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http://visit.llnl.gov/

Open source software interactive, scalable, visualization, animation and analysis tool. Used to generate visualizations, animate them through time, manipulate them with variety of operators and mathematical expressions, and save resulting images and animations for presentations.

Proper citation: VisIt (RRID:SCR_024370) Copy   

•   Source: SciCrunch Registry

http://www.hunter.cuny.edu/chemistry/facilities/nmr/home

A service facility with four main spectrometers. The facility consists of four NMR instruments: a JEOL GX-400, a Varian Inova 500, a Bruker Avance 500 equipped with a 13C-1H cryoprobe, and a Bruker Avance III 600 MHz spectrometer equipped with a cryoprobe. These spectrometers are utilized by scientists from Hunter College, as well as from the entire CUNY community. The large variety of available probes allows detection of virtually any MR-active nuclide. Data analysis is performed either at the spectrometer workstation with vendor software or off-line with third party software packages.

Proper citation: Hunter NMR Spectroscopy Facility (RRID:SCR_000883) Copy   

•   Source: SciCrunch Registry

http://wyss.harvard.edu/viewpage/594/

A core facility with access to imaging equipment and analysis software such as wide-field light microscopy, Total Internal Reflection Fluorescence microscopy (TIRF), confocal microscopy, Atomic Force Microscopy (AFM), Transmission Electron Microscopy (TEM), small animal imaging, spectroscopy, and flow cytometry.

Proper citation: Wyss Institute Imaging Core (RRID:SCR_000898) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/ssaha2-0

A program designed for the efficient mapping of sequence reads onto genomic references. The software is capable of reading most sequencing platforms and giving a range of outputs are supported.

Proper citation: Sequence Search and Alignment by Hashing Algorithm (RRID:SCR_000544) Copy   

•   Source: SciCrunch Registry

http://www.nmrfam.wisc.edu/

Provides access and developes NMR technology to advance range of applications and improves the efficiency, rigor and reproducibility of NMR data acquisition and analysis. Houses NMR spectrometers equipped with state-of-the-art probe technology and protocols to support acquisition of high-quality data. Spectrometers range from 500 MHz to 1100 MHz. Service is tailored to the needs of individual users and projects. Provides training and advice on experimental design, best practices for data acquisition, and data analysis. Experienced staff support users with training opportunities including workshops, video tutorials and protocols.

Proper citation: National Magnetic Resonance Facility at Madison (RRID:SCR_001449) Copy   

•   Source: SciCrunch Registry

http://www.adinstruments.com/products/software/modules/neuro_explorer.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 19, 2018; A provider of computer-based data acquisition and analysis systems for life science. Products enable users to record and analyze life science data quickly and efficiently. ADInstruments product range is based on the PowerLab data acquisition system with LabChart software. The PowerLab system (also MacLab) is used in universities, hospitals, research institutes, pharmaceutical companies, contract research organizations and other private industry research sectors.

Proper citation: ADInstruments - Data Acquisition Systems for Life Science (RRID:SCR_001620) Copy   

•   Source: SciCrunch Registry

http://biology.hunter.cuny.edu/index.php?option=com_content&view=article&id=138&Itemid=117

Facility which provides instruments and instrument resources for analyzing DNA, RNA, protein, and radio-labeled substances.

Proper citation: Hunter Genomic Facility (RRID:SCR_001983) Copy   

•   Source: SciCrunch Registry

http://nrnb.org/index.html

Biomedical technology research center that develops new algorithms, visualizations and conceptual frameworks to study biological networks at multiple levels and scales, from protein-protein and genetic interactions to cell-cell communication and vast social networks. They are developing freely available, open-source suite of software technology that broadly enables network-based visualization, analysis, and biomedical discovery for NIH-funded researchers. This software is enabling researchers to assemble large-scale biological data into models of networks and pathways and to use these networks to better understand how biological systems operate under normal conditions and how they fail in disease. The National Resource for Network Biology is organized around the following key components: Technology Research and Development, Driving Biomedical Projects, Outreach, Training and Dissemination of Tools. The NRNB supports several types of training events, including both virtual and live workshops; tutorials sessions for clinicians, biologists and bioinformaticians; presentations and demonstrations at conferences; online tutorials and webcasts; and annual symposium.

