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https://github.com/gdancik/shinyGEO

Web based tool to download gene expression datasets from GEO in order to perform differential expression and survival analysis for gene of interest. Produces publication ready graphics and generates R code ensuring that all analyses are reproducible. Web based application for analyzing gene expression omnibus datasets.

Proper citation: shinyGEO (RRID:SCR_017605) Copy   

•   Source: SciCrunch Registry

https://scdevdb.deepomics.org/

Database for insights into single cell gene expression profiles during human developmental processes. Interactive database provides DE gene lists in each developmental pathway, t-SNE map, and GO and KEGG enrichment analysis based on these differential genes.

Proper citation: Single Cell Developmental Database (RRID:SCR_017546) Copy   

•   Source: SciCrunch Registry

https://github.com/LaBiOS/Transcriptive

Software tool as bioinformatics analysis pipeline used for RNA sequencing data. Workflow processes raw data from FastQ inputs, aligns reads, generates gene and transcript counts, and performs quality control on results.

Proper citation: Transcriptive (RRID:SCR_017545) Copy   

•   Source: SciCrunch Registry

https://health.uconn.edu/worm-lab/track-a-worm/

Open source system for quantitative assessment of C. Elegans locomotory and bending behavior. Used for quantitative behavioral analyses to understand circuit and gene bases of behavior. Constantly records and analyzes position and body shape of freely moving worm at high magnification.

Proper citation: Track-A-Worm (RRID:SCR_018299) Copy   

•   Source: SciCrunch Registry

https://github.com/WangHYLab/fcirc

Software Python pipeline for linear and circular RNAs of known fusions exploration. Pipeline for exploring linear transcripts and circRNAs of known fusions based on RNA-Seq data. Known fusion genes are from multiple databases like COSMIC, ChimerDB, TicDB, FARE-CAFE and FusionCancer or user-added gene-pairs.

Proper citation: Fcirc (RRID:SCR_018090) Copy   

•   Source: SciCrunch Registry

https://dice-database.org

Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics. Collection of identified cis-eQTLs for 12,254 unique genes, which represent 61% of all protein-coding genes expressed in human cell types. Datasets to help reveal effects of disease risk associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

Proper citation: Database of Immune Cell Epigenomes (RRID:SCR_018259) Copy   

•   Source: SciCrunch Registry

https://metacpan.org/pod/Bio::CUA

Software tool as flexible and comprehensive codon usage analyzer. Used to analyze codon usage bias (CUB) and relevant problems.

Proper citation: Codon Usage Analyzer (RRID:SCR_018500) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/minet/

Open source software R package for inferring large transcriptional networks using mutual information. Implements algorithms for inferring networks such as gene networks from microarray data.

Proper citation: minet (RRID:SCR_018661) Copy   

•   Source: SciCrunch Registry

https://mygene.info/

Web service for querying or retrieving gene annotation data.

Proper citation: MyGene.info (RRID:SCR_018660) Copy   

•   Source: SciCrunch Registry

http://rats.pub

Web service that conducts comprehensive literature mining to identify roles of genes in addiction. Searches PubMed to find abstracts containing genes of interest and list of curated addiction related keywords.

Proper citation: RatsPub (RRID:SCR_018905) Copy   

•   Source: SciCrunch Registry

http://tools.dice-database.org/GOnet/)

Web tool for interactive Gene Ontology analysis of any biological data sources resulting in gene or protein lists.

Proper citation: GOnet (RRID:SCR_018977) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/searches/GO_form.shtml

With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly. Platform: Online tool

Proper citation: MGI GO Browser (RRID:SCR_006489) Copy   

•   Source: SciCrunch Registry

http://unite.ut.ee/index.php

A fungal rDNA internal transcribed spacer (ITS) sequence database (although additional genes and genetic markers are also welcome) to facilitate identification of environmental samples of fungal DNA. Additional important features include user annotation of INSD sequences to add metadata on, e.g., locality, habitat, soil, climate, and interacting taxa. The user can furthermore annotate INSD sequences with additional species identifications that will appear in the results of any analyses done. UNITE focuses on high-quality ITS sequences generated from fruiting bodies collected and identified by experts and deposited in public herbaria. In addition, it also holds all fungal ITS sequences in the International Nucleotide Sequence Databases (INSD: NCBI, EMBL, DDBJ). Both sets of sequences may be used in any analyses carried out. UNITE is accompanied by a project management system called PlutoF, where users can store field data, document the sequencing lab procedures, manage sequences, and make analyses. PlutoF intends to make it possible for taxonomists, ecologists, and biogeographers to use a common platform for data storage, handling, and analyses, with the intent of facilitating an integration of these disciplines. A user can have an unlimited number of projects but still make analyses across any project data available to him.

