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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://gowiki.tamu.edu/wiki/

A wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase...

Proper citation: GONUTS (RRID:SCR_000653) 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.zfishbook.org/NGP/journalcontent/SCORE/SCORE.html

Narrative resource describing a visual data analysis and collection approach that takes advantage of the cylindrical nature of the zebrafish allowing for an efficient and effective method for image capture called, Specimen in a Corrected Optical Rotational Enclosure (SCORE) Imaging. To achieve a non-distorted image, zebrafish were placed in a fluorinated ethylene propylene (FEP) tube with a surrounding, optically corrected imaging solution: water. By similarly matching the refractive index of the housing (FEP tubing) to that of the inner liquid and outer liquid (water), distortion was markedly reduced, producing a crisp imagable specimen that is able to be fully rotated 360 degrees. A similar procedure was established for fixed zebrafish embryos using convenient, readily available borosilicate capillaries surrounded by 75% glycerol. The method described could be applied to chemical genetic screening and other, related high-throughput methods within the fish community and among other scientific fields.

Proper citation: Zebrafish - SCORE Imaging: Specimen in a Corrected Optical Rotational Enclosure (RRID:SCR_001300) Copy   

•   Source: SciCrunch Registry

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

An NIGMS magazine that showcases the exciting ways that scientists are using the power of computers to expand our knowledge of biology and medicine. From text messaging friends to navigating city streets with GPS technology, we''re all living the computing life. But as we''ve upgraded from snail mail and compasses, so too have scientists. Computer advances now let researchers quickly search through DNA sequences to find gene variations that could lead to disease, simulate how flu might spread through your school and design three-dimensional animations of molecules that rival any video game. By teaming computers and biology, scientists can answer new and old questions that could offer insights into the fundamental processes that keep us alive and make us sick. This booklet introduces you to just some of the ways that physicists, biologists and even artists are computing life. Each section focuses on a different research problem, offers examples of current scientific projects and acquaints you with the people conducting the work. You can follow the links for online extras and other opportunities to learn aboutand get involved inthis exciting new interdisciplinary field.

Proper citation: NIGMS Computing Life (RRID:SCR_005850) 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

http://www.mcell.cnl.salk.edu/

Software modeling tool for realistic simulation of cellular signaling in complex 3-D subcellular microenvironment in and around living cells. Program that uses spatially realistic 3D cellular models and specialized Monte Carlo algorithms to simulate movements and reactions of molecules within and between cells.

Proper citation: MCell (RRID:SCR_007307) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/simtkcore

SimTK Core is one of the two packages that together constitute SimTK, the biosimulation toolkit from the Simbios Center. The other major component of SimTK is OpenMM which is packaged separately. This SimTK Core project collects together all the binaries needed for the various SimTK Core subprojects. These include Simbody, Molmodel, Simmath (including Ipopt), Simmatrix, CPodes, SimTKcommon, and Lapack. See the individual projects for descriptions. SimTK brings together in a robust, convenient, open source form the collection of highly-specialized technologies necessary to building successful physics-based simulations of biological structures. These include: strict adherence to an important set of abstractions and guiding principles, robust, high-performance numerical methods, support for developing and sharing physics-based models, and careful software engineering. Accessible High Performance Computing We believe that a primary concern of simulation scientists is performance, that is, speed of computation. We seek to build valid, approximate models using classical physics in order to achieve reasonable run times for our computational studies, so that we can hope to learn something interesting before retirement. In the choice of SimTK technologies, we are focused on achieving the best possible performance on hardware that most researchers actually have. In today''s practice, that means commodity multiprocessors and small clusters. The difference in performance between the best methods and the do-it-yourself techniques most people use can be astoundingeasily an order of magnitude or more. The growing set of SimTK Core libraries seeks to provide the best implementation of the best-known methods for widely used computations such as: Linear algebra, numerical integration and Monte Carlo sampling, multibody (internal coordinate) dynamics, molecular force field evaluation, nonlinear root finding and optimization. All SimTK Core software is in the form of C++ APIs, is thread-safe, and quietly exploits multiple CPUs when they are present. The resulting pre-built binaries are available for download and immediate use. Audience: Biosimulation application programmers interested in including robust, high-performance physics-based simulation in their domain-specific applications.

Proper citation: SimTKCore (RRID:SCR_008268) Copy   

•   Source: SciCrunch Registry

http://images.nigms.nih.gov/

Database of scientific photos, illustrations, and videos made available by the National Institute of General Medical Sciences.

Proper citation: National Institute of General Medical Sciences Image Gallery (RRID:SCR_003480) Copy   

•   Source: SciCrunch Registry

http://libroadrunner.org/

Simulation engine for systems and synthetic biology to be used with other software applications. It retains the original functionality of RoadRunner but has changes in performance, back-end design, event handling, new C++ API, and stochastic simulation support.

Proper citation: libRoadRunner (RRID:SCR_014763) Copy   

•   Source: SciCrunch Registry

http://opensim.stanford.edu

OpenSim is an open-source software system that lets users develop models of musculoskeletal structures and create dynamic simulations of movement. The software provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through multi-institutional collaboration. The underlying software is written in ANSI C++, and the graphical user interface (GUI) is written in Java. OpenSim technology makes it possible to develop customized controllers, analyses, contact models, and muscle models among other things. These plugins can be shared without the need to alter or compile source code. Users can analyze existing models and simulations and develop new models and simulations from within the GUI.

Proper citation: OpenSim (RRID:SCR_002683) Copy   

•   Source: SciCrunch Registry

https://github.com/mrc-ide/PhyDyn

Sofware package for performing Bayesian phylogenetic inference under models that deal with structured populations with complex population dynamics. Enables simultaneous estimation of epidemiological parameters and pathogen phylogenies. Epidemiological modelling in BEAST.

Proper citation: PhyDyn (RRID:SCR_018544) 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

https://www.mc.vanderbilt.edu/victr/dcc/projects/acc/index.php/Main_Page

A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community.

Proper citation: eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) Copy   

•   Source: SciCrunch Registry

http://www.jneurosci.org/supplemental/18/12/4570/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 29, 2013. Supplemental data for the paper Changes in mitochondrial function resulting from synaptic activity in the rat hippocampal slice, by Vytautas P. Bindokas, Chong C. Lee, William F. Colmers, and Richard J. Miller that appears in the Journal of Neuroscience June 15, 1998. You can view digital movies of changes in fluorescence intensity by clicking on the title of interest.

Proper citation: Hippocampal Slice Wave Animations (RRID:SCR_008372) Copy   

•   Source: SciCrunch Registry

http://salilab.org/modeller/modeller.html

Software tool as Program for Comparative Protein Structure Modelling by Satisfaction of Spatial Restraints. Used for homology or comparative modeling of protein three dimensional structures. User provides alignment of sequence to be modeled with known related structures and MODELLER automatically calculates model containing all non hydrogen atoms.

Proper citation: MODELLER (RRID:SCR_008395) Copy   

•   Source: SciCrunch Registry

http://ophid.utoronto.ca/i2d

Database of known and predicted mammalian and eukaryotic protein-protein interactions, it is designed to be both a resource for the laboratory scientist to explore known and predicted protein-protein interactions, and to facilitate bioinformatics initiatives exploring protein interaction networks. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered predictions. It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. It contains 490,600 Source Interactions, 370,002 Predicted Interactions, for a total of 846,116 interactions, and continues to expand as new protein-protein interaction data becomes available.

Proper citation: I2D (RRID:SCR_002957) Copy   

•   Source: SciCrunch Registry

http://dip.doe-mbi.ucla.edu/

Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.

Proper citation: Database of Interacting Proteins (DIP) (RRID:SCR_003167) Copy   

•   Source: SciCrunch Registry