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https://www.hpcwire.com/2005/10/28/swami_the_next_generation_biology_workbench/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. The Next Generation Biology Workbench is a free resource for research and education in Bioinformatics, Genomics, Proteomics, and Phylogenetics. The NGBW is a re-engineering of the Biology Workbench which was designed by Shankar Subramaniam and his group to provide an integrated environment where tools, user data, and public data resources can be easily accessed. The NGBW is designed to be an organic tool that evolves with the needs of the Biomedical research and education communities. The Next Generation Biology Workbench (NGBW) is now available for public use, in its production release.

Proper citation: Swami: The Next Generation Biology Workbench (RRID:SCR_007217) Copy   

•   Source: SciCrunch Registry

http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml

Software programs for segregation and linkage analysis, using a variety of Markov chain Monte Carlo (MCMC) methods. Includes MCMC methods for multilocus gene identity by descent (including homozygosity mapping) and Monte Carlo Lod scores. Also, other programs for EM analysis of quantitative traits.

Proper citation: MORGAN (RRID:SCR_006906) Copy   

•   Source: SciCrunch Registry

https://github.com/BioDepot/nbdocker

Software tool as Jupyter Notebook extension for Docker. Each Docker container encapsulates its individual computing environment to allow different programming languages and computing environments to be included in one single notebook, provides user to document code as well as computing environment.

Proper citation: nbdocker (RRID:SCR_017159) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/omicsGAN

Software generative adversarial network to integrate two omics data and their interaction network to generate one synthetic data corresponding to each omics profile that can result in better phenotype prediction. Used to capture information from interaction network as well as two omics datasets and fuse them to generate synthetic data with better predictive signals.

Proper citation: OmicsGAN (RRID:SCR_022976) Copy   

•   Source: SciCrunch Registry

https://autodocksuite.scripps.edu/adt/

Software graphical user interface to help to set up which bonds will treated as rotatable in the ligand and to analyze dockings. Used for automated docking with selective receptor flexibility. Designed to predict how small molecules, such as substrates or drug candidates, bind to receptor of known 3D structure.

Proper citation: AutoDockTools (RRID:SCR_026401) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/cibc/software/131-shapeworks.html

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on September 2, 2022. Software that is an open-source distribution of a new method for constructing compact statistical point-based models of ensembles of similar shapes that does not rely on any specific surface parameterization. The method requires very little preprocessing or parameter tuning, and is applicable to a wide range of shape analysis problems, including nonmanifold surfaces and objects of arbitrary topology. The proposed correspondence point optimization uses an entropy-based minimization that balances the simplicity of the model (compactness) with the accuracy of the surface representations. The ShapeWorks software includes tools for preprocessing data, computing point-based shape models, and visualizing the results.

Proper citation: ShapeWorks (RRID:SCR_000424) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/NIGMS/

YouTube videos provided by the National Institute of General Medical Sciences (NIGMS).

Proper citation: NIGMS - YouTube (RRID:SCR_005678) Copy   

•   Source: SciCrunch Registry

http://www.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/contrack

An algorithm for identifying pathways that are known to exist between two regions within DTI data of anisotropic tissue, e.g., muscle, brain, spinal cord. The ConTrack algorithms use knowledge of DTI scanning physics and apriori information about tissue architecture to identify the location of connections between two regions within the DTI data. Assuming a course of connection or pathway between these two regions is known to exist within the measured tissue, ConTrack can be used to estimate properties of these connections in-vivo.

Proper citation: ConTrack (RRID:SCR_002681) Copy   

•   Source: SciCrunch Registry

https://github.com/nbcrrolls/workflows/tree/master/Production/AmberGPUMDSimulation

A workflow for running molecular dynamics simulations. It can be used for all-atom molecular dynamic simulations, which involve five steps of minimization, one step of heating, three steps of equilibration, and one or more instances of production. The input is a set of directories that include the MD simulation input scripts, system topology and coordinate files. Output files are list of plots, simulation trajectories, intermediate files, restart files, and the like.

