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https://edspace.american.edu/openbehavior/project/bonzeb/

Portal provides tools for investigating visuomotor integration specific to high speed kinematic tracking in small model organisms in closed loop experiments. University of Toronto scientists developed suite of Bonsai modules for specifically tracking and analyzing zebrafish movements and integrating these data with closed-loop experiments. BonZeb modules can also be used in an 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 project (RRID:SCR_021388) Copy   

•   Source: SciCrunch Registry

http://owlsim.org

Software package that provides the ability to do a number of standard semantic similarity methods and includes novel methods for combining these with dynamic selection of anonymous grouping classes. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OwlSim (RRID:SCR_006819) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/fishface/home

ishFace is an atlas of zebrafish craniofacial development. How do the elements of the craniofacial skeleton arise, grow, and reshape? Answers to this question are coming from both molecular-genetic and cell-biological approaches, which rely, first of all, on precise description of the developmental events and processes that comprise skeletogenesis. Zebrafish, with a sophisticated knowledge of its genetics and genomics, with favorable attributes for phenotypic analyses of development, and with patterns of development conserved among all vertebrates, provides a powerful animal model for learning about craniofacial development. In particular, with current transgenic approaches one can examine craniofacial skeletal elements in exquisite cellular detail during an extended period of development within living, intact embryos and larvae an investigative method unsurpassed in accuracy and sensitivity. We constructed this developmental atlas of the craniofacial skeleton, FishFace, to serve as a guide for such study. We hope that the FishFace Atlas will be particularly useful in comparative and mutational analyses where there is interest in understanding the cellular basis of early skeletogenesis. The heart of the FishFace Atlas uses high magnification (generally a 40x objective) confocal image stacks showing transgenically-labelled chondrocytes or osteoblasts, along with mineralized bone matrix, which is visualized by vital staining with Alizarin red. We present these stacks in sequences that follow particular individual cartilages and bones of the first two pharyngeal arches as they develop during embryonic and larval stages. To do so, we build on the foundation set out in the gold standard reference for describing comprehensively skeletal elements in the zebrafish craniofacial complex, Cubbage and Mabee (1996), which used fixed preparations stained for cartilage and bone through adult stages. The FishFace Atlas element development section adds considerable detail to arch one and two early development, particularly at the cellular level, but also in description of element growth and shaping. Other sections of the FishFace Atlas, at lower magnification, provide anatomical context for the element development section, including an interactive tool made by optical projection tomography (OPT) for learning the anatomy of the entire larval skull. Hence, the FishFace Atlas provides the community with an interactive resource with which the user can understand not only the cellular details, but also complex 3D anatomical relationships, of developing elements in the craniofacial skeleton of the zebrafish.

Proper citation: FishFace - An atlas of zebrafish craniofacial development (RRID:SCR_008894) Copy   

•   Source: SciCrunch Registry

http://www.zfscreens.com/

A commercial organization with expertise and multiple departments that focus on both fish physiology and molecular cell biology. ZF-pharma has developed patented technology for the automated in vivo high-throughput screening of pharmaceutical drug candidates against diseases. They seek industrial partners that are interested in obtaining a license for this technology or, alternatively, would prefer to outsource screening of TB drugs to ZF-pharma. NewCatch BV has developed a tool for use in sustainable aquaculture. The tool will first be used for reproduction of the highly valued fish species eel, pikeperch and sole. They seek industrial / aquaculture partners interested in obtaining a license for ZF-implants in other fish species. NewCatch BV carries out fish reproductive research, for instance European eel (Anguilla anguilla), exploring maturation and reproduction. ZF-Genomics offers multiple sequencing services, including mRNAseq and microRNA analysis and de novo and reference genome assemblies. In addition they also offer the bioinformatics services that are needed to make sense of the sequence data. In addition, they perform Next generation sequencing tasks for (inter)national research project partners and for external customers.

Proper citation: ZF-screens (RRID:SCR_003910) Copy   

•   Source: SciCrunch Registry

http://genetrail.bioinf.uni-sb.de/

A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneTrail (RRID:SCR_006250) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

http://polya.umdnj.edu/

A database of mRNA polyadenylation sites. PolyA_DB version 1 contains human and mouse poly(A) sites that are mapped by cDNA/EST sequences. PolyA_DB version 2 contains poly(A) sites in human, mouse, rat, chicken and zebrafish that are mapped by cDNA/EST and Trace sequences. Sequence alignments between orthologous sites are available. PolyA_SVM predicts poly(A) sites using 15 cis elements identified for human poly(A) sites.

Proper citation: PolyA DB (RRID:SCR_007867) Copy   

•   Source: SciCrunch Registry

http://www.chibi.ubc.ca/Gemma

Resource for reuse, sharing and meta-analysis of expression profiling data. Database and set of tools for meta analysis, reuse and sharing of genomics data. Targeted at analysis of gene expression profiles. Users can search, access and visualize coexpression and differential expression results.

Proper citation: Gemma (RRID:SCR_008007) Copy   

•   Source: SciCrunch Registry

http://phenomebrowser.net/

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   

•   Source: SciCrunch Registry

http://ctdbase.org/

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   

•   Source: SciCrunch Registry

http://www.webgestalt.org/

Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.

Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://akt.ucsf.edu/EGAN/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://genenet2.uthsc.edu/geneinfoviz/search.php

GeneInfoViz is a web based tool for batch retrieval of gene function information, visualization of GO structure and construction of gene relation networks. It takes a input list of genes in the form of LocusLink ID, UniGeneID, gene symbol, or accession number and returns their functional genomic information. Based on the GO annotations of the given genes, GeneInfoViz allows users to visualize these genes in the DAG structure of GO, and construct a gene relation network at a selected level of the DAG. Platform: Online tool

Proper citation: GeneInfoViz (RRID:SCR_005680) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://neuromorpho.org/index.jsp

Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.

Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy   

•   Source: SciCrunch Registry

http://zebra.sc.edu/index.html

A portal to different zebrafish resources such as jobs, book, journals, database, meetings, and K-12 programs. Most information leads to ZFIN: The Zebrafish Model Organism Database.

Proper citation: Zebrafish Information Server (RRID:SCR_002237) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://zebrafishucl.org/zebrafishbrain#about-1

Collates and curates neuroanatomical data and information generated both in-house and by community to communicate current state of knowledge about neuroanatomical structures in developing zebrafish. Most of data come from high resolution confocal imaging of intact brains in which neuroanatomical structures are labelled by combinations of transgenes and antibodies. Community repository for image based data related to neuroanatomy of zebrafish.

Proper citation: Zebrafish Brain Atlas (RRID:SCR_000606) Copy   

•   Source: SciCrunch Registry