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http://mousespinal.brain-map.org/about.html

Platform for exploring spinal cord at cellular and molecular levels. Map of gene expression for adult and juvenile mouse spinal cord. Provides map of normal mouse when used to compare gene expression in diseased or injury models. Interactive database of gene expression mapped across all anatomic segments of mouse spinal cord at postnatal days 4 and 56. Indexed set of images based on RNA in situ hybridization data, searchable and sortable by gene, age, expression, cervical, thoracic, lumbar, sacral, and coccygeal segments.

Proper citation: Allen Mouse Spinal Cord Atlas (RRID:SCR_007418) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/genre/proj/ustilago/

The MIPS Ustilago maydis Genome Database aims to present information on the molecular structure and functional network of the entirely sequenced, filamentous fungus Ustilago maydis. The underlying sequence is the initial release of the high quality draft sequence of the Broad Institute. The goal of the MIPS database is to provide a comprehensive genome database in the Genome Research Environment in parallel with other fungal genomes to enable in depth fungal comparative analysis. The specific aims are to: 1. Generate and assemble Whole Genome Shotgun sequence reads yielding 10X coverage of the U. maydis genome 2. Integrate the genomic sequence assembly with physical maps generated by Bayer CropScience 3. Perform automated annotation of the sequence assembly 4. Align the strain 521 assembly with the FB1 assembly provided by Exelixis 5. Release the sequence assembly and results of our annotation and analysis to public Ustilago maydis is a basidiomycete fungal pathogen of maize and teosinte. The genome size is approximately 20 Mb. The fungus induces tumors on host plants and forms masses of diploid teliospores. These spores germinate and form haploid meiotic products that can be propagated in culture as yeast-like cells. Haploid strains of opposite mating type fuse and form a filamentous, dikaryotic cell type that invades plant tissue to reinitiate infection. Ustilago maydis is an important model system for studying pathogen-host interactions and has been studied for more than 100 years by plant pathologists. Molecular genetic research with U. maydis focuses on recombination, the role of mating in pathogenesis, and signaling pathways that influence virulence. Recently, the fungus has emerged as an excellent experimental model for the molecular genetic analysis of phytopathogenesis, particularly in the characterization of infection-specific morphogenesis in response to signals from host plants. Ustilago maydis also serves as an important model for other basidiomycete plant pathogens that are more difficult to work with in the laboratory, such as the rust and bunt fungi. Genomic sequence of U. maydis will also be valuable for comparative analysis of other fungal genomes, especially with respect to understanding the host range of fungal phytopathogens. The analysis of U. maydis would provide a framework for studying the hundreds of other Ustilago species that attack important crops, such as barley, wheat, sorghum, and sugarcane. Comparisons would also be possible with other basidiomycete fungi, such as the important human pathogen C. neoformans. Commercially, U. maydis is an excellent model for the discovery of antifungal drugs. In addition, maize tumors caused by U. maydis are prized in Hispanic cuisine and there is interest in improving commercial production. The complete putative gene set of the Broad Institute''s second release is loaded into the database and in addition all deviating putative genes from a putative gene set produced by MIPS with different gene prediction parameters are also loaded. The complete dataset will then be analysed, gene predictions will be manually corrected due to combined information derived from different gene prediction algorithms and, more important, protein and EST comparisons. Gene prediction will be restricted to ORFs larger than 50 codons; smaller ORFs will be included only if similarities to other proteins or EST matches confirm their existence or if a coding region was postulated by all prediction programs used. The resulting proteins will be annotated. They will be classified according to the MIPS classification catalogue receiving appropriate descriptions. All proteins with a known, characterized homolog will be automatically assigned to functional categories using the MIPS functional catalog. All extracted proteins are in addition automatically analysed and annotated by the PEDANT suite.

Proper citation: MIPS Ustilago maydis Database (RRID:SCR_007563) Copy   

•   Source: SciCrunch Registry

http://www.homepages.ed.ac.uk/pmckeigu/pooling/poolscore.htm

Software program for analysis of case-control genetic association studies using allele frequency measurements on DNA pools (entry from Genetic Analysis Software)

Proper citation: POOLSCORE (RRID:SCR_007514) Copy   

•   Source: SciCrunch Registry

http://atlasgeneticsoncology.org/

Online journal and database devoted to genes, cytogenetics, and clinical entities in cancer, and cancer-prone diseases. Its aim is to cover the entire field under study and it presents concise and updated reviews (cards) or longer texts (deep insights) concerning topics in cancer research and genomics.

Proper citation: Atlas of Genetics and Cytogenetics in Oncology and Haematology (RRID:SCR_007199) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/GOA

An annotation program which aims to provide high-quality Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index (IPI). It is a central dataset for other major multi-species databases, such as Ensembl and NCBI. Because of the multi-species nature of the UniProtKB, UniProtKB-GOA assists in the curation of 200,000 species. This involves electronic annotation and the integration of high-quality manual GO annotation from all GO Consortium model organism groups and specialist groups. Gene Association Files can be accessed from the Downloads section of the website.

Proper citation: GOA (RRID:SCR_007691) Copy   

•   Source: SciCrunch Registry

http://systers.molgen.mpg.de/

SYSTERS is a database of protein sequences grouped into homologous families and superfamilies. The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes. Gene, Human, Vertebrate, Genome, Human ORFs

Proper citation: SYSTERS (RRID:SCR_007955) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/genes.shtml

Searchable database of mouse genes, DNA segments, cytogenetic markers and QTLs. MGI provides access to integrated data on mouse genes and genome features, from sequences and genomic maps to gene expression and disease models.

