Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://edwardslab.bmcb.georgetown.edu/
The Edwards lab conducts research in various aspects of computational biology and bioinformatics, particularly proteomics and mass spectrometry informatics and DNA and protein based signatures for pathogen detection. Some tools provided by Edwards Lab are the PepArML Meta-Search Engine, PeptideMapper Web-Service, Peptide Sequence Databases, Rapid Microorganism Identification Database (RMIDb), and GlycoPeptideSearch. Our primary area of research is the analysis of mass spectrometry experiments for proteomics. Proteomics, the qualitative and quantitative analysis of the expressed proteins of a cell, makes it possible to detect and compare the protein abundance profiles of different samples. Proteins observed to be under or over expressed in disease samples can lead to diagnostic markers or drug targets. The observation of mutated or alternatively spliced protein isoforms may provide domain experts with clues to the mechanisms by which a disease operates. The detection of proteins by mass spectrometry can even signal the presence of airborne microorganisms, such as anthrax, in the detect-to-protect time-frame. Recent research has focused on the discovery of novel peptides in proteomics datasets, improving the sensitivity and specificity of peptide identification using spectral matching with hidden Markov models, and unsupervised machine-learning based peptide identification result combining. Outside of proteomics, we work on computational tools for the design of highly specific oligonucleotides useful for pathogen signatures and PCR assay design. Recent research has focused on precomputing all human oligos of length 20 that are unique up to 4 string edits; and all bacterial 20-mer oligos that are species specific up to 4 string edits.
Proper citation: Edwards Lab (RRID:SCR_008860) Copy
Exploratory Gene Association Networks (EGAN) is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, iHOP, Google, etc.). EGAN functions as a module for exploratory investigation of analysis results from multiple high-throughput assay technologies, including but not limited to: * Transcriptomics via expression microarrays or RNA-Seq * Genomics via SNP GWAS or array CGH * Proteomics via MS/MS peptide identifications * Epigenomics via DNA methylation, ChIP-on-Chip or ChIP-Seq * In-silico analysis of sequences or literature EGAN has been built using Cytoscape libraries for graph visualization and layout, and is comparable to DAVID, GSEA, Ingenuity IPA and Ariadne Pathway Studio. There are pre-collated EGAN networks available for human (Homo sapiens), mouse (Mus musculus), rat (Rattus norvegicus), chicken (Gallus gallus), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), nematode (Caenorhabditis elegans), mouse-ear cress (Arabidopsis thaliana), rice (Oryza sativa) and brewer's yeast (Saccharomyces cerevisiae). There is now an EGAN module available for GenePattern (human-only). Platform: Windows compatible, Mac OS X compatible, Linux compatible
Proper citation: EGAN: Exploratory Gene Association Networks (RRID:SCR_008856) Copy
A public database that enhances understanding of the effects of environmental chemicals on human health. Integrated GO data and a GO browser add functionality to CTD by allowing users to understand biological functions, processes and cellular locations that are the targets of chemical exposures. CTD includes curated data describing cross-species chemical–gene/protein interactions, chemical–disease and gene–disease associations to illuminate molecular mechanisms underlying variable susceptibility and environmentally influenced diseases. These data will also provide insights into complex chemical–gene and protein interaction networks.
Proper citation: Comparative Toxicogenomics Database (CTD) (RRID:SCR_006530) Copy
http://zebrafish.wi.mit.edu/rnai/
Community built zebrafish RNAi platform that contains plasmids, successfully targeted genes and shRNA sequences, and a forum for discussion. This is a true community platform with users who add data, modify entiries, request features and share using the discussion board.
Proper citation: Zebrafish RNAi Database (RRID:SCR_008965) Copy
http://zfin.org/zf_info/anatomy/dict/sum.html
A structured controlled vocabulary of the anatomy and development of the Zebrafish (Danio rerio). It includes a list of structures, organized hierarchically into an ontology, with descriptions of each structure. The current version is being written by a consortium of researchers, each serving as an expert for a particular set of anatomical structures. Additional anatomical information derived from the current literature is provided by the ZFIN curation group. Development of a complete and uniform anatomical ontology for the zebrafish is vital to the success of zebrafish science. The anatomical ontology is necessary for: * Effective data dissemination and informatics. * A reference framework. * Interoperability.
