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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.

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On page 62 showing 1221 ~ 1240 out of 1,647 results
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  • RRID:SCR_015491

    This resource has 100+ mentions.

http://www.lncrnadb.org/

Searchable database of comprehensive annotations of eukaryotic long non-coding RNAs. Entries are manually curated from referenced literature.

Proper citation: lncRNAdb (RRID:SCR_015491) Copy   


  • RRID:SCR_017487

    This resource has 1+ mentions.

http://smithlabresearch.org/software/methbase/

Central reference methylome database created from public BS-seq datasets. Provides methylation level at individual sites, regions of allele specific methylation, hypo- or hyper-methylated regions, partially methylated regions, and detailed meta data and summary statistics.

Proper citation: MethBase (RRID:SCR_017487) Copy   


  • RRID:SCR_018412

    This resource has 10+ mentions.

https://signalingpathways.org

Web multi omics knowledgebase based upon public, manually curated transcriptomic and cistromic datasets involving genetic and small molecule manipulations of cellular receptors, enzymes and transcription factors. Integrated omics knowledgebase for mammalian cellular signaling pathways. Web browser interface was designed to accommodate numerous routine data mining strategies. Datasets are biocurated versions of publically archived datasets and are formatted according to recommendations of the FORCE11 Joint Declaration on Data Citation Principles73, and are made available under Creative Commons CC 3.0 BY license. Original datasets are available.

Proper citation: Signaling Pathways Project (RRID:SCR_018412) Copy   


  • RRID:SCR_023594

    This resource has 1+ mentions.

https://github.com/citiususc/veryfasttree

Software tool for speeding up estimation of phylogenetic trees for large alignments through parallelization and vectorization strategies.

Proper citation: VeryFastTree (RRID:SCR_023594) Copy   


  • RRID:SCR_000030

http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.html

A software package that provides functions to read raw RT-qPCR data of different platforms.

Proper citation: ReadqPCR (RRID:SCR_000030) Copy   


  • RRID:SCR_001266

http://sourceforge.net/projects/metabnorm/

Software tool as mixed model normalization method for metabolomics data.Uses normalization approach based on mixed model, with simultaneous estimation of correlation matrix.

Proper citation: metabnorm (RRID:SCR_001266) Copy   


  • RRID:SCR_002678

    This resource has 10+ mentions.

http://fantom.gsc.riken.jp/4/

The FANTOM consortium is an international collaborative research project initiated and organized by the RIKEN Omics Science Center. In earlier FANTOM efforts we cloned and annotated 103,000 full-length cDNAs from mouse and distributed them to researchers throughout the world. FANTOM1-3 focused on identifying the transcribed components of mammalian cells. This work improved estimates of the total number of genes and their alternative transcript isoforms in both human and mouse, expanded gene families, and revealed that a large fraction of the transcriptome is non-coding. In addition, with the development of Cap Analysis of Gene Expression (CAGE) FANTOM3 could map a large fraction of transcription start sites and revise our models of promoter structure. This updated web resource provides the previous FANTOM results mapped to current genome builds and presents the results of FANTOM4. In FANTOM4 the focus has changed to understanding how these components work together in the context of a biological network. Using deepCAGE (deep sequencing with CAGE) we monitored the dynamics of transcription start site (TSS) usage during a time course of monocytic differentiation in the acute myeloid leukemia cell line THP-1. This allowed us to identify active promoters, monitor their relative expression and define relevant regions for carrying out transcription factor binding site predictions. Computational methods were then used to build a network model of gene expression in this leukemia and the transcription factors key to its regulation. This work gives the first picture of the wiring between genes involved in acute myeloid leukemia and provides a strategy for identifying key factors that determine cell fates. In addition to the network, FANTOM4 data was used in two additional analyses. The first identified a novel class of short RNAs associated with transcription start sites and the second focused on the role of repetitive element expression in the transcriptome. TOOLS *Genome Browser: graphical display of genomic features, such as promoters, exon structures, H3K9 acetylation, transcription factors positioning on the genome, coupled with gene and promoter activities. *EdgeExpressDB: regulatory interactions, such as transcriptional regulation, post-transcriptional silencing with miRNA, and PPI, coupled with gene and promoter activities. *SwissRegulon: FANTOM4 TF regulation is predicted using Motif Activity Response Analysis (MARA) developed by Erik van Nimwegen at Biozentrum. Follow the link to carry out MARA on your own dataset. *Custom Tracks on the UCSC Genome Browser: FANTOM4 tracks on the UCSC Genome Browser Database. *The RIKEN integrated database of mammals: Integration of FANTOM4 data with other mammalian resources, in particular, produced by RIKEN.

