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http://www.gru.edu/mcg/phy/

Department that trains independent, creative, productive scholars in the physiological sciences. The department offers programs leading to the Ph.D. degree. A combined M.D./Ph.D. or D.M.D./Ph.D. degree program is available for students who obtain prior or concurrent admission to the Schools of Medicine or Dentistry respectively. The primary research interests of the department are Cardiovascular Physiology, Endocrinology, and Neuroscience. Physiology faculty currently hold more than $7,000,000 in extramural funding, ranking 21st out of Medical School Physiology Departments nationally. Members of the Department teach in the Medical and Graduate Schools including Medical Physiology and Intergated Systems Biology, Neuroscience and advanced courses in cardiovascular and endocrine physiology.

Proper citation: Medical College of Georgia Department of Physiology (RRID:SCR_003458) Copy   

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http://www.loria.fr/~coulet/sopharm2.0_description.php

A domain ontology implemented in OWL-DL, which proposes a formal description of pharmacogenomic knowledge. It articulates different ontologies that represent complementary sub-domains of pharmacogenomics, i.e. related to genotype, phenotype, drugs, and clinical trials. SO-Pharm enables the representation of pharmacogenomic relationships between a drug, a genomic variation and a phenotype trait. In addition, it enables the representation of a patient and more largely a panel included in trials, and populations. SO-Pharm enables the representation of measured items on patients such as results from the observation of a phenotype trait or of genomic variations. SO-Pharm supports knowledge about pharmacogenomic hypothesis, case study, and investigations in pharmacogenomics. SO-Pharm is designed to facilitate data integration and knowledge discovery in pharmacogenomics. In addition it provides a consistent articulation of ontologies of pharmacogenomic sub-domains.

Proper citation: Suggested Ontology for Pharmacogenomics (RRID:SCR_003497) Copy   

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http://code.google.com/p/popoolation/

A collection of tools to facilitate population genetic studies of next generation sequencing data from pooled individuals. It builds upon open source tools (bwa, samtools) and uses standard file formats (gtf, sam, pileup) to ensure a wide compatibility. PoPoolation allows to calculate Tajima's Pi, Watterson's Theta and Tajima's D for reference sequences using a sliding window approach. Alternatively these population genetic estimators may be calculated for a set of genes (provided as gtf). One of the main challenges in population genomics is to identify regions of intererest on a genome wide scale. PoPoolation will greatly aid this task by allowing a fast and user friendly analysis of NGS data from DNA pools.

Proper citation: PoPoolation (RRID:SCR_003495) Copy   

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http://theswo.sourceforge.net

An ontology for describing software tools, their types, tasks, versions, provenance and data associated (the input and output data types and the uses the software can be put to).

Proper citation: Software Ontology (RRID:SCR_003493) Copy   

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http://www.humanvariomeproject.org/

Project facilitating the establishment and maintenance of standards systems and infrastructure for the worldwide collection and sharing of all genetic variations effecting human disease. The Human Variome Project produces two categories of recommendations: HVP Standards and HVP Guidelines. HVP Standards are those systems, procedures and technologies that the Human Variome Project Consortium has determined should be used by the community. These carry more weight than the less prescriptive HVP Guidelines, which cover those systems, procedures and technologies that the Human Variome Project Consortium has determined would be beneficial for the community to adopt. HVP Standards and Guidelines are central to supporting the work of the Human Variome Project Consortium and cover a wide range of fields and disciplines, from ethics to nomenclature, data transfer protocols to collection protocols from clinics. They can be thought of as both technical manuals and scientific documents, and while the impact of HVP Standards and Guidelines differ, they are both generated in a similar fashion. A document has been generated both as a guide for those collecting and distributing data and for those developing policy. Items should include those generated by HGVS/HVP collaborators as well as those generated by groups of individual Societies and Standards bodies in all relevant fields worldwide.

Proper citation: Human Variome Project (RRID:SCR_003492) Copy   

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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   

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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   

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http://www.msm.edu/Research/research_centersandinstitutes/NI/

The mission of the Morehouse School of Medicine Neuroscience Institute (MSMNI) is to create a supportive and challenging environment for the investigation and teaching of the functional organization of the nervous system, and to seek ways to reduce suffering brought about by neurological disorders. Members of the MSM NI are involved in teaching graduate students, medical students, and health care professionals about researching and treating medical conditions that are caused by or are rooted in the central nervous system. Additionally, MSM NI offers an 8-week Summer Research Program to qualified undergraduate, post-baccalaureate and first-year medical school students. Funding and administrative support were secured from the National Institutes of Health Office on Research for Minority Health and the National Institute for Neurological Disorders and Stroke (NINDS), respectively. The Neuroscience Institute is composed of selected faculty members from the Department of Neurobiology and the Department of Pharmacology at Morehouse School of Medicine who are conducting grant supported research. MSMNI research areas cover a broad range of cellular and molecular neuroscience and include the molecular biology and physiology of circadian rhythm, mechanisms of sleep and sleep disorders, mechanisms of stroke and stroke prevention, photoreceptor and retinal physiology, glutamate receptor physiology and mechanisms of hyperexcitability in epilepsy. Investigators use a variety of experimental preparations including whole animals, the intact portions of the central nervous system, and simplified preparations, such as tissue slices and single cells, to study cellular activities and cell-cell communication under more controlled conditions.