Proper citation: Molecular Dynamics Workflow (BioKepler) (RRID:SCR_014389) Copy   

•   Source: SciCrunch Registry

https://github.com/CEGRcode/stencil

Web engine for visualizing and sharing life science datasets.Designed to organize, visualize, and enable sharing of interactive genomic data visualizations. Provides ability to inspect and interpret sequencing data, without requiring programming expertise.

Proper citation: STENCIL (RRID:SCR_021878) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/apps/mediawiki/mummergpu/index.php?title=MUMmerGPU

Software tool as high throughput DNA sequence alignment program that runs on nVidia G80-class GPUs. Aligns sequences in parallel on video card to accelerate widely used serial CPU program MUMmer.

Proper citation: MUMmerGPU (RRID:SCR_001200) Copy   

•   Source: SciCrunch Registry

https://github.com/RabadanLab/arcasHLA

Software tool for high resolution HLA typing from RNAseq. Fast and accurate in silico inference of HLA genotypes from RNA-seq.

Proper citation: arcasHLA (RRID:SCR_022286) Copy   

•   Source: SciCrunch Registry

http://zebrafinch.brainarchitecture.org/

Atlas of high resolution Nissl stained digital images of the brain of the zebra finch, the mainstay of songbird research. The cytoarchitectural high resolution photographs and atlas presented here aim at facilitating electrode placement, connectional studies, and cytoarchitectonic analysis. This initial atlas is not in stereotaxic coordinate space. It is intended to complement the stereotaxic atlases of Akutegawa and Konishi, and that of Nixdorf and Bischof. (Akutagawa E. and Konishi M., stereotaxic atalas of the brain of zebra finch, unpublished. and Nixdorf-Bergweiler B. E. and Bischof H. J., A Stereotaxic Atlas of the Brain Of the Zebra Finch, Taeniopygia Guttata, http://www.ncbi.nlm.nih.gov.) The zebra finch has proven to be the most widely used model organism for the study of the neurological and behavioral development of birdsong. A unique strength of this research area is its integrative nature, encompassing field studies and ethologically grounded behavioral biology, as well as neurophysiological and molecular levels of analysis. The availability of dimensionally accurate and detailed atlases and photographs of the brain of male and female animals, as well as of the brain during development, can be expected to play an important role in this research program. Traditionally, atlases for the zebra finch brain have only been available in printed format, with the limitation of low image resolution of the cell stained sections. The advantages of a digital atlas over a traditional paper-based atlas are three-fold. * The digital atlas can be viewed at multiple resolutions. At low magnification, it provides an overview of brain sections and regions, while at higher magnification, it shows exquisite details of the cytoarchitectural structure. * It allows digital re-slicing of the brain. The original photographs of brain were taken in certain selected planes of section. However, the brains are seldom sliced in exactly the same plane in real experiments. Re-slicing provides a useful atlas in user-chosen planes, which are otherwise unavailable in the paper-based version. * It can be made available on the internet. High resolution histological datasets can be independently evaluated in light of new experimental anatomical, physiological and molecular studies.

Proper citation: Zebrafinch Brain Architecture Project (RRID:SCR_004277) Copy   

•   Source: SciCrunch Registry

http://nramm.scripps.edu/

Biomedical technology research center that develops, tests and applies technology aimed toward completely automating the processes involved in solving macromolecular structures using cryo-electron microscopy. The goal is to establish a resource that will serve both as a center for high-throughput molecular microscopy as well as for transferring this technique to the research community. Current Core Technology Research and Development is focused on 4 areas: improving grid substrates and specimen preparation; further automation and optimization of image acquisition; development of an integrated single particle analysis and processing pipeline; and the development of automated high throughput EM screening. NRAMM welcomes applications of both collaborative and service projects.

Proper citation: National Resource for Automated Molecular Microscopy (RRID:SCR_001448) Copy   

•   Source: SciCrunch Registry

http://www.acert.cornell.edu/

Biomedical technology research center that develops methods, both experimental and theoretical, of modern electron spin resonance (ESR) for biomedical applications. Center technologies are applicable to the determination of the structure and complex dynamics of proteins. Principal areas of expertise: * Pulsed Fourier Transform and Two Dimensional ESR * High Frequency-High Field (HFHF) ESR * High Resolution ESR Microscopy * Theory and Computational Methods for Modern ESR Activities include: * making resources available to the biomedical community, * publishing results, * running workshops on the new methodologies, * addressing the need to bring these new technologies to other laboratories.