Proper citation: FANTOM DB (RRID:SCR_002678) Copy   


  • RRID:SCR_002674

    This resource has 1+ mentions.

https://github.com/eduardporta/e-Driver

Software tool to identify cancer driver genes based on linear annotations of biological regions such as protein domains.Uses information on three-dimensional structures of mutated proteins to identify specific structural features. Then algorithm analyzes whether these features are enriched in cancer somatic mutations and are candidate driver genes.

Proper citation: e-Driver (RRID:SCR_002674) Copy   


  • RRID:SCR_002972

http://www.cs.ucr.edu/~yyang027/mrfseq.htm

Algorithm based on a Markov random field (MRF) model that uses additional gene coexpression data to enhance differential gene expression prediction power. It is able to call differentially expressed (DE) genes but also assign confidence scores to each inferred DE gene.

Proper citation: MRFSEQ (RRID:SCR_002972) Copy   


  • RRID:SCR_007666

    This resource has 1+ mentions.

http://fullmal.hgc.jp/

Full-Length cDNA Database is a resource for cDNA libraries of arhtropods and parasites. The arthropod species covered are Anopheles stephensi, Glossina morsitans (Tsetse fly), and Dermatophagoides farinae (House dust mite), while the parasitic species included are Plasmodium falciparum (Malaria), Toxoplasma gondii, Cryptosporidium parvum, Babesia bovis (Babesia), and Echinococcus multilocularis. A specialized database of each species is available as a link from the home page. This database has been constructed and maintained since 2001 by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science. Anopheles stephensi, Glossina morsitans, Tsetse fly, Dermatophagoides farinae, House dust mite, Plasmodium falciparum, Malaria, Toxoplasma gondii, Cryptosporidium parvum, Babesia bovis, Babesia, Echinococcus multilocularis, cDNA, cDNA library, arthropod genome, parasite genome

Proper citation: Full-Length cDNA Database (RRID:SCR_007666) Copy   


  • RRID:SCR_007733

    This resource has 500+ mentions.

http://img.jgi.doe.gov/

Datasets and tools for comparative analysis and annotation of all publicly available genomes from three domains of life in a uniquely integrated context. Plasmids that are not part of a specific microbial genome sequencing project and phage genomes are also included in order to increase its genomic context for comparative analysis. The user interface (see User Interface Map) allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes.

Proper citation: IMG (RRID:SCR_007733) Copy   


http://cegg.unige.ch/mirortho

It contains predictions of precursor miRNA genes covering several animal genomes combining orthology and a Support Vector Machine. We provide homology extended alignments of already known miRBase families and putative miRNA families exclusively predicted by our SVM and orthology pipeline. The current release of miROrtho covers 46 animal genomes. We provide homology extended alignments of already known miRBase families and putative miRNA families exclusively predicted by our SVM and orthology pipeline.

Proper citation: miROrtho: the catalogue of animal microRNA genes (RRID:SCR_007797) Copy   


  • RRID:SCR_007815

    This resource has 10+ mentions.

http://biobases.ibch.poznan.pl/ncRNA/

It is intended to provide information on the sequences and functions of transcripts which do not code for proteins, but perform regulatory roles in the cell. Currently, the database includes over 30,000 individual sequences from 99 species of Bacteria, Archaea and Eukaryota. The primary source of sequences included in the database was the GenBank. Additional annotation information for mouse and human ncRNAs was derived from FANTOM3 database and H-inviational Integrated Database of Annotated Human Genes version 3.4, respectively. Genome mapping information was derived from tha data available at the UCSC Genome Browser site. The sequences and annotations of small cytoplasmic RNAs from bacteria, for which annotation is lacking in the genome sequences, were derived from the Rfam database. The microRNAs or snoRNAs which were available in previous editions, as well as other housekeeping (infrastructural) RNAs (e.g. rRNA, tRNA, snRNA, SRP RNA) are not included in our database to avoid redundancy with more specialized databases which emerged in recent years.

