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https://github.com/rajewsky-lab/spacemake

Software pipeline for processing and analysis of large scale spatial transcriptomics data. Enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports.

Proper citation: Spacemake (RRID:SCR_022207) Copy   

•   Source: SciCrunch Registry
  

http://www.nitrc.org/projects/vutools/

VUIIS (Vanderbilt University Institute of Imaging Science) Image and Data Analysis Core's data processing tools written for MATLAB and, unless stated otherwise, capable of processing 2D/3D images (matrices). These tools are written for ease of use from within MATLAB.

Proper citation: vuTools (RRID:SCR_001704) Copy   

•   Source: SciCrunch Registry
  

http://dunbrack.fccc.edu/pisces/

Software tool as protein sequence culling server. Used for culling sets of protein sequences from Protein Data Bank (PDB) by sequence identity and structural quality criteria. Can provide lists culled from entire PDB or from lists of PDB entries or chains provided by user.

Proper citation: PISCES (RRID:SCR_022181) Copy   

•   Source: SciCrunch Registry
  

http://dissect-trans.sourceforge.net/Home

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software transcriptome-to-genome alignment tool, which can identify and characterize transcriptomic events such as duplications, inversions, rearrangements and fusions.

Proper citation: Dissect (RRID:SCR_000058) Copy   

•   Source: SciCrunch Registry
  

https://www.olympus-lifescience.com/data/olympusmicro/brochures/pdfs/ix71.pdf?rev=EABE

Research inverted system microscope. Olympus IX2 inverted microscope combined with UIS2 optical system. Used for live cell experiments.

Proper citation: Olympus: IX71 Microscope (RRID:SCR_022185) Copy   

•   Source: SciCrunch Registry
  

http://www.mbfbioscience.com/neurolucida

Neurolucida is advanced scientific software for brain mapping, neuron reconstruction, anatomical mapping, and morphometry. Since its debut more than 20 years ago, Neurolucida has continued to evolve and has become the worldwide gold-standard for neuron reconstruction and 3D mapping. Neurolucida has the flexibility to handle data in many formats: using live images from digital or video cameras; stored image sets from confocal microscopes, electron microscopes, and scanning tomographic sources, or through the microscope oculars using the patented LucividTM. Neurolucida controls a motorized XYZ stage for integrated navigation through tissue sections, allowing for sophisticated analysis from many fields-of-view. Neurolucidas Serial Section Manager integrates unlimited sections into a single data file, maintaining each section in aligned 3D space for full quantitative analysis. Neurolucidas neuron tracing capabilities include 3D measurement and reconstruction of branching processes. Neurolucida also features sophisticated tools for mapping delineate and map anatomical regions for detailed morphometric analyses. Neurolucida uses advanced computer-controlled microscopy techniques to obtain accurate results and speed your work. Plug-in modules are available for confocal and MRI analysis, 3D solid modeling, and virtual slide creation. The user-friendly interface gives you rapid results, allowing you to acquire data and capture the full 3D extent of neurons and brain regions. You can reconstruct neurons or create 3D serial reconstructions directly from slides or acquired images, and Neurolucida offers full microscope control for brightfield, fluorescent, and confocal microscopes. Its added compatibility with 64-bit Microsoft Vista enables reconstructions with even larger images, image stacks, and virtual slides. Adding the Solid Modeling Module allows you to rotate and view your reconstructions in real time. Neurolucida is available in two separate versions Standard and Workstation. The Standard version enables control of microscope hardware, whereas the Workstation version is used for offline analysis away from the microscope. Neurolucida provides quantitative analysis with results presented in graphical or spreadsheet format exportable to Microsoft Excel. Overall, features include: - Tracing Neurons - Anatomical Mapping - Image Processing and Analysis Features - Editing - Morphometric Analysis - Hardware Integration - Cell Analysis - Visualization Features Sponsors: Neurolucida is supported by MBF Bioscience.

