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http://niftilib.sourceforge.net

Niftilib is a set of i/o libraries for reading and writing files in the nifti-1 data format. nifti-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. Niftilib currently has C, Java, MATLAB, and Python libraries; we plan to add some MATLAB/mex interfaces to the C library in the not too distant future. Niftilib has been developed by members of the NIFTI DFWG and volunteers in the neuroimaging community and serves as a reference implementation of the nifti-1 file format. In addition to being a reference implementation, we hope it is also a useful i/o library. Niftilib code is released into the public domain, developers are encouraged to incorporate niftilib code into their applications, and, to contribute changes and enhancements to niftilib. Please contact us if you would like to contribute additonal functionality to the i/o library.

Proper citation: Niftilib (RRID:SCR_003355) Copy   

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http://www.etsu.edu/com/pharmacology/default.aspx

Faculty members of our Department are actively engaged in delivering outstanding teaching to undergraduate students, graduate students, medical students, and residents. Our Doctor of Philosophy (graduate) students matriculate to Pharmacology through the Biomedical Sciences Graduate Program at the Quillen College of Medicine. Students pursuing Master of Science and Doctor of Philosophy degrees may pursue a focus in Toxicology. Our faculty members are trained in several medical disciplines and our research applies methodological approaches that span molecular biology, cellular biology, systems biology, and human biology and pathology. Through research, our department strives to understand human disease pathology and use this understanding to develop new therapeutic entities (e.g. drugs) for the treatment of major human diseases. The primary foci of department research efforts are cardiovascular and neuropsychiatric diseases, although other areas of interest and activity exist. Our laboratories are funded by the National Institutes of Health, American Heart Association, the American Foundation for Suicide Prevention and a variety of other agencies and sources.

Proper citation: East Tennessee State University, Department of Pharmacology (RRID:SCR_003350) Copy   

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http://bejerano.stanford.edu/phenotree/

Web server to search for genes involved in given phenotypic difference between mammalian species. The mouse-referenced multiple alignment data files used to perform the forward genomics screen is also available. The webserver implements one strategy of a Forward Genomics approach aiming at matching phenotype to genotype. Forward genomics matches a given pattern of phenotypic differences between species to genomic differences using a genome-wide screen. In the implementation, the divergence of the coding region of genes in mammals is measured. Given an ancestral phenotypic trait that is lost in independent mammalian lineages, it is shown that searching for genes that are more diverged in all trait-loss species can discover genes that are involved in the given phenotype.

Proper citation: Phenotree (RRID:SCR_003591) Copy   

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https://services.healthtech.dtu.dk/

Center for Biological Sequence Analysis of the Technical University of Denmark conducts basic research in the field of bioinformatics and systems biology and directs its research primarily towards topics related to the elucidation of the functional aspects of complex biological mechanisms. A large number of computational methods have been produced, which are offered to others via WWW servers. Several data sets are also available. The center also has experimental efforts in gene expression analysis using DNA chips and data generation in relation to the physical and structural properties of DNA. The on-line prediction services at CBS are available as interactive input forms. Most of the servers are also available as stand-alone software packages with the same functionality. In addition, for some servers, programmatic access is provided in the form of SOAP-based Web Services. The center also educates engineering students in biotechnology and systems biology and offers a wide range of courses in bioinformatics, systems biology, human health, microbiology and nutrigenomics.

Proper citation: DTU Center for Biological Sequence Analysis (RRID:SCR_003590) Copy   

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http://wiki.cns.org

Wiki dedicated to neurosurgical topics, maintained by the Congress of Neurological Surgeons. Members can log in to contribute by adding or editing an article. A wiki is a collaborative technology for organizing information. Visitors can add, remove, and edit content. Like all other wikis, the CNS University's NeuroWiki allows linking among any number of pages. This ease of interaction and operation will engender collaborative authoring.

Proper citation: CNS NeuroWIki (RRID:SCR_003500) Copy   

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http://unp.aas.duke.edu//

The major and minor in Neuroscience at Duke University was approved by the Arts and Sciences Council of Trinity College of Arts and Sciences on April 9, 2009. The program offers three academic plans: Bachelor of Science (B.S.) degree in Neuroscience, Bachelor of Arts (A.B.) degree in Neuroscience, and a Minor in Neuroscience. Although Neuroscience is a new major/minor, there is a rich and long-standing tradition of excellence in undergraduate neuroscience research and education at Duke. Groups of faculty in the Department of Psychology and Neuroscience and the Department of Biology, as well as the Department of Neurobiology in the Duke University School of Medicine, have been especially engaged in teaching neuroscience in undergraduate classes and hosting independent study projects in their research laboratories. Building upon this broad foundation, the new Undergraduate Studies in Neuroscience program is a truly interdisciplinary experience reflecting the diverse sources of knowledge that advance our understanding of the brain sciences. Undergraduate Studies in Neuroscience is a unique collaboration among many Departments and Schools , with administrative support provided by Trinity College of Arts and Sciences and the Duke Institute for Brain Sciences.