Proper citation: National Biomedical Center for Advanced ESR Technology (RRID:SCR_001444) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/cibc/

Biomedical technology research center that produces open-source software tools for biomedical image-based modeling, biomedical simulation and estimation, and the visualization of biomedical data. The Center works closely with software users and collaborators in a range of scientific domains to produce user-optimized tools and provides advice, technical support, workshops, and education to enhance user success. Biological projects and collaborations drive their development efforts, all with a single unifying vision: to develop the role of image-based modeling and analysis in biomedical science and clinical practice. The CIBC has a strong, ongoing emphasis on software simulation of bioelectric fields, with clinically oriented collaborations in cardiac defibrillation and the diagnosis/treatment of epilepsy. In addition, the CIBC has expanded in recent years to include applications of statistical shape analysis and three-dimensional visualization to mouse genetics and neuroimaging and applications of image and geometry processing to cell biology.

Proper citation: Center for Integrative Biomedical Computing (RRID:SCR_001961) Copy   

•   Source: SciCrunch Registry

http://www.lfd.uci.edu/

Biomedical technology research center and training resource that develops novel fluorescence technologies, including instrumentation, methods and software applicable to cellular imaging and the elucidation of dynamic processes in cells. The LFD's main activities are: * Services and Resources: the LFD provides a state-of-the-art laboratory for fluorescence measurements, microscopy and spectroscopy, with technical assistance to visiting scientists. * Research and Development: the LFD designs, tests, and implements advances in the technology of hardware, software, and biomedical applications. * Training and Dissemination: the LFD disseminates knowledge of fluorescence spectroscopic principles, instrumentation, and applications to the scientific community.

Proper citation: Laboratory for Fluorescence Dynamics (RRID:SCR_001437) Copy   

•   Source: SciCrunch Registry

http://www.ks.uiuc.edu/

Biomedical technology research center focusing on the structure and function of supramolecular systems in the living cell as well as on the development of new algorithms and efficient computing tools for physical biology. They bring the most advanced molecular modeling, bioinformatics, and computational technologies to bear on questions of biomedical relevance. They extend, refine and deliver these technologies in response to experimental progress and emerging needs of the wide biomedical research community. They magnify the impact of their work through direct collaboration with experimental researchers, the distribution of cutting-edge and user-friendly software, and via extensive training, service, and dissemination efforts. The multidisciplinary team is engaged in the modeling of large macromolecular systems in realistic environments, and has produced ground-breaking insights into biomolecular processes coupled with mechanical force, bioelectronic processes in metabolism and vision, and with the function and mechanism of membrane proteins. They are committed and work towards further advancement of * Molecular modeling tools which can integrate structural information with bioinformatics databases and molecular dynamics simulations, and which can be used by a wide audience; * High performance molecular visualization and simulation software, capable of modeling biomolecules in realistic environments of 100,000,000 atoms or more; * Conceptual and methodological foundations of molecular modeling in the fields of quantum biology, mechanobiology, and interactive modeling; * Biomedical science through collaborations between theoretical and experimental researchers; * Support of the entire research process and training through a web-enabled collaborative environment; and * Service, training, and dissemination by leveraging web-based molecular graphics and integrated modeling technologies.

Proper citation: NIH Center for Macromolecular Modeling and Bioinformatics (RRID:SCR_001435) Copy   

•   Source: SciCrunch Registry

https://biocars.uchicago.edu/

Biomedical technology research center and training resource that is a state-of-the art, national user facility for synchrotron-based studies of dynamic and static properties of macromolecules by X-ray scattering techniques such as crystallography (specializing in time-resolved), small- and wide-angle X-ray scattering and fiber diffraction. BioCARS operates two X-ray beamlines, embedded in a Biosafety Level 3 (BSL-3) facility unique in the U.S. that permits safe studies of biohazardous materials such as human pathogens., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BioCARS (RRID:SCR_001439) Copy   

•   Source: SciCrunch Registry