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http://bioinformatics.ai.sri.com/ptools/

A software application which supplies software tools to develop and maintain pathway/genome databases (PGDBs). These include the development of organism-specific databases, metabolic reconstruction and metabolic-flux modeling, scientific visualization and web publishing of organism-specific databases, analysis of gene-expression and metabolomics datasets, comparative genome and pathway analyses, and analysis of biological networks.

Proper citation: Pathway Tools (RRID:SCR_013786) Copy   

•   Source: SciCrunch Registry

https://www.aideepmed.com/BioLiP/

Semi-manually curated database for biologically relevant ligand-protein binding interactions. Structure data are collected primarily from Protein Data Bank (PDB), with biological insights mined from literature and other specific databases. Database used for serving needs of ligand-protein docking, virtual ligand screening and protein function annotation.BioLiP2 offers significantly greater coverage of nucleic acid-protein interactions, and interactions involving large complexes, integrates structural alignment algorithms with structure prediction techniques, which enables composite protein structure and sequence-based searching.

Proper citation: BioLiP (RRID:SCR_027685) Copy   

•   Source: SciCrunch Registry

http://scicrunch.org/resources

Portal providing identifiers for Antibodies, Model Organisms, and Tools (software, databases, services) created in support of the Resource Identification Initiative, which aims to promote research resource identification, discovery, and reuse. The portal offers a central location for obtaining and exploring Research Resource Identifiers (RRIDs) - persistent and unique identifiers for referencing a research resource. A critical goal of the RII is the widespread adoption of RRIDs to cite resources in the biomedical literature and other places that reference their generation or use. RRIDs use established community identifiers where they exist, and are cross-referenced in their system where more than one identifier exists for a single resource.

Proper citation: Resource Identification Portal (RRID:SCR_004098) Copy   

•   Source: SciCrunch Registry

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

The NIGMS Inside Life Science series brings you inside the science of health. Each story shows how basic biomedical researchfrom the history of a field to the people doing cutting-edge work todaylays the foundation for advances in disease diagnosis, treatment and prevention. Through explorations of how the body works and highlights from recent studies, you''ll discover even more on what scientists have found and are finding about fundamental life processes. NIGMS supported all of the featured research.

Proper citation: NIGMS Inside Life Science (RRID:SCR_005852) Copy   

•   Source: SciCrunch Registry

http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

•   Source: SciCrunch Registry

http://www.csardock.org

Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.

Proper citation: Community Structure-Activity Resource (RRID:SCR_002206) Copy   

•   Source: SciCrunch Registry

https://simtk.org

A National NIH Center for Biomedical Computing that focuses on physics-based simulation of biological structures and provides open access to high quality simulation tools, accurate models and the people behind them. It serves as a repository for models that are published (as well as the associated code) to create a living archive of simulation scholarship. Simtk.org is organized into projects. A project represents a research endeavor, a software package or a collection of documents and publications. Includes sharing of image files, media, references to publications and manuscripts, as well as executables and applications for download and source code. Simulation tools are free to download and space is available for developers to manage, share and disseminate code.

Proper citation: Simtk.org (RRID:SCR_002680) Copy   

•   Source: SciCrunch Registry

http://bioportal.bioontology.org/

Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.

Proper citation: BioPortal (RRID:SCR_002713) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/foldvillin

An archive of hundreds of all-atom, explicit solvent molecular dynamics simulations that were performed on a set of nine unfolded conformations of a variant of the villin headpiece subdomain (HP-35 NleNle). It includes scripts for accessing the archive of villin trajectories as well as a VMD plug-in for viewing the trajectories. In addition, all starting structures used in the trajectories are also provided. The simulations were generated using a distributed computing method utilizing the symmetric multiprocessing paradigm for individual nodes of the Folding_at_home distributed computing network. The villin trajectories in the archive are divided into two projects: PROJ3036 and PROJ3037. PROJ3036 contains trajectories starting from nine non-folded configurations. PROJ3037 contains trajectories starting from the native (folded) state. Runs 0 through 8 (in PROJ3036) correspond to starting configurations 0 through 8 discussed in the paper in J. Mol. Biol. (2007) 374(3):806-816 (see the publications tab for a full reference), whereas RUN9 uses the same starting configuration as RUN8. Each run contains 100 trajectories (named clone 0-99), each with the same starting configuration but different random velocities. Trajectories vary in their length of time and are subdivided into frames, also known as a generation. Each frame contains around 400 configurational snapshots, or timepoints, of the trajectory, with the last configurational snapshot of frame i corresponding to the first configurational snapshot of generation i+1. The goal is to allow researchers to analyze and benefit from the many trajectories produced through the simulations.