Proper citation: Genes, Genome Features and Maps (RRID:SCR_017524) Copy   

•   Source: SciCrunch Registry

http://www.mirtoolsgallery.org/miRToolsGallery/node/1055

Comprehensive resource of microRNA target predictions and expression profiles. Used for whole genome prediction of miRNA target genes. For each miRNA, target genes are selected on basis of sequence complementarity using position weighted local alignment algorithm, free energies of RNA-RNA duplexes, and conservation of target sites in related genomes. Provides information about set of genes potentially regulated by particular microRNA, co-occurrence of predicted target sites for multiple microRNAs in mRNA and microRNA expression profiles in tissues. Users are allowed to customize algorithm, numerical parameters, and position-specific rules., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: miRanda (RRID:SCR_017496) Copy   

•   Source: SciCrunch Registry

https://ist.medisapiens.com/

Database by Medisapiens Ltd. as fully integrated and annotated human gene expression data source. All genes are comparable across all samples. Provides data analysis options using database of human transcriptome.

Proper citation: IST Online (RRID:SCR_018794) Copy   

•   Source: SciCrunch Registry

https://www.sourcebioscience.com/products/life-sciences-research/clones/rnai-resources/c-elegans-rnai-collection-ahringer/

C. elegans RNAi feeding library distributed by Source BioScience Ltd. Designed for genome wide study of gene function in C. elegans through loss of function studies.

Proper citation: C. elegans RNAi Collection (Ahringer) (RRID:SCR_017064) Copy   

•   Source: SciCrunch Registry

https://vertebrate.genenames.org/

Software resource for vertebrate gene nomenclature. Database of gene symbols. Coordinates with vertebrate nomenclature committees, MGNC (mouse), RGNC (rat), CGNC (chicken), AGNC (Anole green lizard), XNC (Xenopus frog) and ZNC (zebrafish), to ensure genes are named in line with their human homologs.

Proper citation: VGNC (RRID:SCR_017514) Copy   

•   Source: SciCrunch Registry

http://mirwalk.umm.uni-heidelberg.de/

Software tool to store the predicted and the experimentally validated microRNA (miRNA)-target interaction pairs. Predictions within the complete sequence of genes of human, mouse, and rat genomes. Integrates a comparative platform of miRNA-binding sites resulting from ten different prediction datasets.

Proper citation: miRWalk (RRID:SCR_016509) Copy   

•   Source: SciCrunch Registry

http://www.humphreyslab.com/SingleCell/

Software tool as analyzer for kidney single cell datasets. Allows users to query gene expression from mouse or human kidney and human kidney organoid single cell datasets. For details about datasets visit ReBuilding a Kidney website.

Proper citation: Kidney Interactive Transcriptomics (RRID:SCR_017209) Copy   

•   Source: SciCrunch Registry

https://www.alzforum.org/alzpedia

Collection of brief summaries of various genes and proteins implicated in pathophysiology of Alzheimer’s disease and other neurodegenerative disorders. It will be expanded over time and updated periodically in order to reflect current state of knowledge.

Proper citation: ALZPEDIA (RRID:SCR_017548) Copy   

•   Source: SciCrunch Registry

http://structuralbiology.cau.edu.cn/PlantGSEA/

Websever for gene set enrichment analysis of plants. Used for interpreting biological meaning of a list of genes by computing the overlaps with various previously defined gene sets.

Proper citation: PlantGSEA (RRID:SCR_016866) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/dred/index.php

Database of genes related to Repeat Expansion Diseases, as comprehensive manually curated database that covers all reported repeat expansion diseases included in PubMed and OMIM. Detailed information about each repeat and its related genes/diseases can be found in database, links to OMIM, NCBI and Ensembl are also provided. Provides list of predicted genes containing unstable tandem repeats that may cause diseases via abnormal repeat expansion by support vector machine and random forest.

Proper citation: Database of genes related to Repeat Expansion Diseases (RRID:SCR_018086) Copy   

•   Source: SciCrunch Registry

http://pubmatrix.grc.nia.nih.gov/

PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence. PubMatrix is a simple way to rapidly and systematically compare any list of terms against any other list of terms in PubMed. It reports back the frequency of co-occurrence between all pairwise comparisons between the two lists as a matrix table. Lists of terms can be anything; gene names, diseases, gene functions, authors, etc. The user can then quickly sort or browse the frequency matrix table to do individual searches independently. This allows the user to build up tables of word relationships in PubMed in the context of your experiments or your scientific interests. This is useful for analyzing combinatorial datasets, as found with multiplex experimental systems, such as cDNA microarrays, genomic, proteomic, or other multiplex comparisons. The PubMatrix database is an archive of previous searches on many topics. Sponsors: PubMatrix is supported by the National Institutes of Health.

Proper citation: PubMatrix (RRID:SCR_008236) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/stepwise/index.html

Software application that is a stepwise approach to identifying recombination breakpoints in a sequence alignment (entry from Genetic Analysis Software)

Proper citation: R/STEPWISE (RRID:SCR_007420) Copy   

•   Source: SciCrunch Registry

http://www.well.ox.ac.uk/platypus

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software tool designed for efficient and accurate variant detection in high throughput sequencing data. Haplotype based variant caller for next generation sequence data.

Proper citation: Platypus (RRID:SCR_005389) Copy   

•   Source: SciCrunch Registry

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https://cran.r-project.org/web/packages/adegenet/index.html

Software package dedicated to the handling of molecular marker data for multivariate analysis. This package is related to ADE4, a R package for multivariate analysis, graphics, phylogeny and spatial analysis. (entry from Genetic Analysis Software)

Proper citation: ADEGENET (RRID:SCR_000825) Copy   

•   Source: SciCrunch Registry