Proper citation: Duke University Trinity College of Arts and Sciences Undergraduate Neuroscience (RRID:SCR_003345) Copy   

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http://www.xpmutations.org

Interactive repository of mutations and other allelic variations of the genes involved in the DNA repair disorders, Xeroderma Pigmentosum (XP), Cockayne Syndrome (CS), Trichothiodystrophy (TTD), and other UV-sensitivity disorders. Any omitted data or new data may be submitted by using the on-line data submission form. There is a message board system to support discussions amongst those interested in XP and DNA Repair. RESOURCES * Educational module of the molecular biology of Nucleotide Excision Repair * Introduction to the DNA Repair disorders (XP, CS, TTD, UVs) * Background on each of the XP genes * A searchable database of mutations and sequence variations for the XP genes * Contact point for the submission of new mutation data * Discussion Forums and a Guest Book * Web Links to Additional Resources

Proper citation: Allelic Variations of The XP Genes (RRID:SCR_003376) Copy   

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http://sig.biostr.washington.edu/projects/fm/

A domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Its ontological framework can be applied and extended to all other species. The description of how the OWL version was generated is in Pushing the Envelope: Challenges in a Frame-Based Representation of Human Anatomy by N. F. Noy, J. L. Mejino, C. Rosse, M. A. Musen: http://bmir.stanford.edu/publications/view.php/pushing_the_envelope_challenges_in_a_frame_based_representation_of_human_anatomy The Foundational Model of Anatomy ontology has four interrelated components: # Anatomy taxonomy (At), # Anatomical Structural Abstraction (ASA), # Anatomical Transformation Abstraction (ATA), # Metaknowledge (Mk), The ontology contains approximately 75,000 classes and over 120,000 terms; over 2.1 million relationship instances from over 168 relationship types link the FMA's classes into a coherent symbolic model.

Proper citation: FMA (RRID:SCR_003379) Copy   

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http://www.etonbio.com/

An Antibody supplier

Proper citation: Eton Bioscience (RRID:SCR_003533) Copy   

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http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

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http://www.ebi.ac.uk/pride/

Centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. Originally it was developed to provide a common data exchange format and repository to support proteomics literature publications. This remit has grown with PRIDE, with the hope that PRIDE will provide a reference set of tissue-based identifications for use by the community. The future development of PRIDE has become closely linked to HUPO PSI. PRIDE encourages and welcomes direct user submissions of protein and peptide identification data to be published in peer-reviewed publications. Users may Browse public datasets, use PRIDE BioMart for custom queries, or download the data directly from the FTP site. PRIDE has been developed through a collaboration of the EMBL-EBI, Ghent University in Belgium, and the University of Manchester.

Proper citation: Proteomics Identifications (PRIDE) (RRID:SCR_003411) Copy   

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http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Main_Page

Laboratory portal, including software, web-based tools, databases and data sets, related to their research that focuses on the development and application of biophysical and bioinformatics methods aimed at understanding the structural and energetic origins of protein-protein, protein-nucleic acid, and protein-membrane interactions. Their work includes fundamental theoretical research, the development of software tools, and applications to problems of biological importance. In this regard they maintain an active collaborative computational and experimental research program on the molecular basis of cell-cell adhesion. Other problems of current interest include protein structure prediction, the organization of protein sequence/structure space, the prediction of protein function based on protein structure, the structural origins of specificity in protein-DNA interactions, RNA function and, more generally, the electrostatic properties of biological macromolecules.

Proper citation: Honig Lab (RRID:SCR_003410) Copy   

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https://www.marquette.edu/grad/programs-neuroscience.php

Neuroscience specialization in Graduate Program in Biological Sciences at Marquette University brings together researchers from Departments of Biological and Biomedical Sciences at Marquette to offer quality graduate education in the field of neuroscience with the goal of training students for careers as neuroscience researchers and educators. The specialization is for students who wish to pursue a Ph.D. degree. The collaborative and multi-disciplinary neuroscience research environment at Marquette is supported by the Integrative Neuroscience Research Center (INRC), a consortium of researchers committed to advancing neuroscience research and education at Marquette. The Neuroscience Graduate Program offers the opportunity to conduct research in a collaborative, intellectually rigorous environment, with access to the most modern research tools.

Proper citation: Marquette University, Neuroscience (RRID:SCR_003404) Copy   

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http://en.wikibooks.org/wiki/Human_Physiology

Human Physiology is a featured book on Wikibooks because it contains substantial content, it is well-formatted, and the Wikibooks community has decided to feature it on the main page or in other places. Please continue to improve it and thanks for the great work so far! A printable and PDF version are available. You can edit its advertisement template. Contents: 1. Homeostasis 2. Cell Physiology 3. Integumentary System 4. The Nervous System 5. Senses 6. The Muscular System 7. Blood Physiology 8. The Cardiovascular System 9. The Immune System 10. The Urinary System 11. The Respiratory System 12. The Gastrointestinal System 13. Nutrition 14. The Endocrine System 15. The Male Reproductive System 16. The Female Reproductive System 17. Pregnancy and Birth 18. Genetics and Inheritance 19. Development: Birth through Death 20. Appendix 1: Answers to Review Questions 21. Authors 22. Further Reading

Proper citation: Human Physiology (RRID:SCR_003525) Copy   

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https://cabig.nci.nih.gov/tools/caTRIP

THIS RESOURCE IS NO LONGER IN SERVICE documented June 4, 2013. Allows users to query across a number of caBIG data services, join on common data elements (CDEs), and view results in a user-friendly interface. With an initial focus on enabling outcomes analysis, caTRIP allows clinicians to query across data from existing patients with similar characteristics to find treatments that were administered with success. In doing so, caTRIP can help inform treatment and improve patient care, as well as enable the searching of available tumor tissue, enable locating patients for clinical trials, and enable investigating the association between multiple predictors and their corresponding outcomes such as survival caTRIP relies on the vast array of open source caBIG applications, including: * Tumor Registry, a clinical system that is used to collect endpoint data * cancer Text Information Extraction System (caTIES), a locator of tissue resources that works via the extraction of clinical information from free text surgical pathology reports. while using controlled terminologies to populate caBIG-compliant data structures * caTissue CORE, a tissue bank repository tool for biospecimen inventory, tracking, and basic annotation * Cancer Annotation Engine (CAE), a system for storing and searching pathology annotations * caIntegrator, a tool for storing, querying, and analyzing translational data, including SNP data Requires Java installation and network connectivity.

Proper citation: caTRIP (RRID:SCR_003409) Copy   

•   Source: SciCrunch Registry

http://www.reactome.org

Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.

Proper citation: Reactome (RRID:SCR_003485) Copy   

•   Source: SciCrunch Registry

https://neuro.georgetown.edu

Faculty of the Department of Neuroscience participate in the teaching of courses in the Interdisciplinary Program in Neuroscience and the School of Medicine. A Ph.D. in Neuroscience is offered through the Interdisciplinary Program in Neuroscience. Support for graduate training is offered through the Department, the research grants of individual faculty, as well as through three NIH training grants directed by Neuroscience faculty. * Training in Recovery of Function after CNS Injury. Program Director: Barbara S. Bregman, Ph.D. * Training Program in Drug Abuse. Program Director: Barbara S. Bayer, Ph.D. * Training in Neural Injury and Plasticity. Program Director: Jean R. Wrathall, Ph.D. Scientists in the Department of Neuroscience participate in a wide array of research activities with a focus on understanding both the normal and injured nervous system. The theme of neuroplasticity characterizes much of the research in the Department. We study neuroplasticity during normal development and in the adult in response to activity (e.g., learning) or drugs. Our research is also focused on studying the plasticity that ensues after traumatic (such as spinal cord injury) or ischemic damage to the nervous system and over the course of developmental or neurodegenerative diseases (such as Specific Language Impairment, autism, or Parkinson's and Alzheimer's Diseases). The specific research interests of each of the principal investigators falls under four broad subheadings: *CNS disorders ( Faden, Mocchetti, Rebeck, Riesenhuber,Ullman) *Cognitive/Computational (Riesenhuber, Ullman) *Development, Regeneration and recovery of function after injury (Bregman, Faden, Kromer, Ullman, Wrathall) *Neuroimmunology and Drugs of Abuse (Bayer, Faden, Kromer, Mocchetti) Under this common theme, a variety of diverse techniques and models are employed by the faculty. They range from molecular studies of gene function to studies on humans using Event-Related Potentials (ERPs) and functional MRI. Experimental models include cell culture systems, rodent genetic and experimental models of nervous system injury and disorders, as well as the use of computer simulations to understand higher cortical processing.

