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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 21 showing 401 ~ 420 out of 455 results
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  • 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_028224

https://github.com/zfyuan/EpiProfile2.0_Family

Software tool for processing Epi-Proteomics mass spectrometry data. Discriminates isobaric histone peptides using distinguishing fragment ions in their tandem mass spectra and extracts the chromatographic area under the curve using previous knowledge about peptide retention time. Nanoflow liquid chromatography coupled with high resolution tandem mass spectrometry-based quantification tool for histone peptides, which can also be adapted to analyze nonhistone protein samples. EpiProfile 2.0 is extended version of v1.0 for enhanced quantification of histone peptides based on LC-MS/MS analysis.

Proper citation: EpiProfile (RRID:SCR_028224) 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_009628

    This resource has 1+ mentions.

http://www.sci.utah.edu/cibc/software/map3d.html

A scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models such as high resolution EEG, MEG, and ECG.

Proper citation: map3d (RRID:SCR_009628) Copy   


  • RRID:SCR_010278

    This resource has 1000+ mentions.

http://www.datamonkey.org/

Web-based suite of phylogenetic analysis tools for use in evolutionary biology. Web application for comparative analysis of sequence alignments using statistical models. Used for analyzing evolutionary signatures in sequence data. Datamonkey 2.0 provides curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application.

Proper citation: Datamonkey (RRID:SCR_010278) Copy   


  • RRID:SCR_010845

    This resource has 10000+ mentions.

http://targetscan.org/

Web tool to predict biological targets of miRNAs by searching for presence of conserved 8mer, 7mer and 6mer sites that match seed region of each miRNA. Nonconserved sites are also predicted and sites with mismatches in seed region that are compensated by conserved 3' pairing. Used to search for predicted microRNA targets in mammals.

Proper citation: TargetScan (RRID:SCR_010845) Copy   


  • RRID:SCR_012813

    This resource has 10000+ mentions.

http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   


  • RRID:SCR_000667

    This resource has 1000+ mentions.

http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   


http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   


  • RRID:SCR_006997

    This resource has 1000+ mentions.

http://www.microrna.org

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: microRNA.org (RRID:SCR_006997) Copy   


  • RRID:SCR_006949

    This resource has 10+ mentions.

http://physionet.org/physiobank/

Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.

Proper citation: Physiobank (RRID:SCR_006949) Copy   


http://rankprop.gs.washington.edu/

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.

Proper citation: Rankprop - Protein Ranking by Network Propagation (RRID:SCR_007159) Copy   


  • RRID:SCR_007291

    This resource has 1+ mentions.

http://www.birncommunity.org/collaborators/function-birn/

The FBIRN Federated Informatics Research Environment (FIRE) includes tools and methods for multi-site functional neuroimaging. This includes resources for data collection, storage, sharing and management, tracking, and analysis of large fMRI datasets. fBIRN is a national initiative to advance biomedical research through data sharing and online collaboration. BIRN provides data-sharing infrastructure, software tools, strategies and advisory services - all from a single source.

Proper citation: Function BIRN (RRID:SCR_007291) 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://www.unh.edu/research/welcome-university-instrumentation-center

University wide core facility offers NMR,SEM including FIB, EBS, EBSD, Tensile Stage,Confocal,X-Ray Photoelectron Spectroscopy,X-Ray Microscope aka Micro CT, Expert analysis of research and industrial samples,Training in scientific instrument operation and data analysis, Maintenance, repair, and calibration of instruments,Specialty instrument engineering design and application services,Facilitation of access to scientific instruments throughout the university.

Proper citation: University of New Hampshire University Instrumentation Center Core Facility (RRID:SCR_021101) Copy   


http://www.cgl.ucsf.edu/

Biomedical technology resource center that develops software and web-based resources for the visualization and analysis of molecular structure, and related data, at scales ranging from the atomic to the supramolecular. They create tools for handling and integrating diverse types of biomolecular data, including atomic-resolution coordinates, density maps, sequences, annotations, and networks. Their primary efforts are in the visualization and analysis of structures of molecules and molecular assemblies, enzyme sequence-structure-function relationships, and network representations of protein similarity, binding interactions, and biological pathways. They provide technologies to enable identifying the molecular bases of disease and phenotypic variation, annotating proteins of unknown function, identifying targets for drug development, designing drugs, and engineering proteins with new functions. RBVI distributes software tools, including the popular UCSF Chimera visualization and analysis package, develops and hosts the Structure-Function Linkage Database, and provides access to state-of-the-art computational resources in support of research projects in these areas.

Proper citation: Resource for Biocomputing Visualization and Informatics (RRID:SCR_001374) Copy   


http://bowtie-bio.sourceforge.net/recount/

RNA-seq gene count datasets built using the raw data from 18 different studies. The raw sequencing data (.fastq files) were processed with Myrna to obtain tables of counts for each gene. For ease of statistical analysis, they combined each count table with sample phenotype data to form an R object of class ExpressionSet. The count tables, ExpressionSets, and phenotype tables are ready to use and freely available. By taking care of several preprocessing steps and combining many datasets into one easily-accessible website, we make finding and analyzing RNA-seq data considerably more straightforward.

Proper citation: ReCount - A multi-experiment resource of analysis-ready RNA-seq gene count datasets (RRID:SCR_001774) Copy   



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