Proper citation: UNITE (RRID:SCR_006518) Copy   

•   Source: SciCrunch Registry

http://kobas.cbi.pku.edu.cn/

Web server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: KOBAS (RRID:SCR_006350) Copy   

•   Source: SciCrunch Registry

http://www.phytozome.net/

A comparative platform for green plant genomics. Families of orthologous and paralogous genes that represent the modern descendents of ancestral gene sets are constructed at key phylogenetic nodes. These families allow easy access to clade specific orthology / paralogy relationships as well as clade specific genes and gene expansions. As of release v9.1, Phytozome provides access to forty-one sequenced and annotated green plant genomes which have been clustered into gene families at 20 evolutionarily significant nodes. Where possible, each gene has been annotated with PFAM, KOG, KEGG, and PANTHER assignments, and publicly available annotations from RefSeq, UniProt, TAIR, JGI are hyper-linked and searchable., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Phytozome (RRID:SCR_006507) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/bioc/html/GeneAnswers.html

GeneAnswers provide an integrated tool for given genes biological or medical interpretation. It includes statistical test of given genes and specified categories. Microarray techniques have been widely employed in genomic scale studies for more than one decade. The standard analysis of microarray data is to filter out a group of genes from thousands of probes by certain statistical criteria. These genes are usually called significantly differentially expressed genes. Recently, next generation sequencing (NGS) is gradually adopted to explore gene transcription, methylation, etc. Also a gene list can be obtained by NGS preliminary data analysis. However, this type of information is not enough to understand the potential linkage between identified genes and interested functions. The integrated functional and pathway analysis with gene expression data would be very helpful for researchers to interpret the relationship between the identified genes and proposed biological or medical functions and pathways. The GeneAnswers package provides an integrated solution for a group of genes and specified categories (biological or medical functions, such as Gene Ontology, Disease Ontology, KEGG, etc) to reveal the potential relationship between them by means of statistical methods, and make user-friendly network visualization to interpret the results. Besides the package has a function to combine gene expression profile and category analysis together by outputting concept-gene cross tables, keywords query on NCBI Entrez Gene and application of human based Disease ontology analysis of given genes from other species can help people to understand or discover potential connection between genes and functions. Sponsors: This project was supported in part by Award Number UL1RR025741 from the National Center for Research Resources.

Proper citation: GeneAnswers (RRID:SCR_006498) Copy   

•   Source: SciCrunch Registry

http://www.plantontology.org

Ontology and database that links plant anatomy, morphology and growth and development to plant genomics data.Plant Ontology Consortium develops, curates and shares controlled vocabularies (ontologies) that describe plant structures and growth and developmental stages, providing semantic framework for meaningful cross species queries across databases. PO is under active development to expand to encompass terms and annotations from all plants.

Proper citation: Plant Ontology (RRID:SCR_006494) Copy   

•   Source: SciCrunch Registry

http://www.rarechromo.org/html/home.asp

Unique is a source of information and support to families and individuals affected by any rare chromosome disorder and to the professionals who work with them. Unique is a UK-based charity but welcomes members worldwide. Unique''''s Karyotype Database allows users to search the Registered Chromosome Disorders by chromosome, arm and disorder. You may have been given a diagnosis or indication of a chromosome disorder by a geneticist or other medical professional and they may have used a medical term which is unfamiliar to you. So to help you decide if Unique is the appropriate organization for you, we thought it would be useful to describe the different categories of rare chromosome disorder. Rare chromosome disorders can be grouped as structural disorders, numerical disorders and other miscellaneous disorders. Unique: * acts as an international family support group * produces a newsletter three times each year * works to promote awareness of rare chromosome disorders * arranges for families to assist in research into rare chromosome disorders * links families whose children have similar clinical and/or practical problems * works to ensure that the public at large are aware of rare chromosome disorders * works to raise funds to support the group activities and produce literature to make others more aware of our children''''s conditions * assists relevant research projects and the centralisation of information, at all times observing the need for total confidentiality * sets up local groups throughout the UK for families affected by any rare chromosome disorders and to give support and encouragement to each other * develops and maintains a comprehensive computerised database detailing the life-time effects of specific chromosome disorders on affected members * aims to hold an annual conference where families and relevant specialists can meet and be informed of the latest medical, technical and practical developments * liaises and works in co-operation, with other similar support groups and professionals world-wide for the benefit of families and individuals affected by rare chromosome disorders * ensures that hospitals, doctors, health authorities, genetic clinics and other professionals are aware of the group so that we may have early contact with families where required Membership of Unique is free but the group receives no government funding and is heavily reliant on donations and fundraising to continue its work. Please help us in whatever way you can.

Proper citation: Unique (RRID:SCR_006492) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/mgihome/GO/project.shtml

This resource is part of the Gene Ontology Consortium which seeks to provide controlled vocabularies for the description of the molecular function, biological process, and cellular component of gene products. These terms are to be used as attributes of gene products by collaborating databases, facilitating uniform queries across them. GO team members at MGI participate in ontology development, outreach, and functional curation of mouse gene products. The GO vocabularies have a hierarchical structure that permits a range of detail from high-level, broadly descriptive terms to very low level, highly specific terms. This broad range is useful both in annotating genes and in searching for gene information using these terms as search criteria. GO terms are defined, allowing all databases to use the terms consistently and properly. GO annotations in the databases additionally include the publication reference which allowed the association to be made and an evidence statement citing how the association was determined.

Proper citation: Mouse Genome Informatics: The Gene Ontology Project (RRID:SCR_006447) Copy   

•   Source: SciCrunch Registry

http://omim.org

Online catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.

Proper citation: OMIM (RRID:SCR_006437) Copy   

•   Source: SciCrunch Registry