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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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UNAVCO Resource Report Resource Website 10+ mentions |
UNAVCO (RRID:SCR_006706) | UNAVCO | consortium, data or information resource, organization portal, portal | A non-profit university-governed consortium that facilitates geoscience research and education using geodesy. It rovides access to and submission of Geodetic GPS / GNSS Data, Geodetic Imaging Data, Strain and Seismic Borehole Data, and Meteorological Data. Data access web services/API provides the ability to use a command line interface to query metadata and obtain URLs to data and products. UNAVCO also provides a variety of software, including web applications, and desktop utilities for scientists, instructors, students, and others. Web-based data visualization and mapping tools provide users with the ability to view postprocessed data while web-based geodetic utilities provide ancillary information. Downloadable stand-alone software utilities include applications for configuring instruments, managing data collection, download and transfer, and performing computations on the raw data, e.g., data pre-processing or processing. The UNAVCO Facility in Boulder, Colorado is the primary operational activity of UNAVCO and exists to support university and other research investigators in their use of geophysical sensor technology for Earth sciences research. The Facility performs this task in part by archiving GNSS/GPS data and data products for current and future applications. Other data types that scientists use for Earth deformation studies are also held in the UNAVCO Archive collections. UNAVCO operates a community Archive, which provides long-term secure storage and easy retrieval of GNSS data, strain data, various derived products and related metadata. The Archive primarily stores high-precision geodetic data used for research purposes, collected under National Science Foundation and NASA sponsored projects. UNAVCO provides many learning opportunities including: Short Courses and Workshops, Educational Resources, RESESS Research Student Internships, and Technical Training. | gps, geodesy, motion, rock, ice, water, earth surface, gnss, geoscience, geophysical survey, geophysical observatory, geophysical instrument, earth sciences, global positioning system, data archive, geology, geological mapping |
is listed by: re3data.org is listed by: CINERGI is parent organization of: UNAVCO Geodetic Web Services |
NSF ; NASA |
The community can contribute to this resource | ISNI: 0000 0004 0505 9642, Wikidata: Q7865191, grid.239102.b, nlx_154719 | https://ror.org/02n9tn974 | SCR_006706 | University NAVSTAR Consortium | 2026-09-12 12:56:44 | 32 | |||||
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Marine Geosciences Data System MediaBank Resource Report Resource Website |
Marine Geosciences Data System MediaBank (RRID:SCR_006875) | MediaBank | data or information resource, data repository, image repository, service resource, storage service resource, video resource | A collection of high-quality images and videos for education and outreach from the Integrated Earth Data Applications Facility. Albums include: Ridge2000, MARGINS, GeoMapApp, GeoPRISMS, Antarctic and Southern Ocean, Global Multi-Resolution Topography. To contribute your media to Media Bank, you are asked to supply metadata with each image/video supplied. | image collection, bathymetry, biology, chemistry, geology, geophysics, hydrothermal vent, instrumentation, photomosaic, physical oceanography, satellite imagery |
is listed by: CINERGI has parent organization: Columbia University; New York; USA |
NSF | Creative Commons Attribution-NonCommercial-ShareAlike License, v3 | nlx_154726, r3d100012549 | https://doi.org/10.17616/R3VR4N | SCR_006875 | Media Bank | 2026-09-12 12:56:47 | 0 | |||||
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eXpress Resource Report Resource Website 100+ mentions |
eXpress (RRID:SCR_006873) | eXpress | data analysis software, data processing software, sequence analysis software, software application, software resource |
THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018. From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/. Software for streaming quantification for high-throughput DNA/RNA sequencing. Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them. |
quantification, high-throughput, DNA, RNA, sequencing, target, fragment, analysis |
is listed by: OMICtools is listed by: Debian has parent organization: University of California at Berkeley; Berkeley; USA |
NHGRI R01HG006129; NSF |
DOI:10.1038/nmeth.2251 | THIS RESOURCE IS NO LONGER IN SERVICE | SCR_015990, OMICS_01275 | https://sources.debian.org/src/berkeley-express/ | SCR_006873 | eXpress - Streaming quantification for high-throughput sequencing, Berkeley-express | 2026-09-12 12:56:47 | 495 | ||||
