necessary for data and knowledge description of databases storing biological functions and integration of the basic databases. * Conducts and coordinates research and development of innovative and creative technologies and theories which move toward understanding life as an information system, especially approaches by collaboration of computer scientists and experimental scientists. * Provides computer facilities for developing databases and software and making them publicly available. * Sets up training courses for teaching utilization of databases and tools for novices in bioinformatics and sponsors scientific meetings. * Provides community space with high performance computing facilities where innovative ideas are cultivated by free discussion and "trial and error" with the computer in order to promote development of young scientists who will create new biological discoveries based on bioinfomatics and become leaders in the field.

Proper citation: BIRD - Bio Info R and D (RRID:SCR_008010) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

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http://www.louisville.edu/medschool/pharmacology/

The Department of Pharmacology & Toxicology in the School of Medicine at the University of Louisville focuses upon the interaction of drugs and other chemicals with biological systems ranging from individual molecules, to cells, to tissues, to organ systems or individuals. The two disciplines are a continuum incorporating the therapeutic to toxic effect of every drug and chemical. Our departmental programs incorporate pharmacology and/or toxicology, and graduates are well trained to accept employment in either or both disciplines. Our research and curriculum incorporate molecular biology, genetics, neuroscience, biochemistry, physiology and other biomedical sciences, providing maximum flexibility for our graduates.

Proper citation: University of Louisville, Department of Pharmacology (RRID:SCR_007510) Copy   

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http://cagt.bu.edu/page/PRECISE_about

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of interactions between amino acid residues of enzyme and its ligands. Provides summary of interactions between amino acid residues of enzyme and its various ligands including substrate and transition state analogues, cofactors, inhibitors, and products., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRECISE (RRID:SCR_007874) Copy   

•   Source: SciCrunch Registry

http://bio2rdf.blogspot.com/

This is a blog about post genomic knowledge. The website''s goal is to make public datasets from the bioinformatics community available in RDF format via standard SPARQL endpoints.

Proper citation: Bio2RDF atlas of post genomic knowledge (RRID:SCR_007991) Copy   

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http://vega.sanger.ac.uk/

Central repository for high quality frequently updated manual annotation of vertebrate finished genome sequence. Human, mouse and zebrafish are in the process of being completely annotated, whereas for other species the annotation is only of specific genomic regions of particular biological interest. The majority of the annotation is from the HAVANA group at the Welcome Trust Sanger Institute. Users can BLAST, search for specific text, export, and download data. Genomes and details of the projects for each species are available through the homepages for human mouse and zebrafish. The website is built upon code from the EnsEMBL (http://www.ensembl.org) project. Some Ensembl features are not available in Vega. From the users point of view perhaps the most significant of these is MartView. However due to their inclusion in Ensembl, Vega human and mouse data can be queried using Ensembl MartView. Vega contains annotation of the human MHC region in eight haplotypes, and the LRC region in three haplotypes. Vega also contains annotation on the Insulin Dependent Diabetes (IDD) regions on non-reference assemblies for mouse.

Proper citation: VEGA (RRID:SCR_007907) Copy   

•   Source: SciCrunch Registry