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http://www.kojak-ms.org/

Software tool for identification of cross-linked peptides from mass spectra. Used for analysis of chemically cross-linked protein complexes. Used to analyze both novel and existing data sets.

Proper citation: Kojak (RRID:SCR_021028) Copy   

•   Source: SciCrunch Registry

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

Interactive software of a set of modular programs (each performing a specific task) that provide an integrated computing environment for data analysis and system modeling. Unique capabilities of LYSIS include input-output nonlinear system modeling and the novel methodology of Principal Dynamic Modes (PDMs). LYSIS is currently available in two versions: one for LYSIS 7.1 Windows and one for LYSIS 7.2 Matlab. Early versions are also available for UNIX environments, distributed as source code that can be compiled for each UNIX implementation (e.g., Solaris, HPUX, Linux). Specific features of LYSIS that cannot be found in commercially available packages include the efficient kernel estimation using Laguerre expansions and the use of Principal Dynamic Modes (PDMs). These enable input-output modeling of dynamic nonlinear systems with relatively short data-records (even in the presence of considerable noise). System Requirements * Operating System ** Windows XP/Vista/7 ** Sun/Unix: Solaris 2.x

Proper citation: LYSIS (RRID:SCR_001385) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/cibc-software/scirun.html

A Problem Solving Environment (PSE) for modeling, simulation and visualization of scientific problems. SCIRun now includes the biomedical components formally released as BioPSE, as well as BioMesh3D. BioMesh3D is a free, easy to use program for generating quality meshes for the use in biological simulations. The most recent stable release is version 4.6.

Proper citation: SCIRun (RRID:SCR_002541) Copy   

•   Source: SciCrunch Registry

http://beetlebase.org/

A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.

Proper citation: BeetleBase (RRID:SCR_001955) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/ShapeTools

Software library that is a collection of Java classes that enable Java programmers to model, manipulate and visualize geometric shapes and associated data values. It simplifies the creation of application programs by providing a ready-made set of support routines. * File format readers that implement ShapeIO interface (modeled after Java ImageIO) are automatically used when appropriate. * Storage of additional metadata of arbitrary type (other than shape vertices and interconnections) is enabled by the use of data attributes. * Shapes may contain a set of child shapes allowing for the construction and manipulation of complex hierarchies of shapes. * The various components of a shape are specified as interfaces with specific implementations, making it easy to create specialized implementations of a shape component when different performance characteristics are required.

Proper citation: LONI ShapeTools (RRID:SCR_002697) Copy   

•   Source: SciCrunch Registry

http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases

Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.

Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) Copy   

•   Source: SciCrunch Registry

http://ccb.loni.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.

Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy   

•   Source: SciCrunch Registry

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

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/strap/

Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed. Platform: Windows compatible

Proper citation: STRAP (RRID:SCR_005675) Copy   

•   Source: SciCrunch Registry

http://www.zfatlas.psu.edu/

Atlas containing 2- and 3-dimensional, anatomical reference slides of the lifespan of the zebrafish to support research and education worldwide. Hematoxylin and eosin histological slides, at various points in the lifespan of the zebrafish, have been scanned at 40x resolution and are available through a virtual slide viewer. 3D models of the organs are reconstructed from plastic tissue sections of embryo and larvae. The size of the zebrafish, which allows sections to fall conveniently within the dimensions of the common 1 x 3 glass slide, makes it possible for this anatomical atlas to become as high resolution as for any vertebrate. That resolution, together with the integration of histology and organ anatomy, will create unique opportunities for comparisons with both smaller and larger model systems that each have their own strengths in research and educational value. The atlas team is working to allow the site to function as a scaffold for collaborative research and educational activity across disciplines and model organisms. The Zebrafish Atlas was created to answer a community call for a comprehensive, web-based, anatomical and pathological atlas of the zebrafish, which has become one of the most widely used vertebrate animal models globally. The experimental strengths of zebrafish as a model system have made it useful for a wide range of investigations addressing the missions of the NIH and NSF. The Zebrafish Atlas provides reference slides for virtual microscopic viewing of the zebrafish using an Internet browser. Virtual slide technology allows the user to choose their own field of view and magnification, and to consult labeled histological sections of zebrafish. We are planning to include a complete set of embryos, larvae, juveniles, and adults from approximately 25 different ages. Future work will also include a variety of comparisons (e.g. normal vs. mutant, normal vs. diseased, multiple stages of development, zebrafish with other organisms, and different types of cancer)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Zebrafish Atlas (RRID:SCR_006722) Copy   