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SVM-fold: Protein Fold Prediction Resource Report Resource Website |
SVM-fold: Protein Fold Prediction (RRID:SCR_006834) | SVM-fold | service resource | This web server makes predictions of family, superfamily and fold level classifications of proteins based on the Structural Classification of Proteins (SCOP) hierarchy using the Support Vector Machine (SVM) learning algorithm. SVM-FOLD detects subtle protein sequence similarities by learning from all available annotated proteins, as well as utilizing potential hits as identified by PSI-BLAST. Predictions of classes of proteins that do not have any known example with a significant pairwise PSI-BLAST E-value can still be found using SVMs. | has parent organization: University of Washington; Seattle; USA | NIGMS GM74257-01; NSF EIA-0312706 |
nlx_17631 | http://svm-fold.c2b2.columbia.edu/ | SCR_006834 | SVM-fold, Support Vector Machine fold | 2026-09-12 12:56:46 | 0 | |||||||
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Summer School in Computational Sensory-Motor Neuroscience Resource Report Resource Website 1+ mentions |
Summer School in Computational Sensory-Motor Neuroscience (RRID:SCR_006894) | CoSMo 2012 | data or information resource, short course, training resource | This unique summer school focuses on computational techniques integrating the multi-disciplinary nature of sensory-motor neuroscience through combined empirical-theoretical teaching modules and a focus on the use of databases of movement data (NSF CRCNS). Major breakthroughs in brain research have been achieved through computational models. The goal of the Summer School in Computational Sensory-Motor Neuroscience is to provide cross-disciplinary training in mathematical modelling techniques relevant to understanding brain function, dysfunction and treatment. In a unique approach bridging experimental research, clinical pathology and computer simulations, students will learn how to translate ideas and empirical findings into mathematical models. Students will gain a profound understanding of the brain''s working principles and diseases using advanced modelling techniques in hands-on simulations of models during tutored sessions by making use of data / model sharing. This summer school aims at propelling promising students into world-class researchers. Dates: August 5-19, 2012 Location: Northwestern University Chicago (Evanston campus), Illinois, USA Deadlines: * April 22, 2012: Application due, including letters of reference (extended!!!) * May 1, 2012: Notification of acceptance * May 20, 2012: Attendance confirmation of applicants and registration payment This summer school is directed at graduate students and post-doctoral fellows from multi-disciplinary backgrounds, including Life Sciences, Psychology, Computer Science, Mathematics and Engineering. We will also accept highly motivated outstanding under-graduate students. There are no formal prerequisites, but basic knowledge in calculus, linear algebra, neuroscience and the Matlab simulation environment is expected. Enrollment will be limited to 40 participants. | computational, sensory-motor, neuroscience, summer school, graduate student, postdoctoral fellow, undergraduate | has parent organization: Northwestern University; Illinois; USA | Canadian Action and Perception Network ; NSF ; NeuroDevNet ; NSERC Collaborative Research and Training Experience ; McGill Centre for Applied Mathematics in Bioscience and Medicine ; Mitacs ; Natural Sciences and Engineering Research Council of Canada |
nlx_144614 | SCR_006894 | 2012 Summer School in Computational Sensory-Motor Neuroscience | 2026-09-12 12:56:47 | 1 | |||||||
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DynGO Resource Report Resource Website 1+ mentions |
DynGO (RRID:SCR_007009) | DynGO | software resource | DynGO is a client-server application that provides several advanced functionalities in addition to the standard browsing capability. DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations (which requires more disk and memory to handle the semantic retrieval). The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Requirements: Java Platform: Windows compatible, Linux compatible, Unix compatible | gene, annotation, browser, ontology or annotation browser |
is listed by: Gene Ontology Tools is related to: Gene Ontology |
NSF IIS-0430743 | PMID:16091147 | Free for academic use | nlx_149118 | http://gauss.dbb.georgetown.edu/liblab | SCR_007009 | DynGO: a tool for visualizing and mining of Gene Ontology and its associations | 2026-09-12 12:56:49 | 6 | ||||
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Jackal Resource Report Resource Website 10+ mentions |
Jackal (RRID:SCR_008665) | software resource | Jackal is a collection of programs designed for the modeling and analysis of protein structures. Its core program is a versatile homology modeling package. It contains twelve individual programs, each with their own function. | software, software repository, modeling, analysis, protein structure |
has parent organization: Columbia University; New York; USA has parent organization: Howard Hughes Medical Institute |
NSF DBI-9904841; NIGMS 5 R37 GM30518 |
Public, Free | nif-0000-33373 | SCR_008665 | 2026-09-12 12:57:07 | 14 | ||||||||
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Protein Subcellular Location Image Database Resource Report Resource Website |
Protein Subcellular Location Image Database (RRID:SCR_008663) | PSLID | data or information resource, data repository, data set, database, image analysis service, service resource, storage service resource |
THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017. Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging. |
protein, structure, subcellular, organelle, image, fluorescence microscope, annotation, classify, rank, cluster, subcellular localization, 3d spatial image, 2d spatial image, micrograph, content-based retrieval, green fluorescent protein |
is listed by: 3DVC is listed by: Biositemaps has parent organization: Carnegie Mellon University; Pennsylvania; USA |
Merck Company Foundation ; NIGMS GM075205; NCI R33 CA83219; NSF MCB-8920118 |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-33313 | SCR_008663 | PSLID - Protein Subcellular Location Image Database, Protein Subcellular Location Image Database | 2026-09-12 12:57:07 | 0 | ||||||
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Eukaryote Genes Resource Report Resource Website 10+ mentions |
Eukaryote Genes (RRID:SCR_008617) | data or information resource, database | Provides summary of gene and genomic information from eukaryotic organism databases. This includes gene symbol and full name, chromosome, genetic and molecular map information, Gene Ontology (Function/Location/Process) and gene homology, product information, links to extended gene information. | eukaryote, eukaryotic gene ontology, eukaryotic genome, bio.tools |
is listed by: bio.tools is listed by: Debian has parent organization: Indiana University; Indiana; USA |
Indiana University Center for Genomics and Bioinformatics ; NSF DBI 0090782; NSF DBI 9982851 |
Free, Freely available | nif-0000-31969, biotools:eugenes, SCR_013197, nif-0000-02818 | https://bio.tools/eugenes | SCR_008617 | euGenes | 2026-09-12 12:57:06 | 17 | ||||||
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NESCent - National Evolutionary Synthesis Center Resource Report Resource Website 1+ mentions |
NESCent - National Evolutionary Synthesis Center (RRID:SCR_005911) | NESCent | institution | The National Evolutionary Synthesis Center (NESCent) is a nonprofit science center dedicated to cross-disciplinary research in evolution. NESCent promotes the synthesis of information, concepts and knowledge to address significant, emerging, or novel questions in evolutionary science and its applications. NESCent achieves this by supporting research and education across disciplinary, institutional, geographic, and demographic boundaries. Synthetic research in evolutionary science takes many forms but includes integrating novel data sets and models to address important problems within a discipline, developing new analytical approaches and tools, and combining methods and perspectives from multiple disciplines to answer and even create new fundamental scientific questions. NESCent facilitates such synthetic research by providing an environment for fertile interactions among scientists. Our Science and Synthesis program sponsors postdoctoral fellows and sabbatical scholars as resident scientists, and two kinds of meetings, working groups and catalysis meetings. Catalysis meetings provide a novel mechanism for bringing together diverse research communities and cultures to identify common interests, while working groups provide an opportunity for scientists to work together intensively on fundamental synthetic questions over a several-year period. These activities are community driven through our application process and evaluated by an external advisory board. Our Informatics program provides state of the art informatics tools to visiting and in-house scientists and aims to take the lead in assembling novel databases and developing new analytical tools for evolutionary biology. Finally it is sponsoring a major initiative to provide a digital data repository for work in evolutionary biology. NESCent''s Education and Outreach group communicates the results of evolutionary biology research to the general public and scientific community, provides outreach to groups who are underrepresented in evolutionary biology and works to improve evolution education. | evolution, evolutionary biology |
