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http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry

http://www.phenologs.org/

Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided.

Proper citation: Phenologs (RRID:SCR_005529) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/physiobank/database/gaitpdb/

Database that contains measures of gait from 93 patients with idiopathic PD (mean age: 66.3 years; 63% men), and 73 healthy controls (mean age: 66.3 years; 55% men). The database includes the vertical ground reaction force records of subjects as they walked at their usual, self-selected pace for approximately 2 minutes on level ground. Underneath each foot were 8 sensors (Ultraflex Computer Dyno Graphy, Infotronic Inc.) that measure force (in Newtons) as a function of time. The output of each of these 16 sensors has been digitized and recorded at 100 samples per second, and the records also include two signals that reflect the sum of the 8 sensor outputs for each foot. This database also includes demographic information, measures of disease severity (i.e., using the Hoehn & Yahr staging and/or the Unified Parkinson's Disease Rating Scale) and other related measures (available in HTML or xls spreadsheet format). A subset of the database includes measures recorded as subjects performed a second task (serial 7 subtractions) while walking, which shows excerpts of swing time series from a patient with PD and a control subject, under usual walking conditions and when performing serial 7 subtractions. Under usual walking conditions, variability is larger in the patient with PD (Coefficient of Variation = 2.7%), compared to the control subject (CV = 1.3%). Variability increases during dual tasking in the subject with PD (CV = 6.5%), but not in the control subject (CV = 1.2%).

Proper citation: Gait in Parkinson's Disease (RRID:SCR_006891) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/dbSTS/

THIS RESOURCE IS NO LONGER IN SERVICE, as of October 1, 2013; however, the site is still accessible. NCBI resource that contains sequence and mapping data on short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. The dbSTS database offers a route for submission of STS sequences to GenBank. It is designed especially for the submission of large batches of STS sequences.

Proper citation: dbSTS (RRID:SCR_000400) Copy   

•   Source: SciCrunch Registry

http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

•   Source: SciCrunch Registry

http://mistdb.com

Database which contains the signal transduction proteins for complete and draft bacterial and archaeal genomes. The MiST2 database identifies and catalogs the repertoire of signal transduction proteins in microbial genomes.

Proper citation: MiST - Microbial Signal Transduction database (RRID:SCR_003166) Copy   

•   Source: SciCrunch Registry

http://www.sfn.org/SiteObjects/published/0000BDF20016F63800FD712C30FA42DD/1304F8BE908CE526359306C138737F9F/file/NRF%20Contacts.pdf

This resource provides a list of federal program officials in the neurosciences. An informal compendium of names and contact information for nearly 300 research grant and scientific review administrators in 21 organizational units.

Proper citation: NRF Contacts (RRID:SCR_001473) 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

http://www.zebrafinch.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Project to advance understanding of the neural mechanisms of vocal learning by providing a quantitative description of the relationship between physiological variables and vocal performance over the course of development in a songbird, the zebra finch. They propose to study vocal learning dynamically across neuronal and peripheral subsystems, using a novel collaborative approach that will harness the combined expertise of several investigators. Their proposed research model will 1) provide simultaneous measurements of acoustic, articulatory and electrophysiological data that will document the detailed dynamics of the vocal imitation process in a standardized learning paradigm; and 2) incorporate these measurements into a theoretical/computational framework that simultaneously provides a phenomenological description and attempts to elucidate the mechanistic basis of the learning process.

Proper citation: Zebra Finch Song Learning Consortium (RRID:SCR_006356) Copy   

•   Source: SciCrunch Registry

http://www.asn-online.org/

Society leading the fight against kidney disease by educating health professionals, sharing new knowledge, advancing research, and advocating the highest quality care for patients. To accomplish its mission, ASN will: # Educate health professionals by increasing the value of ASN education. # Share new knowledge by improving the quality and expanding the reach of ASN''s communications, including maintaining the premier publications in kidney disease. # Promote the highest quality care by serving as the professional organization informing health policy in kidney disease. # Advance patient care and research in kidney disease by strengthening the pipeline of clinicians, researchers, and educators. To accomplish this goal, ASN will: ## Implement a strategy to increase interest in nephrology careers, which includes promoting diversity within the nephrology workforce. ## Help fund travel to ASN educational activities for physicians and researchers training in the field of kidney disease. ## Use the ASN Grants Program to support outstanding research and foster career development. # Continue to bolster the ASN infrastructure, which includes: ## Increasing diversityincluding age and experience, ethnicity, and genderat all levels of the society. ## Providing avenues for helping ASN members facilitate professional exchange. ## Expanding ASN membership. ## Increasing the ASN Council-Designated Endowment Fund (independent of operational budget) to support grants and other priorities

Proper citation: ASN - American Society of Nephrology (RRID:SCR_006709) Copy   

•   Source: SciCrunch Registry

https://www.mousephenotype.org/imits/

This resource has been replaced by GenTaR. Software tool for the planning of all IMPC mouse production. Allows IMPC production centers to record the progress of mouse production, cre-excision and to summarise the progress of phenotype data collection and transfer to the IMPC DCC. Stores all the mutation molecular structures made for the IKMC, catalogs of all IKMC products.

Proper citation: iMITS (RRID:SCR_016552) Copy   

•   Source: SciCrunch Registry

https://www.portal.brain-bican.org/

Provides molecular and anatomical foundational framework for study of brain function and disorders.Comprehensive Center on Human and Non-Human Primate Brain Cell Atlases with goal to build reference brain cell atlases that will be used throughout research community.

Proper citation: BRAIN Initiative Cell Atlas Network (RRID:SCR_022794) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. A controlled terminology of resources, which is used to improve the sensitivity and specificity of web searches. It includes ''resource_type'', ''area of research'', and ''activity''. It is under development by a number of NIH-funded researchers who have a combined interest in classification of biomedical resources. The biositemaps site is no longer available but the biomedical resource ontology is still available via bioportal Biomedical Resource Ontology (BRO).

Proper citation: Biomedical Resource Ontology (RRID:SCR_004443) Copy   

•   Source: SciCrunch Registry

http://www.proconsortium.org/pro/

An ontological representation of protein-related entities by explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. The ontology has a meta-structure encompassing three areas: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp). NOTICE: The PRO ID format has changed from PRO: to PR: (e.g. PRO:000000563 is now PR:000000563).

Proper citation: PR (RRID:SCR_004964) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pmc/about/pubreader/

A web application which serves as an alternate way to read scientific literature in PubMed Central and Bookshelf. PubReader features an easy-to-read multi-column display, a figure strip for access to figures, and a search function. It is designed especially to support reading on tablets and other smaller devices but is available for reading on laptops and desktops.

Proper citation: PubReader (RRID:SCR_013814) Copy   

•   Source: SciCrunch Registry

https://nemar.org

Portal for human electrophysiological data, supports, sharing and in depth analysis of identified human neuroelectromagnetic brain data including scalp EEG, its magnetic counterpart, MEG, and, intracranial iEEG and ECoG. Open access EEG and MEG data archives, analysis, and visualization. Neuroelectromagnetic data, tools, and compute resource.

Proper citation: NEMAR (RRID:SCR_019100) Copy   

•   Source: SciCrunch Registry

https://run.biosimulations.org

Web tool for executing broad range of modeling studies and visualizing their results. Provides web interface for reusing any model. Models, simulations, and visualizations are available under licenses specified for each resource.

Proper citation: runBioSimulations (RRID:SCR_019110) Copy   

•   Source: SciCrunch Registry

http://dunham.gs.washington.edu/protocols.shtml

A portal for Maitreya Dunham's lab, which works on the genomic analysis of experimental evolution in yeast using microarrays and the chemostat. Research interests of the lab include experimental evolution of genetic networks in yeast, aneuploidy and copy number variation, comparative genomics, technology development and human genetics in yeast.

Proper citation: Maitreya Dunham's Lab (RRID:SCR_000784) Copy   

•   Source: SciCrunch Registry