Tools   Select Another Resource Report Type

http://cs.nyu.edu/~bingsun/

NYU Bioinformatics group applies algorithmic, statistical, and mathematical techniques to solve problems of interest to biology, biotechnology and biomedicine. The group focuses on bioinformatics, computational biology and systems biology with many active projects in areas ranging from single molecules to entire populations: Analysis of Single-Molecule/Single-Cell Data, SPM-based Transcriptomic Profiling, Whole-Genome Haplotype Sequencing using SMASH (Single Molecule Approaches to Haplotype Sequencing), SUTTA (Scoring and Unfolding Trimmed Tree Assembler) assembly algorithm, Analysis of Spatio-Temporal Data, Model Checking and Model Building for Systems Biology, GOALIE-based Phenomenological Models and their Verification, Causality Analysis, Causal Models and their Verification, Analysis of EHR (Electronic Health Record Data) and Disease Models (e.g., Chronic Fatigue Syndrome, Congestive Heart Failure, Deep Vein Thrombosis, etc.), Models of Cancer, Applications to Pancreatic Cancer, Polymorphisms and Biomarkers, Strategies for Group Testing, Epidemiological and Bio-Warfare Models, Planning with Large Agent Networks against Catastrophes (PLAN C), Population Genomics, and Genome Wide Association Studies (GWAS). The group has received its funding from Air Force, Army, CCPR, DARPA, NIH, NIST, NSF, NYSTAR, etc. and various other governmental and commercial entities. Currently, the group is part of an NSF funded Expedition in Computing project (CMACS: Center for Modeling and Analysis of Complex Systems at CMU) and collaborates widely, both nationally and internationally. The group is highly multi-disciplinary, attracting researchers and students from mathematics, statistics, computer science, and biology who team up with physicians, physicists, and chemists as well as professionals in their own disciplines. This group is led by Prof. Bud Mishra, a professor of computer science and mathematics at NYU''s Courant Institute of Mathematical Sciences.

Proper citation: NYU Bioinformatics Group (RRID:SCR_005697) Copy   

•   Source: SciCrunch Registry

http://www.chori.org/

CHORI is the internationally renowned biomedical research institute of Children''s Hospital and Research Center at Oakland. With world-class scientists and research centers known both nationally and internationally in multiple fields, CHORI is 5th in the nation for National Institutes of Health pediatric research funding. Bridging basic science and clinical research in the treatment and prevention of human disease, CHORI is a leader in translational research, providing cures for blood diseases, developing new vaccines for infectious diseases, and discovering new treatment protocols for previously fatal or debilitating conditions. Striving to provide the highest standard of excellence and innovation, CHORI brings together a multidisciplinary collaborative of distinguished investigators in six different Centers of Research: The Center for Cancer Research, The Center for Genetics, The Center for Immunobiology & Vaccine Development, The Center for Nutrition & Metabolism, The Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, and The Center for Sickle Cell Disease & Thalassemia. Within these major areas of focus, CHORI pushes the frontiers of science and of excellence beyond their borders. Among the leading biotech enterprises in the Bay Area, CHORI produced 25 patents in the last 5 years alone. In addition to providing world-class research, CHORI is also a teaching institute, offering unique educational opportunities to high school, college, doctoral and post-doctoral students.

Proper citation: Childrens Hospital Oakland Research Institute (RRID:SCR_005582) Copy   

•   Source: SciCrunch Registry

http://www.na-mic.org/Wiki/index.php/SoftwareInventory

A free open source software platform consisting of the 3D Slicer application software, a number of tools and toolkits such as VTK and ITK, and a software engineering methodology that enables multiplatform implementations. It also draws on other best practices from the community to support automatic testing for quality assurance. The NA-MIC kit uses a modular approach, where the individual components can be used by themselves or together. The NA-MIC kit is fully-compatible with local installation (behind institutional firewalls) and installation as an internet service. Significant effort has been invested to ensure compatibility with standard file formats and interoperability with a large number of external applications. Users of the NAMIC Kit will typically use a combination of its many modular components. * 3D Slicer is a general purpose application. Biomedical researchers will typically use this software tool to load, view, analyze, process and save image data. Slicer has been implemented to interoperate with many other tools, including XNAT, which is an open source image database. * Slicer modules, which are dynamically loaded by Slicer at run-time, can be used to extend Slicer''''s core functionality including defining graphical user interfaces. Modules are typically used by algorithms and application developers. * Application and algorithms developers may also use NA-MIC Kit toolkits and libraries. For example, the Insight Segmentation and Registration Toolkit ITK can be used to develop slicer modules for medical image analysis. The Visualization Toolkit can be used to process, visualize and graphically interact with data. KWWidgets is a 2D graphical user interface toolset that can be used to build applications. Teem is a library of general purpose command-line tools that are useful for processing data. Finally, those individuals wishing to create and manage complex software, the NAMIC-Kit software process is available as embodied in CMake, CTest, CPack, DART and the various documentation, bug tracking and communication tools.

Proper citation: NA-MIC Kit (RRID:SCR_005616) Copy   

•   Source: SciCrunch Registry

http://www.poissonboltzmann.org/apbs/

APBS is a software package for modeling biomolecular solvation through solution of the Poisson-Boltzmann equation (PBE), one of the most popular continuum models for describing electrostatic interactions between molecular solutes in salty, aqueous media. APBS was designed to efficiently evaluate electrostatic properties for such simulations for a wide range of length scales to enable the investigation of molecules with tens to millions of atoms. It also provides implicit solvent models of nonpolar solvation which accurately account for both repulsive and attractive solute-solvent interactions. APBS uses FEtk (the Finite Element ToolKit) to solve the Poisson-Boltzmann equation numerically. FEtk is a portable collection of finite element modeling class libraries written in an object-oriented version of C. It is designed to solve general coupled systems of nonlinear partial differential equations using adaptive finite element methods, inexact Newton methods, and algebraic multilevel methods.

Proper citation: Adaptive Poisson-Boltzmann Solver (RRID:SCR_008387) Copy   

•   Source: SciCrunch Registry

https://cgc.umn.edu

Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.

Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy   

•   Source: SciCrunch Registry

http://www.geisha.arizona.edu/geisha/

Online repository for chicken in situ hybridization information. This site presents whole mount in situ hybridization images and corresponding probe and genomic information for genes expressed in chicken embryos in Hamburger Hamilton stages 1-25 (0.5-5 days). The GEISHA project began in 1998 to investigate using high throughput whole mount in situ hybridization to identify novel, differentially expressed genes in chicken embryos. An initial expression screen of approximately 900 genes demonstrated feasibility of the approach, and also highlighted the need for a centralized repository of in situ hybridization expression data. Objectives: The goals of the GEISHA project are to obtain whole mount in situ hybridization expression information for all differentially expressed genes in the chicken embryo between HH stages 1-25, to integrate expression data with the chicken genome browsers, and to offer this information through a user-friendly graphical user interface. In situ hybridization images are obtained from three sources: 1. In house high throughput in situ hybridization screening: cDNAs obtained from several embryonic cDNA libraries or from EST repositories are screened for expression using high throughput in situ hybridization approaches. 2. Literature curation: Agreements with journals permit posting of published in situ hybridization images and related information on the GEISHA site. 3. Unpublished in situ hybridization information from other laboratories: laboratories generally publish only a small fraction of their in situ hybridization data. High quality images for which probe identity can be verified are welcome additions to GEISHA.

Proper citation: GEISHA - Gallus Expression in Situ Hybridization Analysis: A Chicken Embryo Gene Expression Database (RRID:SCR_007440) Copy   

•   Source: SciCrunch Registry

http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

•   Source: SciCrunch Registry

http://www.msmc.com/neurosciences/wien-center-for-alzheimers-disease-memory-disorders

A joint program between Mount Sinai Medical Center and the University of Miami Department of Psychiatry that seeks an end to Alzheimer's disease and similar disorders through research, diagnosis, education and treatment. The goals are to improve memory and mental responsiveness of Alzheimer's patients, delay the onset of the disease and, ultimately, find a cure. The Wien Center typically conducts multidisciplinary initiatives utilizing clinical trials.

Proper citation: Wien Center For Alzheimer's Disease and Memory Disorders (RRID:SCR_008755) Copy   

•   Source: SciCrunch Registry

http://mli.nih.gov/mli/

High throughput screening services to identify small molecules that can be optimized as chemical probes to study the functions of genes, cells, and biochemical pathways, along with medicinal chemistry and informatics. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. The NIH Molecular Libraries Initiative NIH is designed to discover small molecules that interact with biologically important proteins and pathways and to provide open access to the bioassay and chemical data generated by its research centers. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. As these HTS Technologies were not previously available to the public sector, many investigators may not be familiar with the components and requirements of high throughput screening. A key challenge is to identify small molecules effective at modulating a given biological process or disease state. The Molecular Libraries Roadmap, through one of its components, the Molecular Libraries Probe Production Centers Network (MLPCN), offers biomedical researchers access to the large-scale screening capacity, along with medicinal chemistry and informatics necessary to identify chemical probes to study the functions of genes, cells, and biochemical pathways. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. There are two kinds of data that are available to the scientific community through a dedicated database: Chemical Compounds and Bioassay Results (NCBI). Various types of data, including informative records on substances, compound structures, and biologically active properties of small molecules are housed respectively within PubChem''''s three primary databases: PCSubstance, PCCompound, and PCBioAssay. To date, PubChem contains over 11 million substance records, details about approximately 5.5 million unique compound structures with links to bioassay descriptions, relevant literature, references, and assay data points and over 250 bioassays, a good percentage of which were contributed by the pilot phase of the MLP. The deposition will continue during the current MLPCN phase. NIH anticipates that these projects will also facilitate the development of new drugs, by providing early stage chemical compounds that will enable researchers in the public and private sectors to validate new drug targets, which could then move into the drug-development pipeline. This is particularly true for rare diseases, which may not be attractive for development by the private sector. Funding opportunities are available through the site.

Proper citation: Molecular Libraries Program (RRID:SCR_008847) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/health/services/brain/

A clinical care and research center for neurological conditions such as Alzheimer's, dementia and seizure disorders. It provides a dynamic setting for training healthcare professionals and neuroscience researchers to develop and implement evidence-based treatment.

Proper citation: OHSU Brain Institute (RRID:SCR_008932) Copy   

•   Source: SciCrunch Registry

http://cbfbirn.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

Proper citation: CBFBIRN (RRID:SCR_009543) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://ccdb.ucsd.edu/SAO

Ontology that describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules. It is built according to ontology development best practices (re-use of existing ontologies; formal definitions of terms; use of foundational ontologies). It describes the parts of neurons and glia and how these parts come together to define supracellular structures such as synapses and neuropil. Molecular specializations of each compartment and cell type are identified. The SAO was designed with the goal of providing a means to annotate cellular and subcellular data obtained from light and electron microscopy, including assigning macromolecules to their appropriate subcellular domains. The SAO thus provides a bridge between ontologies that describe molecular species and those concerned with more gross anatomical scales. Because it is intended to integrate into ontological efforts at these other scales, particular care was taken to construct the ontology in a way that supports such integration.

Proper citation: Subcellular Anatomy Ontology (RRID:SCR_003486) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/alzheimers.htm

The Alzheimer's disease arm of the Accelerating Medicines Partnership (AMP) that will identify biomarkers that can predict clinical outcomes, conduct a large scale analysis of human AD patient brain tissue samples to validate biological targets, and to increase the understanding of molecular pathways involved in the disease to identify new potential therapeutic targets. The initiative will deposit all data in a repository that will be accessible for use by the biomedical community. The five year endeavor, beginning in 2014, will result in several sets of project outcomes. For the biomarkers project, tau imaging and EEG data will be released in year two, as baseline data becomes available. Completed data from the randomized, blinded trials will be added after the end of the five year studies. This will include both imaging data and data from blood and spinal fluid biomarker studies. For the network analysis project, each project will general several network models of late onset AD (LOAD) and identify key drivers of disease pathogensis by the end of year three. Years four and five will be dedicated to validating the novel targets and refining the network models of LOAD, including screening novel compounds or drugs already in use for other conditions that may have the ability to modulate the likely targets.

Proper citation: Accelerating Medicines Partnership - Alzheimers (RRID:SCR_003742) Copy   

•   Source: SciCrunch Registry

http://elementsofmorphology.nih.gov/

Data set of standardized terms used to describe human morphology including definitions of terms for the craniofacies in general, the major components of the face, and the hands and feet. This provides a uniform and internationally accepted terms to describe the human phenotype.

