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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://bioinformatics.ai.sri.com/ptools/

A software application which supplies software tools to develop and maintain pathway/genome databases (PGDBs). These include the development of organism-specific databases, metabolic reconstruction and metabolic-flux modeling, scientific visualization and web publishing of organism-specific databases, analysis of gene-expression and metabolomics datasets, comparative genome and pathway analyses, and analysis of biological networks.

Proper citation: Pathway Tools (RRID:SCR_013786) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.topsan.org/

Collect, share, and distribute information about protein three-dimensional structures. It serves as a portal for the scientific community to learn about protein structures solved by SG centers, and also to contribute their expertise in annotating protein function. The premise of the TOPSAN project is that, no matter how much any individual knows about a particular protein, there are other members of the scientific community who know more about certain aspects of the same protein, and that the collective analyses from experts will be far more informative than any local group, let alone individual, could contribute. They believe that, if the members of the biological community are given the opportunity, authorship incentives, and an easy way to contribute their knowledge to the structure annotation, they would do so. Therefore, borrowing elements from successful, distributed, collaborative projects, such as Wikipedia (the free encyclopedia anyone can edit) and from other open source software development projects, TOPSAN will be a broad, collaborative effort to annotate protein structures, initially, those determined at the JCSG. They believe that the annotation of proteins solved by structural genomics consortia offers a unique opportunity to challenge the extant paradigm of how biological data is collected and distributed, and to connect structural genomics and structural biology to the entire biological research community. TOPSAN is designed to be scalable, modular and extensible. Furthermore, it is intended to be immediately useful in a simplistic way and will accommodate incremental improvements to functionality as usage becomes more sophisticated. Their annotation pages will offer the end user a combination of automatically generated as well as expert-curated annotations of protein structures. They will use available technology to increase the speed and granularity of the exchange of scientific ideas, and use incentive mechanisms that will encourage collaborative participation.

Proper citation: TOPSAN (RRID:SCR_005758) Copy   

•   Source: SciCrunch Registry

http://publications.nigms.nih.gov/multimedia/searchresults.asp?search=All

As part of its multimedia outreach, the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health -- the United States'' medical research agency -- offers audio and video podcasts and other multimedia resources that explore the exciting world of basic biomedical research.

Proper citation: NIGMS Multimedia (RRID:SCR_005712) Copy   

•   Source: SciCrunch Registry

http://publications.nigms.nih.gov/chemhealth/

Visit ChemHealthWeb for research highlights, chemist profiles, games and videos and other Web extras. The NIGMS Chemistry of Health booklet describes basic chemistry and biochemistry research that spurs a better understanding of human health.

Proper citation: ChemHealthWeb (RRID:SCR_005851) Copy   

•   Source: SciCrunch Registry

http://polbase.neb.com/

Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.

Proper citation: Polbase (RRID:SCR_006107) Copy   

•   Source: SciCrunch Registry

https://phenome.jax.org/centers/QTLA

Raw data from various QTL (quantitative trait loci) studies using rodent inbred line crosses. Data are available in the .csv format used by R/qtl and pseudomarker programs. In some cases analysis scripts and/or results are posted to accompany the data. These data are provided as a courtesy to the genetic mapping community and may be used for purposes of developing or testing new analysis methods or software and for meta-analysis of quantitative traits. The authors of the datasets retain individual ownership of the data. As a courtesy to the authors, please alert them in advance of any publications that result from reanalysis of these data or obtain permission prior to redistribution of data or results. In all data sets and files, the marker locations have been translated to Cox build 37 coordinates unless otherwise stated. Please consider contributing your data to the QTL Archive.

Proper citation: QTL Archive (RRID:SCR_006213) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/webservices/psicquic/registry/registry?action=STATUS

Web service with well defined methods to enable programmatic access to molecular interactions. Standard for computational access to molecular interaction data resources.

Proper citation: PSICQUIC Registry (RRID:SCR_006389) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry