Tools   Select Another Resource Report Type

http://purl.bioontology.org/ontology/MMO

An ontology designed to represent the variety of methods used to make qualitative and quantitative clinical and phenotype measurements both in the clinic and with model organisms.

Proper citation: Measurement Method Ontology (RRID:SCR_003373) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.isr.syr.edu/

The Institute for Sensory Research (ISR) defines itself as a world class research center dedicated to the discovery and application of knowledge of the sensory systems. Integration of engineering, life, and physical sciences, combining rigorous experimental methodology with mathematical analysis is stressed. Our multidisciplinary approach to bioengineering, sensory neuroscience, graduate, and undergraduate education, makes ISR a unique academic research center. At ISR, we study sensory systems, our gateways to the world. Our ears, eyes, skin, and mouth are channels through which we experience sound, light, texture, etc. These are functions that we usually take for granted until problems arise. Engineers, scientists, and students at ISR investigate both the basic sensory principles used by the brain, and also how the sensory systems can be best utilized, modified, and repaired if necessary to better communicate with our surroundings and with one another. In addition to basic research in hearing, touch, vision, and oro-facial biomechanics, recent projects include the design and testing of sensory-aid devices such as cochlear implants, hearing aids, ear protectors, and tactile aids for the visually and hearing impaired. Additional projects involve visual-depth perception, chewing and swallowing, oto-acoustic emissions, and personal care products such as oral rinses and skin lotions. Research * Auditory * Somatosensory * Vision

Proper citation: Syracuse University; Institute for Sensory Research (RRID:SCR_003377) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.jobtarget.com/corp/

JobTarget is the foundation upon which careers and companies are built. Our technology and services connect millions of job seekers to hundreds of thousands of companies through thousands of job boards. We facilitate faster, more meaningful connections by powering niche job sites that target specific audiences of talent, and providing technology and advertising solutions for employers to more quickly and cost-effectively locate the most qualified candidates for their openings. Explore our Products & Services to experience the JobTarget difference or check out Who We Serve to narrow in on the best solutions to serve you.

Proper citation: JobTarget (RRID:SCR_003365) Copy   

•   Source: SciCrunch Registry

https://github.com/ggloor/ALDEx2

Software tool to examine compositional high-throughput sequence data with Welch's t-test. A differential relative count abundance analysis for the comparison of two conditions. For example, single-organism and meta-rna-seq high-throughput sequencing assays, or of selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, that has been optimized for three or more experimental replicates. Infers sampling variation and calculates the expected Benjamini-Hochberg false discovery rate given the biological and sampling variation using several parametric and non-parametric tests. Can to glm and Kruskal-Wallace tests on one-way ANOVA style designs.

Proper citation: ALDEx2 (RRID:SCR_003364) 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   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IDOMAL

An application ontology to cover all aspects of malaria (clinical, epidemiological, biological, etc) as well as the intervention attempts to control it, extending the infectious disease ontology (IDO).

Proper citation: Malaria Ontology (RRID:SCR_003369) Copy   

•   Source: SciCrunch Registry

http://www.ags.gov.ab.ca/

Portal of geological information, including geology maps, reports, and GIS datasets, to help with the exploration, development and conservation of Alberta's resources.

Proper citation: Alberta Geological Survey (RRID:SCR_003402) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/RCircos/

Software package that provides a simple and flexible way to generate Circos 2D track plot images for genomic data visualization. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics package that comes with R base installation.

Proper citation: RCircos (RRID:SCR_003310) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/primerdesigner/

High throughput PCR primer design software. Target regions defined through a rich set of descriptors, such as Ensembl accessions and arbitrary genomic coordinates, may be specified. Primer pairs are then selected computationally to produce a minimal amplicon set capable of tiling across the specified target regions. As part of the tiling process, primer pairs are computationally screened to meet the criteria for success with one of two PCR amplification protocols.

Proper citation: JCVI Primer Designer (RRID:SCR_003275) Copy   

•   Source: SciCrunch Registry

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

Software package providing an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. It requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The package implements a pipeline to collect, analyze and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.