has parent organization: Duke University; North Carolina; USA has parent organization: University of North Carolina at Chapel Hill; North Carolina; USA has parent organization: North Carolina State University; North Carolina; USA is parent organization of: FEED is parent organization of: Phenoscape Knowledgebase is parent organization of: TreeBASE is parent organization of: Dryad Digital Repository |
NSF EF-0905606 | Wikidata: Q6972505, ISNI: 0000 0000 9027 3547, nlx_149487, grid.419343.8, Crossref funder ID: 100007514 | https://ror.org/001ykb961 | SCR_005911 | National Evolutionary Synthesis Center | 2026-09-12 12:56:33 | 7 | ||||||
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Dryad Digital Repository Resource Report Resource Website 1000+ mentions |
Dryad Digital Repository (RRID:SCR_005910) | data or information resource, data repository, database, service resource, storage service resource | International, curated, digital repository that makes the data underlying scientific publications discoverable, freely reusable, and citable. Particularly data for which no specialized repository exists. Provides the infrastructure for, and promotes the re-use of, data underlying the scholarly literature. Governed by a nonprofit membership organization. Membership is open to any stakeholder organization, including but not limited to journals, scientific societies, publishers, research institutions, libraries, and funding organizations. Most data are associated with peer-reviewed articles, although data associated with non-peer reviewed publications from reputable academic sources, such as dissertations, are also accepted. Used to validate published findings, explore new analysis methodologies, repurpose data for research questions unanticipated by the original authors, and perform synthetic studies.UC system is member organization of Dryad general subject data repository. | international, digital, repository, curated, data, collection, scientific, medical, publication, dataset, FASEB list |
is used by: NIH Heal Project is recommended by: NIDDK Information Network (dkNET) is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases is listed by: CINERGI is listed by: re3data.org is listed by: Connected Researchers is listed by: DataCite is listed by: FAIRsharing is related to: ImpactStory is related to: Connected Researchers has parent organization: NESCent - National Evolutionary Synthesis Center has parent organization: University of North Carolina at Chapel Hill; North Carolina; USA has parent organization: University of California; California; USA |
European Commission ; Institute for Museum and Library Services ; JISC ; NSF |
DOI:10.25504/FAIRsharing.wkggtx, DOI:10.5061, r3d100000044, DOI:10.15146, DOI:10.17616/R34S33, nlx_149486 | https://doi.org/10.17616/R34S33, https://doi.org/10.5061/, https://doi.org/10.15146, https://dx.doi.org/10.5061/, https://dx.doi.org/10.15146, https://fairsharing.org/10.25504/FAIRsharing.wkggtx, https://api.datacite.org/dois?prefix=10.18736, https://api.datacite.org/dois?prefix=10.6076, , https://doi.org/10.17616/R34S33 | http://www.datadryad.org/ | SCR_005910 | , The Dryad Digital Repository, Dryad Digital Repository, Dryad | 2026-09-12 12:56:33 | 2790 | ||||||
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MNE software Resource Report Resource Website 100+ mentions |
MNE software (RRID:SCR_005972) | MNE | data analysis software, data processing software, data visualization software, software application, software resource, software toolkit | Software suite for processing magnetoencephalography and electroencephalography data. Open source Python software for exploring, visualizing, and analyzing human neurophysiological data including MEG, EEG, sEEG, ECoG . Implements all functionality of MNE Matlab tools in Python and extends capabilities of MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics. | Magnetoencephalography data processing, electroencephaography data processing, data analysis, eeg, meg, linux, mac osx, human neurophysiological data, statistics |
is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is listed by: Debian is related to: MNE-BIDS is related to: MATLAB is related to: NumPy is related to: SciPy is related to: Matplotlib is related to: Mayavi: 3D Scientific Data Visualization and Plotting Software Project is related to: NiBabel |
European Research Council (ERC) StG-263584; NCRR P41 RR014075; NIBIB P41 EB015896; NIBIB R01 EB009048; NIDCD F32DC012456; NSF 0958669; NSF 1042134 |
PMID:24161808 PMID:24431986 |
Free, Available for download, Freely available | nlx_151346 | https://sources.debian.org/src/python3-mne/, http://www.nitrc.org/projects/mne, http://www.nmr.mgh.harvard.edu/martinos/ncrr/sofMNE.html, https://github.com/mne-tools/, https://mne.tools/ | SCR_005972 | Minimum Norm Current Estimates Software, Minimum Norm Current Estimates, MNE tools for MEG and EEG data analysis, MNE-Python | 2026-09-12 12:56:33 | 114 | ||||
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Songbird Brain Transcriptome Database Resource Report Resource Website 1+ mentions |
Songbird Brain Transcriptome Database (RRID:SCR_006182) | Songbird Brain Transcriptome Database | analysis service resource, data analysis service, data or information resource, database, production service resource, service resource | Database containing cDNA clone information of the brains of songbirds. These clones are annotated with behavioral information, as well as links to information of homologous genes of other species. The database includes over 91,000 zebra finch brain cDNAs (2009) sequenced by Duke, ESTIMA, and Rockefeller research groups. The project is a collaborative effort of the Jarvis Laboratory of Duke University, Duke Bioinformatics, and The Genomics group of RIKEN, with Erich D. Jarvis as P.I. and Kazuhiro Wada as Co-P.I. Microarrays with the cDNAs in this database are available at Duke http://mgm.duke.edu/genome/dna_micro/core/spotted.htm and through the NIH Neurosciences Microarray Consortium http://arrayconsortium.tgen.org/np2/public/overview.jsp | brain, songbird, microarray, cdna, cdna clone, clone, behavior, homologous gene, annotation, homologue |
is related to: NIH Neuroscience Microarray Consortium is related to: AmiGO has parent organization: Duke University School of Medicine; North Carolina; USA |
Whitehall Foundation ; Klingenstein Foundation ; Packard Foundation ; Human Fronteir Science Program ; RIKEN ; Japanese Ministry of Education Culture Sports Science and Technology MEXT ; NSF ; Waterman award ; NIDCD R01DC7218 |
PMID:17018643 | Public | nlx_151729 | SCR_006182 | 2026-09-12 12:56:36 | 8 | ||||||
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Galaxy Resource Report Resource Website 5000+ mentions |
Galaxy (RRID:SCR_006281) | Galaxy | analysis service resource, data analysis service, data or information resource, organization portal, portal, production service resource, service resource | Open, web-based platform providing bioinformatics tools and services for data intensive genomic research. Platform may be used as a service or installed locally to perform, reproduce, and share complete analyses. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Community has created Galaxy instances in many different forms and for many different applications including Galaxy servers, cloud services that support Galaxy instances, and virtual machines and containers that can be easily deployed for your own server.The Galaxy team is a part of BX at Penn State, and the Biology and Mathematics and Computer Science departments at Emory University.Training Infrastructure as a Service (TIaaS) is a service offered by some UseGalaxy servers to specifically support training use cases. | bioinformatics, workflow, analysis, data sharing, visualization, cloud, genomics, metagenomics, next-generation sequencing, platform, data set, genaddiction tool |
is used by: Nebula lists: PathwayMatcher is listed by: OMICtools is listed by: 3DVC is listed by: Debian is listed by: SoftCite is related to: ABrowse is related to: TRAMS is related to: Stem Cell Commons is related to: Stem Cell Discovery Engine is related to: CardioVascular Research Grid (CVRG) is related to: rQuant is related to: SnpEff is related to: Binding and Expression Target Analysis is related to: PIPE-CLIP is related to: Stem Cell Discovery Engine is related to: Computational Genomics Analysis Tools is related to: SpliceTrap is related to: SMAGEXP is related to: CandiMeth is related to: ewas-galaxy is related to: CLIP-Explorer is related to: Galactic Circos is related to: Tool recommender system in Galaxy is related to: NanoGalaxy is related to: Cistrome is related to: Training Infrastructure as a Service has parent organization: Pennsylvania State University is parent organization of: kmer-SVM works with: Deeptools |
Huck Institutes for the Life Sciences ; Institute for CyberScience at Pennsylvania State University ; Pennsylvania ; USA ; Johns Hopkins University ; NHGRI HG004909; NHGRI HG005133; NHGRI HG005542; NSF DBI0850103; Pennsylvania Department of Health |
PMID:20738864 PMID:20069535 PMID:16169926 |
Free, Freely available | nlx_151896, OMICS_01141 | https://usegalaxy.org/, https://sources.debian.org/src/galaxy/ | SCR_006281 | The Galaxy Project, Galaxy Project | 2026-09-12 12:56:37 | 6255 | ||||
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Rankprop - Protein Ranking by Network Propagation Resource Report Resource Website |
Rankprop - Protein Ranking by Network Propagation (RRID:SCR_007159) | data access protocol, service resource, software resource, source code, web service | THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on May,18,2020. Ranking algorithm that exploits global network structure of similarity relationships among proteins in database by performing diffusion operation on protein similarity network with weighted edges. Source code and web server for searching non-redundant protein database. Web server ranks proteins found in NRDB40 (from PairsDB) against query sequence of amino acids using Rankprop algorithm. | Ranking algorithm, network structure, protein database, similarity relationship, protein similarity network, weighted adges, non redundat protein database, protein database search | has parent organization: University of Washington; Seattle; USA | NIGMS GM74257; NSF DBI-0243257; NSF EIA-0312706 |
PMID:16723003 | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_50351 | http://rankprop.gs.washington.edu/info.php | SCR_007159 | Rankprop | 2026-09-12 12:56:50 | 0 | |||||
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Computational Neuroanatomy Group Resource Report Resource Website |
Computational Neuroanatomy Group (RRID:SCR_007150) | CNG | data or information resource, portal, software resource, topical portal | Multidisciplinary research team devoted to the study of basic neuroscience with a specific interest in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, they seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column). Achievements by the CNG include the development of software for the quantitative analysis of dendritic morphology, the implementation of computational models to simulate neuronal structure, and the synthesis of anatomically accurate, large scale neuronal assemblies in virtual reality. Based on biologically plausible rules and biophysical determinants, they have designed stochastic models that can generate realistic virtual neurons. Quantitative morphological analysis indicates that virtual neurons are statistically compatible with the real data that the model parameters are measured from. Virtual neurons can be generated within an appropriate anatomical context if a system level description of the surrounding tissue is included in the model. In order to simulate anatomically realistic neural networks, axons must be grown as well as dendrites. They have developed a navigation strategy for virtual axons in a voxel substrate. | dendritic morphology, neuronal morphology, neuronal electrophysiology, mammalian brain, neural network, cell, model, morphology, network connectivity, basal ganglia, modeling software, hippocampus, hermissenda learning, caulescence, tree structure, neuron, virtual neural network, morphological class of neuron, virtual neuron, virtual brain, ca3 pyramidal cell, arborvitae, ca1 pyramidal cell, polymorphic cell, dg granule cell, axonal navigation, synaptic connectivity, neuroplasticity, neuroanatomy, neuroinformatics, computation, network model, neural circuit, cellular event, expression, ca3, ca1 pyramidal neuron, digital morphological reconstruction, digital reconstruction, dendrite, axon, neuronal tree, signaling pathway |
has parent organization: George Mason University: Krasnow Institute for Advanced Study is parent organization of: L-Measure is parent organization of: Hippocampus 3D Model |
NINDS ; NIMH ; NSF ; Human Brain Project |
nif-0000-00503 | http://krasnow.gmu.edu/cn3/index3.html | SCR_007150 | Computational Neuroanatomy Group at the Krasnow Institute for Advanced Study | 2026-09-12 12:56:50 | 0 | ||||||
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Organelle DB Resource Report Resource Website 1+ mentions |
Organelle DB (RRID:SCR_007837) | Organelle DB | d spatial image, data or information resource, data repository, database, image collection, service resource, storage service resource | Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light. | gene, fly, vertebrate, human, mouse, plant, worm, yeast, protein, k-12, organelle, protein localization, function, subcellular structure, protein complex, sequence, annotation, micrograph, visualization, data analysis service |
is related to: Gene Ontology has parent organization: University of Michigan; Ann Arbor; USA |
American Cancer Society Research Scholar Grant RSG-06-179-01-MBC; March of Dimes Basil O'Connor Starter Scholar Research award 5-FY05-1224; NSF DBI-0543017 |
PMID:17130152 PMID:15608270 |
Free, Acknowledgement requested | nif-0000-03226 | SCR_007837 | Organelle DB: A Database of Organelles and Protein Complexes | 2026-09-12 12:56:57 | 7 | |||||
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Fungal Genetics Stock Center Resource Report Resource Website 100+ mentions |