Proper citation: Molecular Simulation Trajectories Archive of a Villin Variant (RRID:SCR_002704) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://cytoscape.org

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Proper citation: Cytoscape (RRID:SCR_003032) Copy   

•   Source: SciCrunch Registry

http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://ontodog.hegroup.org/index.php

Ontodog is a web-based ontology view generator. It can generate inSubset annotation ontology, user preferred label annotation ontology and subset of source ontology. Simply provide Ontodog input term file (Microsoft Excel file or tab-delimited text file), select one source ontology or enter your own source ontology and SPARQL endpoint, then set the settings for Ontodog output files and get the OWL (RDF/XML) Output files. Ontodog performs the basic ontology modularization-like function, i.e.,it automatically extracts all axioms and related terms associated with user-specified signature term(s). In addition, Ontodog includes extra features: (1) extracting all instance data associated with the retrieved class terms and annotations; and (2) recursively extracting all axioms and related terms indirectly associated with signature terms. More features are being added to Ontodog, such as relabeling preferred names for various ontology terms to fit in with the needs from a specific community. The Ontodog input data requires a source ontology and a list of user-specified signature terms in tab-delimited format. Ontodog provides the template files for generating the signature terms as the input terms file to download. There are several output options that the users can choose based on their needs. With more and more ontologies being developed, Ontodog offers a timely web-based package of solutions for ontology view generation. Ontodog provides an efficient approach to promote ontology sharing and interoperability. It is easy to use and does not require knowledge of SPARQL, script programming, and command line operation. Ontodog is developed to serve the ontology community for ontology reuse. It is freely available under the Apache License 2.0. The source code is made available under Apache License 2.0.

Proper citation: Ontodog: A Web-based Ontology View Generator (RRID:SCR_005061) Copy   

•   Source: SciCrunch Registry

http://www.mouse-genome.bcm.tmc.edu/ENU/MutagenesisProj.asp

THIS RESOURCE IS NO LONGER IN SERVICE. For updated mutant information, please visit MMRRC or The Jackson Laboratory. Produces, characterizes, and distributes mutant mouse strains with defects in embryonic and postembryonic development. The goal of the ENU Mutagenesis project III is to determine the function of genes on mouse Chromosome 11 by saturating the chromosome with recessive mutations. The distal 40 cM of mouse Chr 11 exhibits linkage conservation with human Chromosome 17. We are using the chemical N-ethyl-N-nitrosourea (ENU) to saturate wild type chromosomes with point mutations. By determining the function of genes on a mouse chromosome, we can extrapolate to predict function on a human chromosome. We expect many of the new mutants to represent models of human diseases such as birth defects, patterning defects, growth and endocrine defects, neurological anomalies, and blood defects. Because many of the mutations we expect to isolate may be lethal or detrimental to the mice, we are using a unique approach to isolate mutations. This approach uses a balancer chromosome that is homozygous lethal and carries a dominant coat color marker to suppress recombination over a reasonable interval.

Proper citation: Mouse Mutagenesis Center for Developmental Defects (RRID:SCR_007321) Copy   

•   Source: SciCrunch Registry

http://cellprofiler.org

Software tool to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. It counts cells and also measures the size, shape, intensity and texture of every cell (and every labeled subcellular compartment) in every image. It was designed for high throughput screening but can perform automated image analysis for images from time-lapse movies and low-throughput experiments. CellProfiler has an increasing number of algorithms to identify and measure properties of neuronal cell types.

Proper citation: CellProfiler Image Analysis Software (RRID:SCR_007358) Copy   

•   Source: SciCrunch Registry

http://oufti.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://evcouplings.org/

Web server provides functional and structural information about proteins from their evolutionary record using methods from statistical physics. Computes evolutionary couplings from sequence alignments and predicts 3D structure for your protein of interest. Allows to run former EVcouplings, EVmutation, EVfold and EVcomplex jobs.

Proper citation: Evolutionary Couplings Server (RRID:SCR_018745) Copy   

•   Source: SciCrunch Registry

https://www.bcforms.org

Software toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks. Web tool for describing molecular structure of macromolecular complexes, including non canonical monomeric forms, circular topologies, and crosslinks. Describes semantic meaning of whole cell computational models.

Proper citation: BcForms (RRID:SCR_018654) Copy   

•   Source: SciCrunch Registry