Proper citation: ddCt (RRID:SCR_003396) Copy   

•   Source: SciCrunch Registry

http://www.elsevier.com/online-tools/pathway-studio/biological-database

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. MedScan is a fast and flexible biomedical information extraction technology. It uses dictionaries to identify individual biomedical terms (proteins, cellular processes, small molecules, diseases, etc) referred to in literature articles, and applies advanced natural language processing techniques to detect the relationships within the article and extract these terms and the relationships; the overall process of detection, identification, extraction and assembling, is termed Information Harvesting. Information extracted by MedScan represents the multiple aspects of protein function, including protein modification, cellular localization, protein-protein interactions, gene expression regulation, molecular transport and synthesis, as well as association with diseases, and regulation of various cellular processes. This scope can be broadened by modifying information extraction rules and the dictionaries. Dictionaries can be assembled on any topic or area that is represented in the literature you wish to harvest. High-throughput data generation methodologies like microarray gene expression require new approaches for gathering information for data analysis. For the best results, computational approaches used for high-throughput data analysis require that biological information from the literature be a coherent and integrated part of the analysis software itself. Pathway Studio meets this challenge through its MedScan Technology and underlying ResNet database. All editions of Pathway Studio contain MedScan Technology to harvest information from the literature and to save this information in the Pathway Studio ResNet database ready for data analysis. MedScan is more than a web search engine. Indeed, the output of a Google search can be channeled into MedScan for example. Web searches, like Google, are excellent at finding items as a result of a query. A quick look at the output list usually locates the item for which you are looking. This approach however, is not well suited for information and knowledge gathering. Also, once information is gathered, where do you put it for later computational use? MedScan meets this challenge for the area of biomedical literature and biomedical online information. PubMed meets the needs for a central repository of biomedical literature. Researchers can go to PubMed and search for any topic and articles of interest, much like a web type of search. However, just like a web type of search, PubMed also provides a list of all the hits with a link to the articles. If a single article, or even just a few, are sought, this search approach is useful. Alternatively, MedScan will list all the articles of interest but additionally scans the text for relationships, highlights these relationships in the articles and then lists these relationships and the biological molecules and processes involved in the relationships in separate tables. The tables of relationships can be viewed graphically in Pathway Studio and can be saved into the ResNet database for use in experimental data analysis.

Proper citation: MedScan (RRID:SCR_003314) Copy   

•   Source: SciCrunch Registry

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

An R package for extending the grammar of graphics for genomic data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

Proper citation: ggbio (RRID:SCR_003313) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/dranew/defuse

Software package for gene fusion discovery using RNA-Seq data. It uses clusters of discordant paired end alignments to inform a split read alignment analysis for finding fusion boundaries.

Proper citation: deFuse (RRID:SCR_003279) Copy   

•   Source: SciCrunch Registry

http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

•   Source: SciCrunch Registry

http://vano.cellexplorer.org/

VANO is a Volume image object AnNOtation System for 3D multicolor image stacks, developed by Hanchuan Peng, Fuhui Long, and Gene Myers. VANO provides a well-coordinated way to annotate hundreds or thousands of 3D image objects. It combines 3D views of images and spread sheet neatly, and is just easy to manage 3D segmented image objects. It also lets you incorporate your segmentation priors, and lets you edit your segmentation results! This system has been used in building the first digital nuclei atlases of C. elegans at the post-embryonic stage (joint work with Stuart Kim lab, Stanford Univ), the single-neuron level fruit fly neuronal atlas of late embryos (with Chris Doe lab, Univ of Oregon, HHMI), and the compartment-level of digital map(s) of adult fruit fly brains (several labs at Janelia Farm, HHMI). VANO is cross-platform software. Currently the downloadable versions are for Windows (XP and Vista) and Mac (Intel-chip based, Leopard or Tiger OS). If you need VANO for different systems (such as 64bit or 32bit, Redhat Linux, Ubuntu, etc), you can either compile the software, or send an email to pengh (at) janelia.hhmi.org. VANO is Open-Source. You can download both the source code files and pre-complied versions at the Software Downloads page.

Proper citation: Volume image object AnNOtation System (RRID:SCR_003393) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry