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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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On page 13 showing 241 ~ 260 out of 455 results
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https://elegansvariation.org/

Supplier and researcher of wild C. elegans strains. CeNDR supplies organisms, analyzes whole-genome sequences, and facilitates genetic mappings to aid researchers in gene discovery.

Proper citation: Caenorhabditis elegans Natural Diversity Resource (CeNDR) (RRID:SCR_014958) Copy   


  • RRID:SCR_001443

    This resource has 1+ mentions.

http://www.macchess.cornell.edu/

MacCHESS Synchrotron Source for Structural Biology advances structural characterization of proteins and biomolecules critical for understanding key biological processes and properties through leveraging both established and emerging X-ray synchrotron technologies. Used to collect data that comprises all or part of research programs.

Proper citation: MacCHESS (RRID:SCR_001443) Copy   


  • RRID:SCR_014631

    This resource has 100+ mentions.

http://fatcat.burnham.org/

Web server for flexible protein structure comparison. Structure alignment is formulated as the aligned fragment pairs chaining process allowing at most t twists, and the flexible structure alignment is transformed into a rigid structure alignment when t is forced to be 0., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FATCAT (RRID:SCR_014631) Copy   


  • RRID:SCR_016368

    This resource has 1000+ mentions.

http://bowtie-bio.sourceforge.net/bowtie2/index.shtml

Ultrafast and memory efficient tool for aligning sequencing reads to long reference sequences. Supports gapped, local, and paired end alignment modes. More suited to finding longer, gapped alignments in comparison with original Bowtie method.

Proper citation: Bowtie 2 (RRID:SCR_016368) Copy   


  • RRID:SCR_014828

    This resource has 1+ mentions.

http://cellorganizer.org

Image analysis software that learns modular models of things such as cell shape, nuclear shape, vesicular organelle distribution and microtubule distribution directly from 2D or 3D images and can produce specific instances of cell geometries without the need to create them by hand or to segment microscope images. These geometries can be combined with biochemical models to perform spatially realistic cell simulations if used in conjunction with MCell.

Proper citation: CellOrganizer (RRID:SCR_014828) Copy   


  • RRID:SCR_015715

    This resource has 1+ mentions.

http://www.ccg.unam.mx/tfmodeller

Web application that scans a library of protein-DNA complexes and builds comparative models of proteins bound to DNA. Its results include complex coordinates, schematic interface diagrams, interface alignments and DNA motifs.

Proper citation: TFmodeller (RRID:SCR_015715) Copy   


  • RRID:SCR_015682

    This resource has 1+ mentions.

http://amp.pharm.mssm.edu/gen3va/

Software tool for aggregation and analysis of gene expression signatures from related studies.Used to aggregate and analyze gene expression signatures extracted from GEO by crowd using GEO2Enrichr. Used to view aggregated report that provides global, interactive views, including enrichment analyses, for collections of signatures from multiple studies sharing biological theme.

Proper citation: GEN3VA (RRID:SCR_015682) Copy   


http://amp.pharm.mssm.edu/CREEDS/

Software resource that allows students or the general public find variants that may be significantly associated with some disease. CREEDS also visualizes and analyzes gene expression signatures.

Proper citation: CRowd Extracted Expression of Differential Signatures (RRID:SCR_015680) Copy   


  • RRID:SCR_015724

    This resource has 10+ mentions.

http://neuroexpresso.org/

Database of mouse brain cell type-specific gene expression datasets. NeuroExpresso is able to demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression.

Proper citation: NeuroExpresso (RRID:SCR_015724) Copy   


  • RRID:SCR_015701

    This resource has 100+ mentions.

https://www.rosettacommons.org/home

Molecular modeling software package for 3D structure prediction and high resolution design of proteins, nucleic acids, and non natural polymers. Used in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes.

Proper citation: Rosetta (RRID:SCR_015701) Copy   


  • RRID:SCR_004097

    This resource has 1000+ mentions.

https://www.cgl.ucsf.edu/chimera/

Software tool for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials.

Proper citation: UCSF Chimera (RRID:SCR_004097) Copy   


http://www.tcdb.org/

Curated, relational database containing sequence, classification, structural, functional and evolutionary information about transport systems from variety of living organisms based on IUBMB-approved transporter classification (TC) system. Descriptions, TC numbers, and examples of over 600 families of transport proteins are provided. TC system is analogous to Enzyme Commission (EC) system for classification of enzymes, except that it incorporates both functional and phylogenetic information. TCDB users may submit their own sequenced proteins and descriptions for inclusion into database. The software tools used are all freely available for download. These programs are used for analysis of Protein and DNA sequences. Programs require UNIX server to run.

Proper citation: Transporter Classification Database (RRID:SCR_004490) Copy   


  • RRID:SCR_004869

    This resource has 5000+ mentions.

http://www.pantherdb.org/

System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PANTHER (RRID:SCR_004869) Copy   


  • RRID:SCR_004911

    This resource has 1+ mentions.

http://u-compare.org/

An integrated text mining / natural language processing system based on the Unstructured Information Management Architecture (UIMA) Framework. It allows interoperability of text mining tools and allows the creation of text mining workflows, comparison and visualization of tools. U-Compare can be launched straight from the web or downloaded. As the name implies comparison of components and workflows is a central feature of the system. U-Compare allows sets of components to be run in parallel on the same inputs and then automatically generates statistics for all possible combinations of these components. Once a workflow has been created in U-Compare it can be exported and shared with other users or used with other UIMA compatible tools and so in addition to comparison, U-Compare also functions as a general purpose workflow creation tool. It contains a repository of 50+ biomedical text mining components. These components are included in the U-Compare single-click-to-launch package, ready to use by just drag-and-drop. You can also use this repository independent from the U-Compare system. Link with Taverna It has a link with Taverna for scientific workflows, http://bioinformatics.oxfordjournals.org/content/26/19/2486.abstract, where you can use U-Compare and its workflow from within the Taverna workflow. There are two ways, the U-Compare Taverna plugin and the U-Compare command line mode as a Taverna activity. We have recently integrated it with Peter Murray-Rust''''s OSCAR for Chemistry (see http://www.nactem.ac.uk/cheta/) Web Demo: http://www.nactem.ac.uk/software/cheta/

Proper citation: U-Compare (RRID:SCR_004911) Copy   


  • RRID:SCR_007980

    This resource has 1+ mentions.

http://people.biochem.umass.edu/sfournier/fournierlab/snornadb/

A database of S. cerevisiae H/ACA and C/D box snoRNAs, useful for research on rRNA nucleotide modifications in the ribosome, especially those created by small nucleolar RNA:protein complexes (snoRNPs). The interactive service enables a user to visualize the positions of pseudouridines, 2'-O-methylations, and base methylations in three-dimensional space in the ribosome and also in linear and secondary structure formats of ribosomal RNA. The tools provide additional perspective on where the modifications occur relative to functional regions within the rRNA and relative to other nearby modifications. This package of tools is presented as a major enhancement of an existing but significantly upgraded yeast snoRNA database. The other key features of the enhanced database include details of the base pairing of snoRNAs with target RNAs, genomic organization of the yeast snoRNA genes, and information on corresponding snoRNAs and modifications in other model organisms.

Proper citation: Yeast snoRNA Database (RRID:SCR_007980) Copy   


https://simtk.org/home/lapack

This project is the SimTK Core implementation of the extremely reliable, high speed linear algebra package LAPACK and the underlying BLAS library on which LAPACK is built. It uses ATLAS to generate hand tuned BLAS kernels for a variety of hardware platforms, including multiprocessors, using a variety of operating systems including Windows, Mac, and Red Hat Linux. These platforms are pre-built and make the binaries available as a single shared library which can be conveniently used by any program. This means that users who are not experts in high performance scientific computation can nonetheless use the fastest linear algebra methods available for their machines.

Proper citation: LAPACK linear algebra library (RRID:SCR_008661) Copy   


http://pslid.org/

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.

Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy   


http://trans.nih.gov/bmap/index.htm

The Brain Molecular Anatomy Project is a trans-NIH project aimed at understanding gene expression and function in the nervous system. BMAP has two major scientific goals: # Gene discovery: to catalog of all the genes expressed in the nervous system, under both normal and abnormal conditions. # Gene expression analysis: to monitor gene expression patterns in the nervous system as a function of cell type, anatomical location, developmental stage, and physiological state, and thus gain insight into gene function. In pursuit of these goals, BMAP has launched several initiatives to provide resources and funding opportunities for the scientific community. These include several Requests for Applications and Requests for Proposals, descriptions of which can be found in this Web site. BMAP is also in the process of establishing physical and electronic resources for the community, including repositories of cDNA clones for nervous system genes, and databases of gene expression information for the nervous system. Most of the BMAP initiatives so far have focused on the mouse as a model species because of the ease of experimental and genetic manipulation of this organism, and because many models of human disease are available in the mouse. However, research in humans, other mammalian species, non-mammalian vertebrates, and invertebrates is also being funded through BMAP. For the convenience of interested investigators, we have established this Web site as a central information resource, focusing on major NIH-sponsored funding opportunities, initiatives, genomic resources available to the research community, courses and scientific meetings related to BMAP initiatives, and selected reports and publications. When appropriate, we will also post initiatives not directly sponsored by BMAP, but which are deemed relevant to its goals. Posting decisions are made by the Trans-NIH BMAP Committee

Proper citation: BMAP - Brain Molecular Anatomy Project (RRID:SCR_008852) Copy   


  • RRID:SCR_006695

    This resource has 5000+ mentions.

http://www.ebi.ac.uk/interpro

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

Proper citation: InterPro (RRID:SCR_006695) Copy   


http://www.webgestalt.org/

Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.

Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy   



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