Proper citation: Morehouse School of Medicine Neuroscience Institute (RRID:SCR_003484) Copy   

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https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) Copy   

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http://www.phmtox.msu.edu/

At the Department of Pharmacology & Toxicology at Michigan State University, we combine integrative research, active learning and intellectual enrichment to prepare the student for advancement and leadership in their chosen field. The Department provides courses for undergraduate students, graduate students, medical students of the allopathic, osteopathic and veterinary colleges, and nursing students. In addition, specialized courses of study are offered in areas of professional development and life-long learning. From molecular and cellular levels to organ systems and whole animal models, our graduate and undergraduate programs encompass multiple areas of study, empowering students to challenge the boundaries of knowledge and chart their own unique path in the biomedical sciences. The disciplines of pharmacology and toxicology play a momentous role in human health today, and their applications in the professional world are vast. The department offers: * Pharmacology & Toxicology Graduate Doctoral Program * Online MS Programs ** Online Professional Science Masters in Integrative Pharmacology ** Online Masters in Pharmacology * Undergraduate Courses in Pharmacology & Toxicology * Dual Major Graduate Program in Toxicology (joint Pharmacology & Toxicology/Environmental Toxicology graduate program) * NIGMS Integrative and Organ Systems Pharmacology Short Course * Summer Undergraduate Research Fellowships

Proper citation: Michigan State University, Department of Pharmacology and Toxicology (RRID:SCR_003483) Copy   

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http://www.i2b2cictr.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 08, 2013. A two year Clinical and Translational Science Award (CTSA) supplement that set up a SHRINE (Shared Health Research Informatics NEtwork) network to create an information exchange environment that successfully shared 4.2M deidentified patient records. The network successfully linked i2b2 sites at UW, UCSF, UC Davis and Harvard Catalyst. Recombinant Data Corporation was actively involved in this implementation. This is a collaborative information exchange pilot project to adapt and extend data discovery tools and processes to enhance research design and retrospective data study capabilities for clinical translational investigators. The novel approach of this project will be to incrementally build a common technical, semantic and appropriately secure and governed distributed system in close partnership with active researchers at three large and geographically distributed academic medical centers. This collaboration will extend the Informatics for Integrating Biology and the Bedside (i2b2) software architecture developed by the Harvard based National Center for Biomedical Computing (NCBC) to support multi-institution data query capabilities. The anticipated outcome of this two-year project is to make high-level anonymized descriptive characteristics of population-level data discoverable for research design, hypothesis generation and retrospective data studies.

Proper citation: i2b2 Cross-Institutional Clinical Translational Research project (RRID:SCR_003367) Copy   

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http://biomodels.net/kisao/

An ontology that classifies algorithms available for the simulation of models in biology, their characteristics and the parameters required for their use.

Proper citation: Kinetic Simulation Algorithm Ontology (RRID:SCR_003361) Copy   

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http://www.c2b2.columbia.edu/danapeerlab/html/jistic.html

Software tool for analyzing datasets of genome-wide copy number variation to identify driver aberrations in cancer.

Proper citation: JISTIC (RRID:SCR_003482) Copy   

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http://braintrap.inf.ed.ac.uk/braintrap/

This database contains information on protein expression in the Drosophila melanogaster brain. It consists of a collection of 3D confocal datasets taken from EYFP expressing protein trap Drosophila lines from the Cambridge Protein Trap project. Currently there are 884 brain scans from 535 protein trap lines in the database. Drosophila protein trap strains were generated by the St Johnston Lab and the Russell Lab at the University of Cambridge, UK. The piggyBac insertion method was used to insert constructs containing splice acceptor and donor sites, StrepII and FLAG affinity purification tags, and an EYFP exon (Venus). Brain images were acquired by Seymour Knowles-Barley, in the Armstrong Lab at the University of Edinburgh. Whole brain mounts were imaged by confocal microscopy, with a background immunohistochemical label added to aid the identification of brain structures. Additional immunohistochemical labeling of the EYFP protein using an anti-GFP antibody was also used in most cases. The trapped protein signal (EYFP / anti-GFP), background signal (NC82 label), and the merged signal can be viewed on the website by using the corresponding channel buttons. In all images the trapped protein / EYFP signal appears green and the background / NC82 channel appears magenta. Original .lsm image files are also available for download.