Proper citation: Neurolucida (RRID:SCR_001775) Copy   

•   Source: SciCrunch Registry
  

https://github.com/atlab/hdf5matlab

Software library for manipulating neural data files generated in Andreas Tolias Lab.

Proper citation: hdf5matlab (RRID:SCR_003595) Copy   

•   Source: SciCrunch Registry
  

https://cpndb.ca/

A curated collection of chaperonin sequence data collected from public databases or generated by a network of collaborators exploiting the cpn60 target in clinical, phylogenetic and microbial ecology studies. The database contains all available sequences for both group I and group II chaperonins. Users can search the database by Chaperonin type, group (I or II), BLAST, or other options, and can also enter and analyze FASTA sequences.

Proper citation: cpnDB: A Chaperonin Database (RRID:SCR_002263) Copy   

•   Source: SciCrunch Registry
  

http://cobre.mrn.org/megsim/

Realistic simulated MEG datasets ranging from basic sensory to oscillatory sets that mimic functional connectivity; as well as basic visual, auditory, and somatosensory empirical sets. The simulated sets were created for the purpose of testing analysis algorithms across the different MEG systems when the truth is known. MEG baseline recordings were obtained from 5 healthy participants, using three MEG systems: VSM/CTF Omega, Elekta Neuromag Vectorview, 4-D Magnes 3600. Simulated signals were embedded within the CTF and Neuromag 306 baseline recordings (4-D to be added). Participant MRIs are available. Averaged simulation files are available as netcdf files. Neuromag 306 averaged simulations are also available in fif format. Also available: single trials of data where the simulated signal is jittered about a mean value, continuous fif files where the simulated signal is marked by a trigger, and simulations with oscillations added to mimic functional connectivity.

Proper citation: MEGSIM (RRID:SCR_002420) Copy   

•   Source: SciCrunch Registry
  

http://www.udel.edu/Biology/Wags/histopage/colorpage/cne/cne.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. An image collection of tissue from the central nervous system and peripheral nervous system.

Proper citation: Nervous Tissue Color Images (RRID:SCR_002416) Copy   

•   Source: SciCrunch Registry
  

http://pharmacology.mc.duke.edu/

Department of Pharmacology and Cancer Biology spans two overlapping and broad disciplines, one exploring how chemical agents impact living cells and one seeking to understand how inappropriate responses to environmental molecules and internal cellular cues can lead to development of Cancer. Occupying Levine Science Research Center, Pharmacology and Cancer Biology department is dedicated to mentoring and training of graduate students and postdoctoral fellows.Innovative undergraduate program also allows students majoring in Biology or Chemistry at Duke to complete area specialization in Pharmacology, as well as offering courses in Pharmacology and Neuropharmacology for undergraduates. Department trains also students working towards Ph.D.s in Molecular Cancer Biology. Moreover, students enter our department through several university-wide multi-disciplinary programs including the Toxicology, Cell and Molecular Biology Program and the University Program in Genetics and Genomics. Our 23 faculty members are remarkably diverse and use all of the tools available to biomedical scientists to address questions critical to fundamental biology and human health. The faculty members share the common goal of exploiting cellular signaling pathways to address a myriad of important scientific questions relevant to cancer, metabolism, nervous system function, drugs of abuse and environmental toxicants.

Proper citation: Duke University, Pharmacology and Cancer Biology (RRID:SCR_003342) 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.patricbrc.org/portal/portal/patric/Home

A Bioinformatics Resource Center bacterial bioinformatics database and analysis resource that provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. The PATRIC project includes three primary collaborators: the University of Chicago, the University of Manchester, and New City Media. The University of Chicago is providing genome annotations and a PATRIC end-user genome annotation service using their Rapid Annotation using Subsystem Technology (RAST) system. The National Centre for Text Mining (NaCTeM) at the University of Manchester is providing literature-based text mining capability and service. New City Media is providing assistance in website interface development. An FTP server and download tool are available.