Proper citation: National Resource for Network Biology (RRID:SCR_004259) Copy   

•   Source: SciCrunch Registry

http://www.clcbio.com/products/clc-main-workbench/

A suite of software for DNA, RNA and protein sequence data analysis. The software allows for the analysis and visualization of Sanger sequencing data as well as gene expression analysis, molecular cloning, primer design, phylogenetic analyses, and sequence data management.

Proper citation: CLC Main Workbench (RRID:SCR_000354) Copy   

•   Source: SciCrunch Registry

http://www.biochem.mpg.de/en/rd/baumeister/research/ContentCEM/Software_development

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A software platform for low dose electron tomography (ET) for all processing steps: acquisition, alignment, reconstruction, and analysis. Requires: Matlab R2008a and Image Processing Toolbox (V6.1)

Proper citation: Acquisition and Analysis for Electron Tomography (RRID:SCR_000192) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

•   Source: SciCrunch Registry

http://www.preger.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Sample collection of oocytes obtained from various sized antral follicles, and embryos obtained through a variety of different protocols. The PREGER makes it possible to undertake quantitative gene-expression studies in rhesus monkey oocytes and embryos through simple and cost-effective hybridization-based methods.

Proper citation: Primate Embryo Gene Expression Resource (RRID:SCR_002765) Copy   

•   Source: SciCrunch Registry

http://www.fmri.wfubmc.edu/cms/software

Research group based in the Department of Radiology of Wake Forest University School of Medicine devoted to the application of novel image analysis methods to research studies. The ANSIR lab also maintains a fully-automated functional and structural image processing pipeline supporting the image storage and analysis needs of a variety of scientists and imaging studies at Wake Forest. Software packages and toolkits are currently available for download from the ANSIR Laboratory, including: WFU Biological Parametric Mapping Toolbox, WFU_PickAtlas, and Adaptive Staircase Procedure for E-Prime.

Proper citation: Advanced Neuroscience Imaging Research Laboratory Software Packages (RRID:SCR_002926) Copy   

•   Source: SciCrunch Registry

http://www.altanalyze.org/

Software application for microarry, RNA-Seq and metabolomics analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), it will assess alternative exon (known and novel) expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, it provides comprehensive methods for the analysis of other data (RMA summarization, batch-effect removal, QC, statistics, annotation, clustering, network creation, lineage characterization, alternative exon visualization, gene-set enrichement and more). AltAnalyze can be run through an intuitive graphical user interface or command-line and requires no advanced knowledge of bioinformatics programs or scripting. Alternative regulated exons can be subsequently visualized in the context of proteins, domains and microRNA binding sites with the Cytoscape Plugin DomainGraph.

Proper citation: AltAnalyze - Alternative Splicing Analysis Tool (RRID:SCR_002951) Copy   

•   Source: SciCrunch Registry

http://imaging.indyrad.iupui.edu/projects/SPHARM/

A matlab-based 3D shape modeling and analysis toolkit, and is designed to aid statistical shape analysis for identifying morphometric changes in 3D structures of interest related to different conditions. SPHARM-MAT is implemented based on a powerful 3D Fourier surface representation method called SPHARM, which creates parametric surface models using spherical harmonics.

Proper citation: SPHARM-MAT (RRID:SCR_002545) Copy   

•   Source: SciCrunch Registry

http://nipy.org/nipype/

A package for writing fMRI analysis pipelines and interfacing with external analysis packages (SPM, FSL, AFNI). Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Proper citation: Nipype (RRID:SCR_002502) Copy   

•   Source: SciCrunch Registry

http://www.kcl.ac.uk/ioppn/depts/neuroimaging/research/imaginganalysis/Software/PIPR.aspx

Software toolbox designed to provide machine learning methods for pre-processed imaging data allowing for two (or more) class classification in the context of drug development. The Toolbox includes implementations of Gaussian Process Classification, Support Vector Machines, Ordinal Regression and Sparse Multinomial Logistic Regression for fMRI, Structural and ASL imaging data.