Proper citation: BrainTrap: Fly Brain Protein Trap Database (RRID:SCR_003398) Copy   

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http://www.stritch.luc.edu/neuroscience/

The Neuroscience Graduate Program at Loyola trains students to become the neuroscientists who will carry on exciting research. Since our program is interdepartmental and interdisciplinary, our students have an exceptionally broad choice of advisors and research topics on which to work. The neuroscience program offers a Ph.D., M.D./Ph.D., and Masters degree. Our students begin working towards their doctorate in neuroscience by first obtaining a broad base of knowledge in the whole field of neuroscience--brain anatomy, physiology, biochemistry, and pharmacology. After selecting a research advisor at the end of the first year, students usually take several electives in the advisor's home department to develop specialization and strength in one particular area. Each student is exposed to various situations where he or she learns how to express their ideas effectively, whether at a graduate seminar or as a teaching assistant in the medical neuroscience course. Throughout their training, students have the opportunity to interact and work closely with faculty and to receive individualized attention that continues until degree completion.

Proper citation: Loyola University Chicago, Neuroscience (RRID:SCR_003399) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/pvca.html

Software package that contains the function to assess the batch sourcs by fitting all sources as random effects including two-way interaction terms in the Mixed Model (depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book Batch Effects and Noise in Microarray Experiements, chapter 12.

Proper citation: PVCA (RRID:SCR_001356) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/metaArray.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package for data transformation for meta-analysis of microarray Data: Transformation of gene expression data to signed probability scale (MCMC/EM methods) and combined differential expression on raw scale: Weighted Z-score after stabilizing mean-variance relation within platform.

Proper citation: metaArray (RRID:SCR_001353) Copy   

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http://library.med.utah.edu/kw/hyperbrain/

An online tutorial for human neuroanatomy designed as a supplement to textbook and class learning or as a lab substitute when human specimens, slides and models are not available. HyperBrain includes thousand of images and hundreds of linked illustrated glossary terms, as well as movies, quizzes and interactive animations. Last updated 2012.

Proper citation: HyperBrain (RRID:SCR_001595) Copy   

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http://www.pd-doc.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on December 02, 2011. Notice: This domain name expired on 10/29/11 and is pending renewal or deletion PD-DOC is a portal and a database resource, hosting a database and linking to other databases and data sets of clinical and translational data. PD-DOC functions to organize and facilitate clinical and translational research in Parkinson's disease. The PD-DOC Database contains standardized data collected by user institutions on large numbers of patients with Parkinsons disease and other parkinsonian disorders. In some cases, data is obtained at a single point in time, while in others data is collected repeatedly over time. The PD-DOC Database is composed of the Core Data Set (CDS) which consists of those variables required to be gathered for each subject whose data is entered into the PD-DOC database. In 2005, working groups of Udall Center and invited experts deliberated to establish the components of each CDS section (e.g. General Clinical, Cognitive/Behavioral, Postmortem Brain Neuropathological Findings). The PD-DOC CDS was established and designed to optimize data analyses and data mining for large numbers of subjects participating in a variety of research studies. In most cases corresponding DNA samples are available form the NINDS Human Genetic Repository (at Coriell). Much of the website is publicly available for viewing. To request access to sections of the website dealing with downloading or requesting data, requesting a consultation, or submitting data or other information you will need to register. Before registering, you should read the PD-DOC Policies. Note that PD-DOC data can be used for research purposes only. Once your registration is successfully completed you will be automatically logged into the website.

Proper citation: PD-DOC (RRID:SCR_001596) Copy   

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https://dpcpsi.nih.gov/onr/nrcc

Coordinates nutritional sciences-related research and research training across the National Institutes of Health (NIH) and among Federal Agencies by providing mechanisms to communicate research, research training, policy, and education initiatives. The DNRC facilitates the exchange of information, coordinates workshops and seminars on critical issues, encourages national and international research collaborations, and serves as the NIH primary point of contact for the Department of Health and Human Services (DHHS) and other agencies, departments, and organizations in matters pertaining to nutritional sciences and physical activity. Through its dedicated efforts to promote scientific policy reviews, innovative research, interagency collaboration, and technical advancements, the DNRC strives to define the increasing roles of nutritional sciences and physical activity in health promotion and disease prevention and treatment.

Proper citation: NIH Division of Nutrition Research Coordination (RRID:SCR_001469) Copy   

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