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http://www.ebi.ac.uk/biomodels-main/

Repository of mathematical models of biological and biomedical systems. Hosts selection of existing literature based physiologically and pharmaceutically relevant mechanistic models in standard formats. Features programmatic access via Web Services. Each model is curated to verify that it corresponds to reference publication and gives proper numerical results. Curators also annotate components of models with terms from controlled vocabularies and links to other relevant data resources allowing users to search accurately for models they need. Models can be retrieved in SBML format and import/export facilities are being developed to extend spectrum of formats supported by resource.

Proper citation: BioModels (RRID:SCR_001993) Copy   

•   Source: SciCrunch Registry

http://www.pathwaycommons.org/pc

Database of publicly available pathways from multiple organisms and multiple sources represented in a common language. Pathways include biochemical reactions, complex assembly, transport and catalysis events, and physical interactions involving proteins, DNA, RNA, small molecules and complexes. Pathways were downloaded directly from source databases. Each source pathway database has been created differently, some by manual extraction of pathway information from the literature and some by computational prediction. Pathway Commons provides a filtering mechanism to allow the user to view only chosen subsets of information, such as only the manually curated subset. The quality of Pathway Commons pathways is dependent on the quality of the pathways from source databases. Pathway Commons aims to collect and integrate all public pathway data available in standard formats. It currently contains data from nine databases with over 1,668 pathways, 442,182 interactions,414 organisms and will be continually expanded and updated. (April 2013)

Proper citation: Pathway Commons (RRID:SCR_002103) Copy   

•   Source: SciCrunch Registry

http://www.berkeleybop.org/

The BBOP, located at the Lawrence Berkeley National Labs, is a diverse group of scientific researchers and software engineers dedicated to developing tools and applying computational technologies to solve biological problems. Members of the group contribute to a number of projects, including the Gene Ontology, OBO Foundry, the Phenotypic Quality Ontology, modENCODE, and the Generic Model Organism Database Project. Our group is focused on the development, use, and integration of ontolgies into biological data analysis. Software written or maintained by BBOP is accessible through the site.

Proper citation: Berkeley Bioinformatics Open-Source Projects (RRID:SCR_006704) Copy   

•   Source: SciCrunch Registry

http://www.peptideatlas.org

Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. The raw data, search results, and full builds can be downloaded for other uses. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. The long term goal of the project is full annotation of eukaryotic genomes through a thorough validation of expressed proteins. The PeptideAtlas provides a method and a framework to accommodate proteome information coming from high-throughput proteomics technologies. The online database administers experimental data in the public domain. You are encouraged to contribute to the database.

Proper citation: PeptideAtlas (RRID:SCR_006783) Copy   

•   Source: SciCrunch Registry

http://cebs.niehs.nih.gov

Repository for toxicogenomics data, including study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. Data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. Data relating to environmental health, pharmacology, and toxicology. It is not necessary to have microarray data, but study design and phenotypic anchoring data are required.CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Biomedical Investigation Database is another component of CEBS system. used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee. BID has been shared with Health Canada and the US Environmental Protection Agency.

Proper citation: Chemical Effects in Biological Systems (CEBS) (RRID:SCR_006778) Copy   

•   Source: SciCrunch Registry

http://redfly.ccr.buffalo.edu

Curated collection of known Drosophila transcriptional cis-regulatory modules (CRMs) and transcription factor binding sites (TFBSs). Includes experimentally verified fly regulatory elements along with their DNA sequence, associated genes, and expression patterns they direct. Submission of experimentally verified cis-regulatory elements that are not included in REDfly database are welcome.

Proper citation: REDfly Regulatory Element Database for Drosophilia (RRID:SCR_006790) Copy   

•   Source: SciCrunch Registry

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.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://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://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://evolution.genetics.washington.edu/phylip.html

A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.

Proper citation: PHYLIP (RRID:SCR_006244) Copy   

•   Source: SciCrunch Registry

http://stormo.wustl.edu/ScerTF

Catalog of over 1,200 position weight matrices (PWMs) for 196 different yeast transcription factors (TFs). They've curated 11 literature sources, benchmarked the published position-specific scoring matrices against in-vivo TF occupancy data and TF deletion experiments, and combined the most accurate models to produce a single collection of the best performing weight matrices for Saccharomyces cerevisiae. ScerTF is useful for a wide range of problems, such as linking regulatory sites with transcription factors, identifying a transcription factor based on a user-input matrix, finding the genes bound/regulated by a particular TF, and finding regulatory interactions between transcription factors. Enter a TF name to find the recommended matrix for a particular TF, or enter a nucleotide sequence to identify all TFs that could bind a particular region.

Proper citation: ScerTF (RRID:SCR_006121) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/

Model organism database for the social amoeba Dictyostelium discoideum that provides the biomedical research community with integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a ''''reference genome'''' in the Amoebozoa clade. They highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase. The Dicty Stock Center currently holds over 1500 strains targeting over 930 different genes. There are over 100 different distinct amoebozoan species. In addition, the collection contains nearly 600 plasmids and other materials such as antibodies and cDNA libraries. The strain collection includes: * strain catalog * natural isolates * MNNG chemical mutants * tester strains for parasexual genetics * auxotroph strains * null mutants * GFP-labeled strains for cell biology * plasmid catalog The Dicty Stock Center can accept Dictyostelium strains, plasmids, and other materials relevant for research using Dictyostelium such as antibodies and cDNA or genomic libraries.

Proper citation: Dictyostelium discoideum genome database (RRID:SCR_006643) Copy   

•   Source: SciCrunch Registry

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/index.shtml

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

Proper citation: Bowtie (RRID:SCR_005476) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/Dicty_Info/dicty_anatomy_ontology.html

An ontology to describe Dictyostelium where the structural makeup of Dictyostelium and its composing parts including the different cell types, throughout its life cycle is defined. There are two main goals for this new tool: (1) promote the consistent annotation of Dictyostelium-specific events, such as phenotypes (already in use), and in the future, of gene expression information; and (2) encourage researchers to use the same terms with the same intended meaning. To this end, all terms are defined. The complete ontology can be browsed using EBI''s ontology browser tool. (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=DDANAT)

Proper citation: Dictyostelium Anatomy Ontology (RRID:SCR_005929) Copy   

•   Source: SciCrunch Registry

http://www.genenetwork.org/

Web platform that provides access to data and tools to study complex networks of genes, molecules, and higher order gene function and phenotypes. Sequence data (SNPs) and transcriptome data sets (expression genetic or eQTL data sets). Quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. Used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Users are welcome to enter their own private data.

Proper citation: GeneNetwork (RRID:SCR_002388) 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