Proper citation: Georgetown, Neuroscience (RRID:SCR_003363) Copy   

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http://neuro.med.harvard.edu/

The mission of the Department of Neurobiology is to promote research and teaching that leads to a better understanding of the normal and diseased brain. The Department faculty are committed to training leaders of the next generation of neuroscientists, including graduate and medical students. Candidates for the Ph.D. in Neurobiology are admitted to the graduate Program in Neuroscience. This interdepartmental training program links the Department of Neurobiology with faculty in the Harvard affiliated hospitals and with faculty in other basic science departments. The Program, established in 1981, now includes about 90 investigators who participate in the training of Ph.D. candidates. Approximately fifteen students are accepted each year so that the steady state enrollment is usually about 80-90. This Program in Neuroscience attracts superb students with a broad range of interests from all areas of the globe. The goals of our training are to produce scientists who have explored one area and one level of analysis in great depth, but who are familiar with the full scope of neuroscience. They should be able to move from one level to another in a critical and creative manner. We also try to develop an appreciation for translational research that bears on human brain disease. The Department of Neurobiology, established in 1966 with Stephen W. Kuffler as Chair, was the first of its kind. The intent was to bring together members of traditional departments- physiologists, biochemists, and anatomists- in order to understand the principles governing communication between cells in the nervous system. This interdisciplinary approach was revolutionary at the time, and the interdisciplinary theme has continued to permeate the evolution of the field of neuroscience ever since. The Program in Neuroscience is one of four programs administered by the Division of Medical Sciences (DMS). DMS, located at the medical school, is a division of the Faculty of Arts and Sciences of Harvard University.

Proper citation: Harvard University Neurobiology (RRID:SCR_003368) Copy   

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http://mimi.ncibi.org/MimiWeb/main-page.jsp

MiMi Web gives you an easy to use interface to a rich NCIBI data repository for conducting your systems biology analyses. This repository includes the MiMI database, PubMed resources updated nightly, and text mined from biomedical research literature. The MiMI database comprehensively includes protein interaction information that has been integrated and merged from diverse protein interaction databases and other biological sources. With MiMI, you get one point of entry for querying, exploring, and analyzing all these data. MiMI provides access to the knowledge and data merged and integrated from numerous protein interactions databases and augments this information from many other biological sources. MiMI merges data from these sources with deep integration into its single database with one point of entry for querying, exploring, and analyzing all these data. MiMI allows you to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI displays results of your queries in easy-to-browse interfaces and provides you with workspaces to explore and analyze the results. Among these workspaces is an interactive network of protein-protein interactions displayed in Cytoscape and accessed through MiMI via a MiMI Cytoscape plug-in. MiMI gives you access to more information than you can get from any one protein interaction source such as: * Vetted data on genes, attributes, interactions, literature citations, compounds, and annotated text extracts through natural language processing (NLP) * Linkouts to integrated NCIBI tools to: analyze overrepresented MeSH terms for genes of interest, read additional NLP-mined text passages, and explore interactive graphics of networks of interactions * Linkouts to PubMed and NCIBI's MiSearch interface to PubMed for better relevance rankings * Querying by keywords, genes, lists or interactions * Provenance tracking * Quick views of missing information across databases. Data Sources include: BIND, BioGRID, CCSB at Harvard, cPath, DIP, GO (Gene Ontology), HPRD, IntAct, InterPro, IPI, KEGG, Max Delbreuck Center, MiBLAST, NCBI Gene, Organelle DB, OrthoMCL DB, PFam, ProtoNet, PubMed, PubMed NLP Mining, Reactome, MINT, and Finley Lab. The data integration service is supplied under the conditions of the original data sources and the specific terms of use for MiMI. Access to this website is provided free of charge. The MiMI data is queryable through a web services api. The MiMI data is available in PSI-MITAB Format. These files represent a subset of the data available in MiMI. Only UniProt and RefSeq identifiers are included for each interactor, pathways and metabolomics data is not included, and provenance is not included for each interaction. If you need access to the full MiMI dataset please send an email to mimi-help (at) umich.edu.

Proper citation: Michigan Molecular Interactions (RRID:SCR_003521) Copy   

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http://cng.gmu.edu:8080/Lm

A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.

Proper citation: L-Measure (RRID:SCR_003487) Copy   

•   Source: SciCrunch Registry