•   Source: SciCrunch Registry

http://www.autopack.org/

An open-source general packing algorithm that packs 3D objects onto surfaces, into volumes, and around volumes. It provides a general architecture to allow various packing algorithms to interoperate efficiently in the same model. autoPack can incorporate any packing solution into its modular python program architecture, but is currently optimized to provide a novel solution to the loose packing problem which places objects of discrete size into place (compared to advancing front, popcorn, or other fast tight-packing solutions that allow objects to scale to arbitrary masses.) Most popular 3D software programs now contain robust physics engines based on Bullet that can separate small collections of overlapping objects or allow volumes to be filled by pouring shapes from generators, but these approaches fails for large complex systems and result in either overlapping geometry, crashed software, or non-random gradients. Most packing algorithms are designed to position objects as efficiently as possible, but autoPack allows the user to select from random loose packing to highly organized packing methods����??even to choose both methods at the same time. autoPack positions 3D geometries into, onto, and around volumes with minimal to zero overlap. autoPack mixes several packing approaches and procedural growth algorithms. autoPack can thus place objects with forces and constraints to allow a high degree of control ranging from completely random distributions to highly ordered structures. * zero to minimal overlaps depending on the method used * accuracy vs speed parameters selected by the user * zero edge effects * complete control, from fully random to fully ordered distributions * agent-based interaction, weighting, and collision control

Proper citation: Autopack (RRID:SCR_006830) Copy   

•   Source: SciCrunch Registry

http://www.imagevis3d.org/

A new volume rendering program developed by the NIH/NCRR Center for Integrative Biomedical Computing (CIBC). The main design goals of ImageVis3D are: simplicity, scalability, and interactivity. Simplicity is achieved with a new user interface that gives an unprecedented level of flexibility (as shown in the images). Scalability and interactivity for ImageVis3D mean that both on a notebook computer as well as on a high end graphics workstation, the user can interactively explore terabyte sized data sets. Finally, the open source nature as well as the strict component-by-component design allow developers not only to extend ImageVis3D itself but also reuse parts of it, such as the rendering core. This rendering core, for instance, is planned to replace the volume rendering subsystems in many applications at the SCI Institute and with their collaborators.

Proper citation: ImageVis3D (RRID:SCR_009566) Copy   

•   Source: SciCrunch Registry

http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Dataset of structural MR images of 70 subjects collected during 2008-2010 across a wide range of ages. The dataset also contains resting state fMRI for most subjects. The structural images are T1 weighted, T2 weighted-FLAIR, 25 direction DTI, and the T1 mapping DESPOT [1] sequence. Reconstructed T1 maps for each subject are also available. The aquisition protocol was designed to study structural differences between young and older adults including both shape and intensity changes. Anonymized DICOM image sessions and processed images for each subject are available. The data is licensed under the Creative Commons Attribution License. It may be used freely for commercial, academic, or other use, as long as the original source is properly cited. http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Proper citation: Age Related Atrophy Dataset (RRID:SCR_009528) Copy   

•   Source: SciCrunch Registry

https://doi.org/10.5281/zenodo.592960

Image reconstruction software for MRI. Its library provides common operations on multi-dimensional arrays, Fourier and wavelet transforms, as well as generic implementations of iterative optimization algorithms.

Proper citation: Berkeley Advanced Reconstruction Toolbox (RRID:SCR_016168) Copy   

•   Source: SciCrunch Registry

http://fit.genomics.lbl.gov/cgi-bin/myFrontPage.cgi

Web tool for browsing genome wide fitness experiments for diverse bacteria from Deutschbauer lab, the Arkin lab, and collaborators. Collection of mutant phenotypes for bacterial genes of unknown function.

Proper citation: Fitness Browser (RRID:SCR_018981) Copy   

•   Source: SciCrunch Registry

http://www.cbioportal.org/

A portal that provides visualization, analysis and download of large-scale cancer genomics data sets.

Proper citation: cBioPortal (RRID:SCR_014555) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

https://github.com/fmaguire/Bridger_Assembler

Software package as de novo trascriptome assembler for RNA-Seq data. Framework for de novo transcriptome assembly using RNA-seq data. Can assemble all transcripts from short reads without using reference. Input RNA-Seq reads in fasta or fastq format, and ouput all assembled candidate transcripts in fasta format. Operating system Unix/Linux.

Proper citation: Bridger (RRID:SCR_017039) Copy   

•   Source: SciCrunch Registry

https://modbase.compbio.ucsf.edu/foxs/

Web server for computing theoretical scattering profile of structure and fitting of experimental profile. Computes SAXS profile of given atomistic model and fits it to experimental profile. Used for structural modeling applications with small angle X-ray scattering data.

Proper citation: FoXS (RRID:SCR_017269) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/redcap-to-nda

Software for metadata-driven electronic data capture to export REDCap data dictionaries and data to the NIMH National Data Archive (NDA). Prepares data submissions as csv formatted spreadsheets for data dictionary spreadsheets and for data spreadsheets.

Proper citation: redcap-to-nda (RRID:SCR_016008) Copy   

•   Source: SciCrunch Registry