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http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

•   Source: SciCrunch Registry

http://protege.stanford.edu

Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development.

Proper citation: Protege (RRID:SCR_003299) Copy   

•   Source: SciCrunch Registry

http://sbgrid.org/

Computing resources structural biologists need to discover the shapes of the molecules of life, it provides access to web-enabled structural biology applications, data sharing facilities, biological data sets, and other resources valuable to the computational structural biology community. Consortium includes X-ray crystallography, NMR and electron microscopy laboratories worldwide.SBGrid Service Center is located at Harvard Medical School.SBGrid's NIH-compliant Service Center supports SBGrid operations and provides members with access to Software Maintenance, Computing Access, and Training. Consortium benefits include: * remote management of your customized collection of structural biology applications on Linux and Mac workstations; * access to commercial applications exclusively licensed to members of the Consortium, such as NMRPipe, Schrodinger Suite (limited tokens) and the Incentive version of Pymol; remote management of supporting scientific applications (e.g., bioinformatics, computational chemistry and utilities); * access to SBGrid seminars and events; and * advice about hardware configurations, operating system installations and high performance computing. Membership is restricted to academic/non-profit research laboratories that use X-ray crystallography, 2D crystallography, NMR, EM, tomography and other experimental structural biology technologies in their research. Most new members are fully integrated with SBGrid within 2 weeks of the initial application.

Proper citation: Structural Biology Grid (RRID:SCR_003511) Copy   

•   Source: SciCrunch Registry

http://mimi.ncibi.org/MimiWeb/main-page.jsp

MiMi Web gives you an easy to use interface to a rich NCIBI data repository for conducting your systems biology analyses. This repository includes the MiMI database, PubMed resources updated nightly, and text mined from biomedical research literature. The MiMI database comprehensively includes protein interaction information that has been integrated and merged from diverse protein interaction databases and other biological sources. With MiMI, you get one point of entry for querying, exploring, and analyzing all these data. MiMI provides access to the knowledge and data merged and integrated from numerous protein interactions databases and augments this information from many other biological sources. MiMI merges data from these sources with deep integration into its single database with one point of entry for querying, exploring, and analyzing all these data. MiMI allows you to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI displays results of your queries in easy-to-browse interfaces and provides you with workspaces to explore and analyze the results. Among these workspaces is an interactive network of protein-protein interactions displayed in Cytoscape and accessed through MiMI via a MiMI Cytoscape plug-in. MiMI gives you access to more information than you can get from any one protein interaction source such as: * Vetted data on genes, attributes, interactions, literature citations, compounds, and annotated text extracts through natural language processing (NLP) * Linkouts to integrated NCIBI tools to: analyze overrepresented MeSH terms for genes of interest, read additional NLP-mined text passages, and explore interactive graphics of networks of interactions * Linkouts to PubMed and NCIBI's MiSearch interface to PubMed for better relevance rankings * Querying by keywords, genes, lists or interactions * Provenance tracking * Quick views of missing information across databases. Data Sources include: BIND, BioGRID, CCSB at Harvard, cPath, DIP, GO (Gene Ontology), HPRD, IntAct, InterPro, IPI, KEGG, Max Delbreuck Center, MiBLAST, NCBI Gene, Organelle DB, OrthoMCL DB, PFam, ProtoNet, PubMed, PubMed NLP Mining, Reactome, MINT, and Finley Lab. The data integration service is supplied under the conditions of the original data sources and the specific terms of use for MiMI. Access to this website is provided free of charge. The MiMI data is queryable through a web services api. The MiMI data is available in PSI-MITAB Format. These files represent a subset of the data available in MiMI. Only UniProt and RefSeq identifiers are included for each interactor, pathways and metabolomics data is not included, and provenance is not included for each interaction. If you need access to the full MiMI dataset please send an email to mimi-help (at) umich.edu.

Proper citation: Michigan Molecular Interactions (RRID:SCR_003521) Copy   

•   Source: SciCrunch Registry

http://www.isi.edu/integration/karma/

An information integration software tool that enables users to integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can publish the integrated data as RDF or store it in a database.

