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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Software for statistical approach to identify loci within genes that are both significantly enriched in slowly translated codons and evolutionarily conserved, and also co-translational protein folding model.
Proper citation: Coarse grained co-translational folding analysis (RRID:SCR_022271) Copy
Interactive Python based interface to Rosetta molecular modeling suite. Stand alone Python based implementation of Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using major Rosetta sampling and scoring functions.
Proper citation: PyRosetta (RRID:SCR_018541) Copy
Software designed for analysis of microscopy data. It performs sub-pixel precision detection, quantification of cells and fluorescence signals, as well as other image analysis functions.
Proper citation: Oufti (RRID:SCR_016244) Copy
https://biochem.missouri.edu/chapman/software.htm
Software for fitting of atomic models into density maps derived from x-ray crystallography or electron microscopy.
Proper citation: RSRef (RRID:SCR_017211) Copy
https://www.phenix-online.org/documentation/reference/refinement.html
Software tool for a general purpose crystallographic structure refinement within the PHENIX package. Serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB.
Proper citation: Phenix.refine (RRID:SCR_016736) Copy
https://github.com/brentp/mosdepth
Software command line tool for rapidly calculating genome wide sequencing coverage. Measures depth from BAM or CRAM files at either each nucleotide position in genome or for sets of genomic regions. Used for fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing quick coverage calculation for genomes and exomes.
Proper citation: mosdepth (RRID:SCR_018929) Copy
https://mibig.secondarymetabolites.org/
MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.
Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy
http://hanalyzer.sourceforge.net/
An open-source data integration system designed to assist biologists in explaining the results observed in genome-scale experiments as well as generating new hypotheses. It combines information extraction techniques, semantic data integration, and reasoning and facilitates network visualization. The Hanalyzer source code and binaries are available for download.
Proper citation: Hanalyzer (RRID:SCR_000923) Copy
http://www.isi.edu/projects/bioscholar/overview
Knowledge management and engineering system software for experimental biomedical scientists permitting a single scientific worker (at the level of a graduate student or postdoctoral worker) to design, construct and manage a shared knowledge repository for a research group derived on a local store of PDF files. Usability is especially emphasized within a laboratory so that this software could provide support to experimental scientists attempting to construct a personalized representation of their own knowledge on a medium scale. The BioScholar system uses a graphical interface to create experimental designs based on the experimental variables in the system. The design is then analyzed to construct a tabular input form based on the data flow. They call this methodology "Knowledge Engineering from Experimental Design" or "KEfED". The approach is domain-independent but domain-specific modules reasoning can be constructed to generate interpretations from the observational data represented in the KEfED model. The application is available for download as platform-specific installers including Linux, Unix, Mac OS, and Windows. The installer will install an application that will run the BioScholar server. This server uses Jetty as its integrated web server.
Proper citation: Bioscholar (RRID:SCR_001380) Copy
https://simtk.org/home/allopathfinder
Software application and code base that allows users to compute likely allosteric pathways in proteins. The underlying assumption is that residues participating in allosteric communication should be fairly conserved and that communication happens through residues that are close in space. The initial application for the code provided was to study the allosteric communication in myosin. Myosin is a well-studied molecular motor protein that walks along actin filaments to achieve cellular tasks such as movement of cargo proteins. It couples ATP hydrolysis to highly-coordinated conformational changes that result in a power-stroke motion, or "walking" of myosin. Communication between a set of residues must link the three functional regions of myosin and transduce energy: the catalytic ATP binding region, the lever arm, and the actin-binding domain. They are investigating which residues are likely to participate in allosteric communication pathways. The application is a collection of C++/QT code, suitable for reproducing the computational results of the paper. (PMID 17900617) In addition, they provide input and alignment information to reproduce Figure 3 (a key figure) in the paper. Examples provided will show users how to use AlloPathFinder with other protein families, assumed to exhibit an allosteric communication. To run the application a multiple sequence alignment of representative proteins from the protein family is required along with at least one protein structure.
Proper citation: Allopathfinder (RRID:SCR_002702) Copy
PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.
Proper citation: PILGRM (RRID:SCR_004749) Copy
http://biomedicalcomputationreview.org
Magazine published by Simbios, a National NIH Center for Biomedical Computing, covering the latest research wherever computation, biology, and medicine intersect. In addition to disseminating information about the latest research in biomedical computation, they aim to foster community amongst the wide audience interested in any and all aspects of biomedical computing. Whether you are a long time researcher in this area or new to it, please consider joining those who have already started to participate in Biomedical Computation Review. You are encouraged to: * Write a letter to the editor on any relevant topics * Suggest your favorite topics that should receive more attention * Suggest an idea for a feature article * Propose an idea for an Under the Hood tutorial * Tell us any other way in which we can better serve this community
Proper citation: Biomedical Computation Review (RRID:SCR_004866) Copy
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
https://vanvalen.github.io/about/
Software for segmenting individual cells in microscopy images using deep learning. Cell segmentation software.