Proper citation: elements of morphology (RRID:SCR_003707) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/autoimmune.htm

The autoimmune disease arm of the Accelerating Medicine Partnership (AMP), which aims to identify and validate the most promising biological targets of disease for new diagnostic and drug development, that is focused on rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). They seek to identify shared common flaws in inflammation, particularly those that are shared with a larger number of autoimmune disorders which can cause severe disability, greatly affect quality of life, and are associated with an increased risk of death. This project aims to reveal biomarkers and biological targets for drug development, matching existing drugs to patients with specific molecular profiles who are most likely to benefit. The research plan proposes a 5 year process. Year one will include startup activities such as validation of tissue acquisition processes and analytic technologies, and the development of operating procedures. The second year will focus on identification of disease specific pathways by comparing data from patients and healthy individuals. Years 3-5 will expand the scale to include comparisons of different subsets of patients with RA or lupus to allow molecularly based patient stratification for precise treatment. The final 12 months (2019) will also include preliminary target validation. The data will be made publicly available through an internet-based information portal.

Proper citation: Accelerating Medicines Partnership Autoimmune Diseases of Rheumatoid Arthritis and Lupus (RRID:SCR_003731) Copy   

•   Source: SciCrunch Registry

http://www.med.uc.edu/cardio_bio/

Our 24 faculty members approach the Research and Training in Cardiovascular Biology program from different subspecialties that include genetics, metabolism, development, cellular biology, systems biology, structural biology, biophysics, pharmacology, molecular biology, bioinformatics and biochemistry. While these subspecialties are clearly diverse, our faculty collaboratively leverages these areas toward the common goal of understanding cardiovascular disease from the gene all the way up to integrated organism function (systems biology). This diverse array of subspecialties provides a truly unique training environment that few centers can match. Another critical aspect of our training program is our steadfast commitment to a superior and nurturing training environment for our predoctoral trainees, postdoctoral trainees and clinician-scientists. Our training faculty are uniformly committed to monitoring our personnel for success in every way possible, to not only ensure their future placement in the academic ranks but to also build a stronger cardiovascular community around the country. The current National Institutes of Health-sponsored Research and Training in Cardiovascular Biology was instituted in 1978 by Arnold Schwartz, MD, PhD. This program has trained more than 120 scientists, who have pursued independent research careers and are holding prominent scientific positions worldwide. Our trainees have been distinguished as chairs of basic science departments, directors of centers or pharmaceutical companies, clinical directors and tenured faculty members in academic research. The overall emphasis continues to focus on integrative training and well-rounded knowledge of the fundamentals in biochemical, molecular, physiological and pharmacological underpinnings of cardiovascular disease. Dr. Schwartz has been a constant guiding force since the program was established. The University of Cincinnati, with Cincinnati Children's, has also developed a reputation as a leading center for the generation and analysis of genetically modified mouse models for interrogation of gene-disease relationships in the heart. This theme has been expanded to incorporate molecular genomics, proteomics and bioinformatics, as we continue to be among the leaders in the nation in molecular pathway analysis associated with single gene manipulations in the hearts of mice. Most faculty and trainees are using these approaches, but they are also well-versed in many other aspects of cardiovascular science, including excellence in basic physiology, pharmacology, biochemistry, structural biology and molecular biology. Thus, we are a rare conglomeration of faculty in which all aspects of cardiovascular biology are practiced, starting with cutting-edge molecular and genetic approaches, spanning more traditional cellular and whole animal approaches to build an integrated network of functional and disease-relevant data and extending to translational research incorporating cell therapy.

Proper citation: University of Cincinnati Research and Training in Cardiovascular Biology (RRID:SCR_003860) Copy   

•   Source: SciCrunch Registry

https://neurowiki.case.edu/

Curriculum materials for an Introduction to Neurobiology course for undergraduate and graduate students.

The course focuses on the analysis of neurons and neural circuits for behavior using the fundamental principles of neuroscience. From the online course syllabus, the 24 units that make up the course may be directly accessed. Each unit contains a reading, links to at least one simulation, and a problem set.

A list of all available simulations can be found here: https://neurowiki.case.edu/wiki/Simulations. * 25 simulations are written in JavaScript and will run in any browser.
Source code: https://github.com/CWRUChielLab/JSNeuroSim * Pre-compiled executables (Windows, Mac, Linux) are available for 1 desktop simulation, the Nernst Potential Simulator.
Source code: https://github.com/CWRUChielLab/Nernst Structure of the Course * Solving problems based on simulations of neuronal components, neurons, and simple circuits to understand how they work. * For advanced students, writing a neuroscience Wikipedia article, critical review, or grant, in stages.

Proper citation: NeuroWiki (RRID:SCR_004066) Copy   

•   Source: SciCrunch Registry

http://www.cmhd.ca/genetrap/

Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) 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