Proper citation: Pharmacological Imaging and Pattern Recognition toolbox (RRID:SCR_003874) Copy   

•   Source: SciCrunch Registry

http://www.primervfx.com/#welcome

PrimerParadise is an online PCR primer database for genomics studies. The database contains predesigned PCR primers for amplification of exons, genes and SNPs of almost all sequenced genomes. Primers can be used for genome-wide projects (resequencing, mutation analysis, SNP detection etc). The primers for eukaryotic genomes have been tested with e-PCR to make sure that no alternative products will be generated. Also, all eukaryotic primers have been filtered to exclude primers that bind excessively throughout the genome. Genes are amplified as amplicons. Amplicons are defined as only one genes exons containing maximaly 3000 bp long dna segments. If gene is longer than 3000 bp then it is split into the segments at length 3000 bp. So for example gene at length 5000 bp is split into two segment and for both segments there were designed a separate primerpair. If genes exons length is over 3000 bp then it is split into amplicons as well. Every SNP has one primerpair. In addition of considering repetitive sequences and mono-dinucleotide repeats, we avoid designing primers to genome regions which contain other SNPs. -There are two ways to search for primers: you can use features IDs ( for SNP primers Reference ID, for gene/exon primers different IDs (Ensembl gene IDs, HUGO IDs for human genes, LocusLink IDs, RefSeq IDs, MIM IDs, NCBI gene names, SWISSPROT IDs for bacterial genes, VEGA gene IDs for human and mouse, Sanger S.pombe systematic gene names and common gene names, S.cerevisiae GeneBanks Locus, AccNo, GI IDs and common gene names) -you can use genome regions (chromosome coordinates, chromosome bands if exists) -Currently we provide 3 primers collections: proPCR for prokaryotic organisms genes primers -euPCR for eukaryotic organisms genes/exons primers -snpPCR for eukaryotic organisms SNP primers Sponsors: PrimerStudio is funded by the University of Tartu.

Proper citation: PrimerStudio (RRID:SCR_008232) Copy   

•   Source: SciCrunch Registry

http://locustdb.genomics.org.cn/

The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects. Its transcriptomic data provide invaluable information for molecular entomology study of the insect and pave a way for comparative studies of other medically, agronomically, and ecologically relevant insects. This first transcriptomic database of the locust (LocustDB) has been developed, building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. It currently hosts 45,474 high quality EST sequences from the locust, which were assembled into 12,161 unigenes. This database contains original sequence data, including homologous/orthologous sequences, functional annotations, pathway analysis, and codon usage, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. LocustDB also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. It starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporation of in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

Proper citation: Migratory Locust EST Database (RRID:SCR_008201) Copy   

•   Source: SciCrunch Registry

https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 29,2025. Electroencephalogram (EEG) data recorded from invasive and scalp electrodes. The EEG database contains invasive EEG recordings of 21 patients suffering from medically intractable focal epilepsy. The data were recorded during an invasive pre-surgical epilepsy monitoring at the Epilepsy Center of the University Hospital of Freiburg, Germany. In eleven patients, the epileptic focus was located in neocortical brain structures, in eight patients in the hippocampus, and in two patients in both. In order to obtain a high signal-to-noise ratio, fewer artifacts, and to record directly from focal areas, intracranial grid-, strip-, and depth-electrodes were utilized. The EEG data were acquired using a Neurofile NT digital video EEG system with 128 channels, 256 Hz sampling rate, and a 16 bit analogue-to-digital converter. Notch or band pass filters have not been applied. For each of the patients, there are datasets called ictal and interictal, the former containing files with epileptic seizures and at least 50 min pre-ictal data. the latter containing approximately 24 hours of EEG-recordings without seizure activity. At least 24 h of continuous interictal recordings are available for 13 patients. For the remaining patients interictal invasive EEG data consisting of less than 24 h were joined together, to end up with at least 24 h per patient. An interdisciplinary project between: * Epilepsy Center, University Hospital Freiburg * Bernstein Center for Computational Neuroscience (BCCN), Freiburg * Freiburg Center for Data Analysis and Modeling (FDM).

Proper citation: Electroencephalogram Database: Prediction of Epileptic Seizures (RRID:SCR_008032) Copy   

•   Source: SciCrunch Registry