Proper citation: Zebrafish Anatomical Ontology (RRID:SCR_005887) Copy
PhenomeNet is a cross-species phenotype similarity network. It contains the experimentally observed phenotypes of multiple species as well as the phenotypes of human diseases. PhenomeNet provides a measure of phenotypic similarity between the phenotypes it contains. The latest release (from 22 June 2012) contains 124,730 complex phenotype nodes taken from the yeast, fish, worm, fly, rat, slime mold and mouse model organism databases as well as human disease phenotypes from OMIM and OrphaNet. The network is a complete graph in which edge weights represent the degree of phenotypic similarity. Phenotypic similarity can be used to identify and prioritize candidate disease genes, find genes participating in the same pathway and orthologous genes between species. To compute phenotypic similarity between two sets of phenotypes, we use a weighted Jaccard index. First, phenotype ontologies are used to infer all the implications of a phenotype observation using several phenotype ontologies. As a second step, the information content of each phenotype is computed and used as a weight in the Jaccard index. Phenotypic similarity is useful in several ways. Phenotypic similarity between a phenotype resulting from a genetic mutation and a disease can be used to suggest candidate genes for a disease. Phenotypic similarity can also identify genes in a same pathway or orthologous genes. PhenomeNet uses the axioms in multiple species-dependent phenotype ontologies to infer equivalent and related phenotypes across species. For this purpose, phenotype ontologies and phenotype annotations are integrated in a single ontology, and automated reasoning is used to infer equivalences. Specifically, for every phenotype, PhenomeNet infers the related mammalian phenotype and uses the Mammalian Phenotype Ontology for computing phenotypic similarity. Tools: * PhenomeBLAST - A tool for cross-species alignments of phenotypes * PhenomeDrug - method for drug-repurposing
Proper citation: phenomeNET (RRID:SCR_006165) Copy
https://github.com/ncguilbeault/BonZeb
Open source, modular software tools for high resolution zebrafish tracking and analysis.Software suite of Bonsai modules for specifically tracking and analyzing zebrafish movements and integrating these data with closed loop experiments.Can be used in open loop fashion for collecting, analyzing, and integrating data from multiple sources in real time, or from offline sources for batch processing of pre-recorded data.
Proper citation: BonZeb (RRID:SCR_021392) Copy
http://www.kaluefflab.com/znrc.html
A group of scientists who collaborate and promote zebrafish neuroscience research. The consortium has opportunities for networking, scholarly publications and zebrafish-related symposia and conferences. The consortium is a supporter of the Zebrafish Neurophenome Project (ZNP), an initiative for a database of zebrafish behavioral and physiological data in an online, open source format.
Proper citation: Zebrafish Neuroscience Research Consortium (RRID:SCR_000298) Copy
http://ccb.jhu.edu/software/glimmerhmm/
A gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM's GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).
Proper citation: GlimmerHMM (RRID:SCR_002654) Copy
http://www.stanford.edu/~rnusse/pathways/targets.html
A list of target genes of Wnt/beta-catenin signaling. Suggestions for additions are welcome. Direct targets are defined as those with Tcf binding sites and demonstrating that these sites are important.