Proper citation: DeepCell (RRID:SCR_022197) Copy
http://simbios.stanford.edu/index.html
Simbios is the NIH Center for physics-based Simulation of Biological Structures. Simbios provides infrastructure, software, and training to help biomedical researchers understand biological form and function as they create novel drugs, synthetic tissues, medical devices, and surgical interventions. Simbios is investigating a wide scale of biological structures - from molecules to organisms. Driving biological problems include RNA folding, protein folding, myosin dynamics, cardiovascular dynamics, and neuromuscular biomechanics. Investigators interested in collaborating with Simbios can apply for NIH funding. To encourage collaboration in building accurate biological models and simulations, Simbios also provides the biomedical community with https://simtk.org, a free, secure, distributed, development system for projects. Projects may include models, software, data, documentation, publications, and graphics and have automatic backups and off-site storage. Projects may be public or private and have project-specific mailing lists, forums, bug & feature databases, news, blogs, and source-code repositories. Simbios is developing and disseminating the SimTK core simulation toolkit, (simtk.org/home/simtkcore). SimTK core is open-source software developed by experienced professionals. The software includes advanced capabilities for modeling the geometry and physics of biological systems. To ensure utility and accuracy, the software and training material is being developed and tested in close collaboration with biomedical scientists. Simbios has developed OpenSim, an application for advanced neuromuscular modeling that uses the SimTK toolkit, and is making it openly available at simtk.org/home/opensim. Simbios also publishes the Biomedical Computation Review, a magazine devoted to the science and tools in biocomputation, aimed at the community which encompasses the diverse biocomputation disciplines. To help researchers find high quality software and tools Simbios has also establishes the Simbiome an inventory of high-quality commercial and academic bio-simulation tools. Simbios has recurring openings for postdoctoral researchers.
Proper citation: Simbios (RRID:SCR_004320) Copy
Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
Proper citation: ImageJ (RRID:SCR_003070) Copy
https://www.proteinspire.org/MOPED/
An expanding multi-omics resource that enables rapid browsing of gene and protein expression information from publicly available studies on humans and model organisms. MOPED also serves the greater research community by enabling users to visualize their own expression data, compare it with existing studies, and share it with others via private accounts. MOPED uniquely provides gene and protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis utilizing SPIRE (Systematic Protein Investigative Research Environment). Data can be queried for specific genes and proteins; browsed based on organism, tissue, localization and condition; and sorted by false discovery rate and expression. MOPED links to various gene, protein, and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED (MOPED 2.5) The current version of MOPED (MOPED 2.5, 2014) contains approximately 5 million total records including ~260 experiments and ~390 conditions.
Proper citation: MOPED - Model Organism Protein Expression Database (RRID:SCR_006065) Copy
https://simtk.org/home/rna-viz-proto
A software application for animating and visualising RNA and other macromolecular structures. Users are able to use their intuition to interactively refold RNA structures and produce morphs from one structure to another. It allow researchers to explore and manipulate molecular structures Imported from BiositeMaps registry, to better understand structure:function relationships, folding pathways, and molecular motion.
Proper citation: ToRNADo (RRID:SCR_002706) Copy
http://ecoliwiki.net/colipedia/index.php/Welcome_to_EcoliWiki
A component of EcoliHub, EcoliWiki is a wiki-based system for finding, editing, and adding information about E. coli K-12 and other model organism strains of E. coli. EcoliWiki is being constructed to include information about bacteriophage, plasmids, and mobile genetic elements. Information should be easily accessible and correct, and users have the right to edit any information they feel is incorrect. Most of the E. coli information was initially seeded with a subset of information from parsing EcoCyc data dumps. For phage gamma and the F plasmid, Genbank accessions were converted to GFF, which was parsed into the appropriate tables. Other sources of content include: * user additions * monthly addition of annotations from EcoCyc * structural data from the PDB * domains and motif information from InterPro * various databases including EcoGene, RegulonDB, Genbank, GenoBase, ASAP * many many scientific papers EcoliWiki participates in the RefGenome project. EcoliWiki provides REST web services as part of the EcoliHub Web Services infrastructure project.
Proper citation: EcoliWiki (RRID:SCR_010656) Copy
Software platform to integrate transcription factor gene interactions and validate regulatory networks. Gene regulatory network validation.
Proper citation: ConnecTF (RRID:SCR_022577) Copy
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