Proper citation: Pathosystems Resource Integration Center (RRID:SCR_004154) Copy   

•   Source: SciCrunch Registry
  

http://www.imi-getreal.eu/

Consortium that aims to improve the efficiency of the medicine development process by better incorporating estimates of relative effectiveness into drug development and to enrich decision-making by regulatory authorities and health technology assessment (HTA) bodies through: * Bringing together regulators, HTA bodies, academics, companies, patients and other societal stakeholders; * Assessing existing processes, methodologies, and key research issues; * Proposing innovative (and more pragmatic) trial designs and assessing the value of information; * Proposing and testing innovative analytical and predictive modelling approaches; * Assessing operational, ethical, regulatory issues and proposing and testing solutions; * Creating new decision making frameworks, and building open tools to allow for the evaluation of development programs and use in the assessment of the value of new medicines; * Sharing and discussing deliverables with, among others, Pharmaceutical companies, regulatory authorities, HTA / reimbursement agencies, clinicians and patient organizations; * Developing training activities for researchers, decision makers and societal stakeholders in the public and private sector in order to increase knowledge about various aspects of relative effectiveness. The expected impact is that it will contribute to the knowledge base, particularly to inform clinical decision making and improve the efficiency of the R&D process. GETREAL will help to generate a consensus on best practice in the timing, performance and use of real life clinical studies in regulatory and reimbursement decision-making. It will also help to create a strong platform for the communication of results and for future discussions in this important area.

Proper citation: GetReal (RRID:SCR_003862) Copy   

•   Source: SciCrunch Registry
  

http://www.theseed.org/wiki/Home_of_the_SEED

The SEED is a framework to support comparative analysis and annotation of genomes. The cooperative effort focuses on the development of the comparative genomics environment and, more importantly, on the development of curated genomic data. Curation of genomic data (annotation) is done via the curation of subsystems by an expert annotator across many genomes, not on a gene by gene basis. From the curated subsystems we extract a set of freely available protein families (FIGfams). These FIGfams form the core component of our RAST automated annotation technology. Answering numerous requests for automatic Seed-Quality annotations for more or less complete bacterial and archaeal genomes, we have established the free RAST-Server (RAST=Rapid Annotation using Subsytems Technology). Using similar technology, we make the Metagenomics-RAST-Server freely available. We also provide a SEED-Viewer that allows read-only access to the latest curated data sets. We currently have 58 Archaea, 902 Bacteria, 562 Eukaryota, 1254 Plasmids and 1713 Viruses in our database. All tools and datasets that make up the SEED are in the public domain and can be downloaded at ftp://ftp.theseed.org

Proper citation: SEED (RRID:SCR_002129) Copy   

•   Source: SciCrunch Registry
  

http://www.med.unc.edu/bric/ideagroup/free-softwares/intergroup-image-registration

Software package that provides solutions for registering two groups of images, which are the necessary steps for many brain-related applications.

Proper citation: Inter-Group Registration Toolbox (RRID:SCR_002404) Copy   

•   Source: SciCrunch Registry
  

http://purl.bioontology.org/ontology/NIFCELL

Ontology for cell types from NIFSTD

Proper citation: NIF Cell Ontology (RRID:SCR_003977) Copy   

•   Source: SciCrunch Registry
  

http://arrowsmith.psych.uic.edu/arrowsmith_uic/

Portal for documenting the Arrowsmith project and developing text mining tools for scientific, and specifically neuroscience, literature. It also contains a search functions that identifies similar concepts between two articles.

Proper citation: Arrowsmith (RRID:SCR_002523) Copy   

•   Source: SciCrunch Registry
  

http://purl.bioontology.org/ontology/MS

A structured controlled vocabulary for the annotation of mass spectrometry experiments.

Proper citation: Mass Spectrometry Ontology (RRID:SCR_003579) Copy   

•   Source: SciCrunch Registry
  

http://www.predictprotein.org/

Web application for sequence analysis and the prediction of protein structure and function. The user interface intakes protein sequences or alignments and returned multiple sequence alignments, motifs, and nuclear localization signals., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Predictions for Entire Proteomes (RRID:SCR_002803) Copy   

•   Source: SciCrunch Registry