Proper citation: Target genes of Wnt/beta-catenin signaling (RRID:SCR_007022) Copy
http://www.uniprot.org/program/Chordata
Data set of manually annotated chordata-specific proteins as well as those that are widely conserved. The program keeps existing human entries up-to-date and broadens the manual annotation to other vertebrate species, especially model organisms, including great apes, cow, mouse, rat, chicken, zebrafish, as well as Xenopus laevis and Xenopus tropicalis. A draft of the complete human proteome is available in UniProtKB/Swiss-Prot and one of the current priorities of the Chordata protein annotation program is to improve the quality of human sequences provided. To this aim, they are updating sequences which show discrepancies with those predicted from the genome sequence. Dubious isoforms, sequences based on experimental artifacts and protein products derived from erroneous gene model predictions are also revisited. This work is in part done in collaboration with the Hinxton Sequence Forum (HSF), which allows active exchange between UniProt, HAVANA, Ensembl and HGNC groups, as well as with RefSeq database. UniProt is a member of the Consensus CDS project and thye are in the process of reviewing their records to support convergence towards a standard set of protein annotation. They also continuously update human entries with functional annotation, including novel structural, post-translational modification, interaction and enzymatic activity data. In order to identify candidates for re-annotation, they use, among others, information extraction tools such as the STRING database. In addition, they regularly add new sequence variants and maintain disease information. Indeed, this annotation program includes the Variation Annotation Program, the goal of which is to annotate all known human genetic diseases and disease-linked protein variants, as well as neutral polymorphisms.
Proper citation: UniProt Chordata protein annotation program (RRID:SCR_007071) Copy
https://scicrunch.org/scicrunch/data/source/nlx_154697-8/search?q=*
A data set of connectivity statements from BAMS, CoCoMac, BrainMaps, Connectome Wiki, the Hippocampal-Parahippocampal Table of Temporal-Lobe.com, and Avian Brain Circuitry Database. The data set lists which brain sites connectivity is to and from, the organism connectivity is mapped in, and journal references.
Proper citation: Integrated Nervous System Connectivity (RRID:SCR_006391) Copy
http://www.sbpdiscovery.org/technology/sr/Pages/LaJolla_AnimalFacility.aspx
Animal facility that provides housing for specific pathogen free rodents, frogs, and zebrafish. The facility also has trained animal care technicians provide expertise in animal husbandry, transgenic and knockout mouse breeding colony maintenance and assistance with routine technical procedures.
Proper citation: Sanford Burnham Prebys Medical Discovery Institute Animal Facility (RRID:SCR_014849) Copy
Collection of revertible protein trap gene-breaking transposon (GBT) insertional mutants in zebrafish with active or cryopreserved lines from initially identified lines. Open to community-wide contributions including expression and functional annotation and represents world-wide central hub for information on how to obtain these lines from diverse members of International Zebrafish Protein Trap Consortium (IZPTC) and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information. Registration allows users to save their favorite lines for easy access, request lines from Mayo Clinic catalog, contribute to line annotation with appropriate credit, and puts them on optional mailing list for future zfishbook newletters and updates.
Proper citation: zfishbook (RRID:SCR_006896) Copy
http://www.dukekidneycenter.org/cores/animal-models-core
Core facility that provides access to a range of experimental models of kidney, heart and vascular diseases. It also provides comprehensive phenotyping services for kidney functions, blood pressure and other cardiovascular functions.
Proper citation: Duke O'Brien Center for Kidney Research Animal Models Core (RRID:SCR_015267) Copy
http://www.uab.edu/medicine/hrfdcc/cores/b
Core whose goals include Generation of New Animal and Cell Models of HRFDs, to establish In Vivo Biosensors to Study Signaling Pathways Involved in HRFD Ciliopathies, and to generate and distribute HRFD Related Biologicals to the Center?s Investigator Base.
Proper citation: UAB Hepatorenal Fibrocystic Diseases Core Center Engineered Models Resource (RRID:SCR_015310) Copy
http://www.mayo.edu/research/centers-programs/model-systems-core/overview
Core that makes available PKD model systems and technologies to PKD researchers at Mayo and at other institutions. Its services include C. elegans PKD-targeted services, Zebrafish PKD-targeted services, and Rodent PKD-targeted services.
Proper citation: Translational Polycystic Kidney Disease (PKD) Center at Mayo Clinic Rochester Model Systems Core (RRID:SCR_015312) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the dkNET Resources search. From here you can search through a compilation of resources used by dkNET and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that dkNET has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on dkNET then you can log in from here to get additional features in dkNET such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within dkNET that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.