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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 It reports published and unpublished data on human mitochondrial DNA variation.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://avis.princeton.edu/pixie/index.php

bioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).

Proper citation: bioPIXIE (RRID:SCR_004182) Copy   

•   Source: SciCrunch Registry

http://solgenomics.net/

A clade oriented, community curated database containing genomic, genetic, phenotypic and taxonomic information for plant genomes. Genomic information is presented in a comparative format and tied to important plant model species such as Arabidopsis. SGN provides tools such as: BLAST searches, the SolCyc biochemical pathways database, a CAPS experiment designer, an intron detection tool, an advanced Alignment Analyzer, and a browser for phylogenetic trees. The SGN code and database are developed as an open source project, and is based on database schemas developed by the GMOD project and SGN-specific extensions.

Proper citation: SGN (RRID:SCR_004933) 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

https://github.com/danbider/lightning-pose

Software video centric package for direct video manipulation. Semi supervised animal pose estimation algorithm, Bayesian post processing approach and deep learning package. Improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools.

Proper citation: Lightning Pose (RRID:SCR_024480) Copy   

•   Source: SciCrunch Registry

http://lepr.ofm-research.org/

Database of results of published experimental studies involving liquid-solid phase equilibria relevant to natural magmatic systems.

Proper citation: Library of Experimental Phase Relations (RRID:SCR_002202) Copy   

•   Source: SciCrunch Registry

https://enigma.lbl.gov/regprecise/

Collection of manually curated inferences of regulons in prokaryotic genomes. Database for capturing, visualization and analysis of transcription factor regulons that were reconstructed by comparative genomic approach in wide variety of prokaryotic genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RegPrecise (RRID:SCR_002149) Copy   

•   Source: SciCrunch Registry

http://www.earthchem.org/seddb

Geochemical database for marine and terrestrial sediments primarily from the published literature containing a full range of analytical values for sediment samples, primarily from marine sediment cores. It includes major and trace element concentrations, radiogenic and stable isotope ratios, and data for a plethora of materials such as organic and inorganic components, leachates, and size fractions. SedDB also archives a vast array of metadata relating to the individual sample.

Proper citation: SedDB (RRID:SCR_002210) Copy   

•   Source: SciCrunch Registry

http://www.earthchem.org/petdb

Accepts and provides access to geochemical and petrological data for ocean floor igneous and metamorphic rocks, (whole rock, volcanic, glass, mineral, and melt inclusion analyses), and mantle and lower-crustal xenolith samples. Data are compiled primarily from the published literature. Authors are encouraged to submit their datasets and databases to EarthChem.

Proper citation: PetDB (RRID:SCR_002209) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry

http://magi.cs.brown.edu/

A tool for annotating, exploring, and analyzing gene sets that may be associated with cancer.

Proper citation: Mutation Annotation and Genomic Interpretation (RRID:SCR_002800) Copy   

•   Source: SciCrunch Registry

http://kb.phenoscape.org/

Knowledgebase that uses ontologies to integrate phenotypic data from genetic studies of zebrafish with evolutionary variable phenotypes from the systematic literature of ostariophysan fishes. Users can explore the data by searching for anatomical terms, taxa, or gene names. The expert system enables the broad scale analysis of phenotypic variation across taxa and the co-analysis of these evolutionarily variable features with the phenotypic mutants of model organisms. The Knowledgebase currently contains 565,158 phenotype statements about 2,527 taxa, sourced from 57 publications, as well as 38,189 phenotype statements about 4,727 genes, retrieved from ZFIN. 2013-01-26.

Proper citation: Phenoscape Knowledgebase (RRID:SCR_002821) Copy   

•   Source: SciCrunch Registry

http://www.plexdb.org/index.php

PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens. PLEXdb is a genotype to phenotype, hypothesis building information warehouse, leveraging highly parallel expression data with seamless portals to related genetic, physical, and pathway data. The integrated tools of PLEXdb allow investigators to use commonalities in plant biology for a comparative approach to functional genomics through use of large-scale expression profiling data sets.

Proper citation: PLEXdb - Plant Expression Database (RRID:SCR_006963) Copy   

•   Source: SciCrunch Registry

http://www.digitalfishlibrary.org/index.php

A database of 3D magnetic resonance (MRI) images of fish accessible to scientists, educators and the general public via the web. The Marine Vertebrate Collection at the Scripps Institution of Oceanography provides the majority of the DFL specimens.

Proper citation: Digital Fish Library (RRID:SCR_008338) Copy   

•   Source: SciCrunch Registry

https://web.njit.edu/~matveev/calc.html

A modeling tool for simulating intracellular calcium diffusion and buffering. CalC solves continuous reaction-diffusion PDEs describing the entry of calcium into a volume through point-like channels, and its diffusion, buffering and binding to calcium receptors. Its features include: being platform-independent; being operated by simple script; combinable with MATLAB; and providing real-time views. Demos and manuals are provided on the website.

Proper citation: CalC (RRID:SCR_014259) Copy   

•   Source: SciCrunch Registry

http://interactome.baderlab.org/

Project portal for the Human Reference Protein Interactome Project, which aims generate a first reference map of the human protein-protein interactome network by identifying binary protein-protein interactions (PPIs). It achieves this by systematically interrogating all pairwise combinations of predicted human protein-coding genes using proteome-scale technologies.

Proper citation: Human Reference Protein Interactome Project (RRID:SCR_015670) Copy   

•   Source: SciCrunch Registry

https://github.com/broadinstitute/Drop-seq

Software Java tools for analyzing Drop-seq data. Used to analyze gene expression from thousands of individual cells simultaneously. Analyzes mRNA transcripts while remembering origin cell transcript.

Proper citation: Drop-seq tools (RRID:SCR_018142) Copy   

•   Source: SciCrunch Registry

https://github.com/satijalab/seurat

Software R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. Used for quality control, analysis, and exploration of single-cell RNA sequencing (scRNA-seq) data.

Proper citation: Seurat (RRID:SCR_016341) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/gernerlab/cytomap/-/wikis/home

Software tool as spatial analysis software for whole tissue sections.Utilizes information on cell type and position to phenotype local neighborhoods and reveal how their spatial distribution leads to generation of global tissue architecture.Used to make advanced data analytic techniques accessible for single cell data with position information.

Proper citation: CytoMAP (RRID:SCR_021227) Copy   

•   Source: SciCrunch Registry

https://github.com/hahnlab/CAFExp

Software tool for computational analysis of gene family evolution. Used for statistical analysis of evolution gene family sizes. Models evolution of gene family sizes over phylogeny.

Proper citation: Computational Analysis of gene Family Evolution (RRID:SCR_018924) Copy   

•   Source: SciCrunch Registry