Proper citation: Karma (RRID:SCR_003732) Copy   

•   Source: SciCrunch Registry

http://yogo.msu.montana.edu/

A set of software tools created to rapidly build scientific data-management applications. These applications will enhance the process of data annotation, analysis, and web publication. The system provides a set of easy-to-use software tools for data sharing by the scientific community. It enables researchers to build their own custom-designed data management systems. The problem of scientific data management rests on several challenges. These include flexible data storage, a way to share the stored data, tools to curate the data, and history of the data to show provenance. The Yogo Framework gives you the ability to build scientific data management applications that address all of these challenges. The Yogo software is being developed as part of the NeuroSys project. All tools created as part of the Yogo Data Management Framework are open source and released under an OSI approved license.

Proper citation: Yogo Data Management System (RRID:SCR_004239) Copy   

•   Source: SciCrunch Registry

http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

•   Source: SciCrunch Registry

http://www.cs.gsu.edu/~serghei/?q=drut

Software for Discovery and Reconstruction of Unannotated Transcripts in Partially Annotated Genomes from High-Throughput RNA-Seq Data.

Proper citation: DRUT (RRID:SCR_004351) Copy   

•   Source: SciCrunch Registry

http://phenex.phenoscape.org/

Software application for annotating character matrix files with ontology terms. Character states can be annotated using Entity-Quality syntax, where entity, quality, and possibly related entities are drawn from requisite ontologies. In addition, taxa (the rows of a character matrix) can be annotated with identifiers from taxonomy ontology. Phenex saves ontology annotations alongside original free text character matrix data using new NeXML format standard for evolutionary data.

Proper citation: Phenex (RRID:SCR_021748) Copy   

•   Source: SciCrunch Registry

https://github.com/mourisl/Rcorrector

Software tool as kmer based error correction method for RNAseq data. Can also be applied to other types of sequencing data where read coverage is nonuniform, such as single cell sequencing. Used for error correction for Illumina RNAseq reads.

Proper citation: Rcorrector (RRID:SCR_022011) Copy   

•   Source: SciCrunch Registry

https://github.com/Benson-Genomics-Lab/TRF

Software tool to locate and display tandem repeats in DNA sequences. Program to analyze DNA sequences.

Proper citation: Tandem Repeats Finder (RRID:SCR_022193) Copy   

•   Source: SciCrunch Registry

https://github.com/marbl/MashMap

Software tool as fast approximate aligner for long DNA sequences. Used for computing local alignment boundaries between long DNA sequences.

Proper citation: MashMap (RRID:SCR_022194) Copy   

•   Source: SciCrunch Registry

http://hymao.org

A structured controlled vocabulary of the anatomy of the Hymenoptera (bees, wasps, sawflies and ants)

Proper citation: Hymenoptera Anatomy Ontology (RRID:SCR_003340) Copy   

•   Source: SciCrunch Registry

http://www.geosamples.org/

Sample Catalog and Registry for the International Geo Sample Number. SESAR catalogs and preserves sample metadata profiles, and provides access to the sample catalog via the Global Sample Search.

Proper citation: System for Earth Sample Registration (RRID:SCR_002222) Copy   

•   Source: SciCrunch Registry

http://nsidc.org/agdc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. Archives and distributes Antarctic glaciological and cryospheric system data collected by the U.S. Antarctic Program. The Data Catalog contains data sets collected by individual investigators and products assembled from many different PI data sets, published literature, and other sources. The catalog provides useful compilations of important geophysical parameters, such as accumulation rate or ice velocity. The NSF OPP Guidelines and Award Conditions for Scientific Data state that PIs should submit data collected as a result of their OPP grant to a designated data center as soon as possible, but no later than two years after the data are collected.

Proper citation: Antarctic Glaciological Data Center (RRID:SCR_002219) Copy   

•   Source: SciCrunch Registry

http://www.morphbank.net/

An NSF supported image repository of over 374,000 high-resolution photographs of approximately 4,000 species for research and education, used largely but not exclusively in the area of biodiversity research. Images can be annotated by users and browsed by specimen, view, taxonomy, location, collection, or annotation.

Proper citation: MorphBank (RRID:SCR_003147) Copy   

•   Source: SciCrunch Registry

http://www.plantcyc.org/

Broad network of plant metabolic pathway databases with two types of databases: a reference database called PlantCyc and single species/taxon databases, such as AraCyc. Additional external metabolic pathway databases are affiliated with the PMN. These databases remain under the autonomous control of the PMN collaborators who provide them. PMN draws upon the work of many individuals with expertise in annotating genomes, generating metabolic pathway databases, curating biochemical information from the literature, and forming extensive network of collaborations with biological databases and biochemistry researchers. In addition to providing biochemical reaction diagrams, organism-specific metabolic maps, detailed descriptions of enzymes and pathways, and links to other resources, the PMN website houses tutorials to help guide teachers and students as they learn more about the valuable bioinformatic data and analysis tools that are crucial elements of modern biological research. Please help expand the content of the PMN databases, including AraCyc and PlantCyc! Any and all new data submissions related to plant biochemical pathways are welcomed. You can also correct an existing pathway. The PMN has several tools available for analyzing the data presented in PlantCyc and the other species-specific metabolic databases. You may browse the pathway ontology, compound ontology, and enzyme commission ontology. *PlantCyc: a comprehensive plant biochemical pathway database, containing curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism. It provides access to manually curated or reviewed information about shared and unique metabolic pathways present in over 350 plant species. * AraCyc: provides access to manually curated or reviewed information about metabolic pathways for the model plant Arabidopsis thaliana. The pathways may be unique to Arabidopsis or shared with other organisms. Data from gene expression, proteomic, and metabolomic experiments in Arabidopsis can be overlaid on a metabolic pathway map using the OMICS Viewer. * PoplarCyc: provides access to manually curated or reviewed information about metabolic pathways for the model tree Populus trichocarpa and a few other related Populus species and hybrids. The pathways may be unique to poplar or shared with other organisms. Data from gene expression, proteomic, and metabolomic experiments in poplar can be overlaid on a metabolic pathway map using the OMICS Viewer.

Proper citation: Plant Metabolic Network (RRID:SCR_003778) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://www.vistrails.org/

Open-source scientific workflow and provenance management system that provides support for simulations, data exploration and visualization. It was designed to manage these rapidly-evolving workflows. VisTrails has a comprehensive provenance infrastructure that maintains detailed history information about the steps followed and data derived in the course of an exploratory task: VisTrails maintains provenance of data products, of the workflows that derive these products and their executions. This information is persisted as XML files or in a relational database, and it allows users to navigate workflow versions in an intuitive way, to undo changes but not lose any results, to visually compare different workflows and their results, and to examine the actions that led to a result. It also enables a series operations and user interfaces that simplify workflow design and use, including the ability to create and refine workflows by analogy and to query workflows by example. VisTrails supports the creation and execution of workflows. It allows the combination of loosely-coupled resources, specialized libraries, grid and Web services. The released version comes with support for several packages including, VTK, Image Magick, Web Services, and pylab. You can also download packages contributed by users, as well as create your own packages/modules. Workflows can be run interactively, through the VisTrails GUI, or in batch using a VisTrails server. VisTrails is written in Python and it uses the multi-platform Qt library for its user interface. It runs on Mac, Linux and Windows. Provenance-rich results derived by VisTrails can be included in LaTeX, Wiki, Microsoft Word and PowerPoint documents.

Proper citation: VisTrails (RRID:SCR_006261) Copy   

•   Source: SciCrunch Registry

http://www.ibioseminars.org/

iBioSeminars offers: * Free, on-demand lectures: Many universities/colleges have limited access to high profile leaders in biological research. Our goal is to add 15-20 seminars per year, of similar quality to outstanding lectures that are currently in this library. Access, through web streaming or download, is completely free-of-charge. * Targeting a broad audience: iBioSeminars start with an extended introduction, making them accessible to non-specialists and students, and then progress to cover current research. Senior scientists and students can view and enjoy these lectures. * Education: iBioSeminars are being used by undergraduate and graduate teachers to augment their classroom material. We have now added an education component to this web site (including lecture notes, questions/answers and short video clips for teaching). * International communication: iBioSeminars have viewers in 115 countries and they are being internally promoted in several countries as an educational tool and scientific resource. * Goodwill: Lecturers generously donate their time to prepare these lectures. The project, largely funded by HHMI, is a grass roots efforts with time invested by several individuals at UCSF, HHMI and ASCB.

Proper citation: iBioSeminars (RRID:SCR_005848) Copy   

•   Source: SciCrunch Registry