Fungal Genetics Stock Center (RRID:SCR_008143) | biomaterial supply resource, material resource, organism supplier | The Fungal Genetics Stock Center is a resource available to the Fungal Genetics research community and to educational and research organizations in general. While some fungi can cause disease in humans, most people have innate immunity against fungi. Some people with diseases of the immune system are at increased risk of infection by fungi. Drugs have been developed in the last 5 years that help with this. Fungal Genetics is the study of genes and genetic traits in fungi. In the past this has been important in the elucidation of what a gene is, what the genetic material is, how genes relate to enzymes, how enzymes relate to traits and how important traits change or evolve. In the present, Fungal Genetics is important to understanding how fungi are pathogens of plants and animals, how fungi can be used in industry for the production of enzymes, chemicals, food, and drugs. Fungi are also essential to processing bio-mass in the attempt to use ethanol as a fuel source. The FGSC is funded largely by a grant from the National Science Foundation (Award Number 0235887) of the United States of America. Sponsors: Supported by a grant from the National Science Foundation. | drug, fungal genetic, fungus, animal, basic research knowledge base, database, disease, plant, FASEB list | has parent organization: University of Missouri; Missouri; USA | NSF G12967 | nif-0000-20977 | SCR_008143 | FGSC | 2026-09-12 12:57:00 | 198 | ||||||||
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Adaptive Poisson-Boltzmann Solver Resource Report Resource Website 50+ mentions |
Adaptive Poisson-Boltzmann Solver (RRID:SCR_008387) | APBS | software resource | APBS is a software package for modeling biomolecular solvation through solution of the Poisson-Boltzmann equation (PBE), one of the most popular continuum models for describing electrostatic interactions between molecular solutes in salty, aqueous media. APBS was designed to efficiently evaluate electrostatic properties for such simulations for a wide range of length scales to enable the investigation of molecules with tens to millions of atoms. It also provides implicit solvent models of nonpolar solvation which accurately account for both repulsive and attractive solute-solvent interactions. APBS uses FEtk (the Finite Element ToolKit) to solve the Poisson-Boltzmann equation numerically. FEtk is a portable collection of finite element modeling class libraries written in an object-oriented version of C. It is designed to solve general coupled systems of nonlinear partial differential equations using adaptive finite element methods, inexact Newton methods, and algebraic multilevel methods. | software package, modeling, biomolecular, electrostatic, molecular, dynamics, binding energy, equilibrium, protein, ligand, solvation, kinetics, simulation, finite element |
is listed by: 3DVC is related to: Finite Element Toolkit has parent organization: Washington University in St. Louis; Missouri; USA |
IBM/American Chemical Society ; NPACI/San Diego Supercomputer Center ; W. M. Keck Foundation ; National Biomedical Computation Resource ; NSF ; NIH |
nif-0000-30035 | SCR_008387 | 2026-09-12 12:57:03 | 51 | ||||||||
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Divvy Resource Report Resource Website 1+ mentions |
Divvy (RRID:SCR_006336) | Divvy | data analysis software, data processing software, data visualization software, software application, software resource, source code | Software application for performing unsupervised machine learning and visualization with a focus on the clustering (separating data into groups) and dimensionality reduction (finding low dimensional structure in high dimensional data) subfields of machine learning. For visualization we provide support for both the whole dataset (e.g. a scatter plot) and points (e.g. transforming a particular point into an image). * Endlessly extensible. Every clusterer, reducer, point visualizer and dataset visualizer in Divvy is a plugin. We''ve provided a few big ones (K-means, PCA, scatter plot, &c.) and we''re hoping the community will use our plugin protocol to build many more. Each plugin defines its own UI, so your algorithm can look and behave the way that you want it to without top-down constraints. * Have lots of cores? Divvy is both task and data parallel. No longer will you be waiting for one algorithm to complete before you start another. Start as many as you want and keep using the UI. Only started one? With data parallelism we''ll still push your new MacBook Pro to 800% CPU utilization. * Part of your workflow: Export your clusterings and reductions to .csv and your visualizations to .png. Use your Matlab or R data with our Matlab/R to Divvy export tools available at http://github.com/jmlewis/divvy. | data analysis, cluster, machine learning, visual analytics, data visualization, plugin, k-means, principal component analysis, scatter plot | has parent organization: University of California at San Diego; California; USA | NSF 0963071 | MIT License | nlx_152038 | SCR_006336 | 2026-09-12 12:56:38 | 1 |
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