Proper citation: Noncoding RNA database (RRID:SCR_007815) Copy   


  • RRID:SCR_007851

    This resource has 1+ mentions.

http://www.cmbi.ru.nl/phylopat

A database of phylogenetic patterns of evolution between 46 different species. PhyloPat uses the latest release of EnsMart (release 52), and their one-to-one, one-to-many and many-to-many orthologies. First, we stored all of the Ensembl IDs within the 46 species, and the orthologies between them. Second, we determined the evolutionary order of the studied species using the NCBI Taxonomy database. The phylogenetic tree of these species can be viewed here. Third, we used this phylogenetic tree as a starting point for building our phylogenetic lineages. For each gene in the first species (S. cerevisiae), we looked for orthologs in the other species. All orthologs were added to the phylogenetic lineage, and in the next round were checked for orthologs themselves, until no more orthologies were found for any of the genes. This process was repeated for all genes in all species that were not connected to any phylogenetic lineage yet. The complete phylogenetic lineage determination generated 329,998 phylogenetic lineages, consisting of 973,821 genes. These lineages can be queried here by phylogenetic patterns, MySQL regular expressions or simply a list of Ensembl/EMBL/EntrezGene/HGNC IDs. Output can be given in HTML, Excel or plain text format.

Proper citation: PhyloPat (RRID:SCR_007851) Copy   


  • RRID:SCR_007850

    This resource has 50+ mentions.

http://phylomedb.bioinfo.cipf.es

Database for phylomes, that is, complete collections of phylogenetic trees for all proteins encoded in a given genome. It aims at providing a repository of high-quality phylogenies and alignments for proteins encoded in model species. To derive a phylome, each protein encoded in a given genome is used as a seed to retrieve its homologs in other complete genomes. These sequences are aligned and processed to derive reliable phylogenies using several phylogenetic methods. Besides providing the evolutionary history of the gene families, phylomeDB includes phylogeny based predictions of orthology and paralogy relationships., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhylomeDB (RRID:SCR_007850) Copy   


  • RRID:SCR_007848

    This resource has 1+ mentions.

http://www.partigenedb.org/

A publicly available database resource containing the assembled partial genomes for ~700 eukaryotic organisms. Partial genomes are generated from expressed sequence tag datasets containing more than 1000 sequences. PartiGeneDB allows users to view sets of genes and identify genes of interest in organisms for which a full genome is not currently available. PartiGeneDB is automatically updated to include new organism datasets as they are generated. PartiGeneDB provides four portals of entry into the database. It is hosted and supported by the Hospital for Sick Children, Toronto. In addition to providing a comprehensive resource facilitating comparative analyses, PartiGeneDB allows researchers to access the partial genomes of organisms that may not be available elsewhere. However, we recommend and encourage users interested in exploring datasets from a single organism in more depth, that you visit the specific web sites associated with the sequencing effort associated with that organism .

Proper citation: PartiGeneDB (RRID:SCR_007848) Copy   


  • RRID:SCR_007778

    This resource has 1000+ mentions.

http://metacyc.org/

MetaCyc is a database of nonredundant, experimentally elucidated metabolic pathways. MetaCyc contains more than 1,200 pathways from more than 1,600 different organisms, and is curated from the scientific experimental literature. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated compounds, enzymes, and genes.

Proper citation: MetaCyc (RRID:SCR_007778) Copy   


  • RRID:SCR_007777

    This resource has 500+ mentions.

http://merops.sanger.ac.uk/

An information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.

Proper citation: MEROPS (RRID:SCR_007777) Copy   


http://locate.imb.uq.edu.au/

LOCATE is a curated database that houses data describing the membrane organization and subcellular localization of proteins from the RIKEN FANTOM4 mouse and human protein sequence set. The membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing peer-reviewed publications.

Proper citation: LOCATE: subcellular localization database (RRID:SCR_007763) Copy   


http://www.mgc.ac.cn/VFs/

An integrated and comprehensive database of virulence factors for bacterial pathogens (also including Chlamydia and Mycoplasma). VFDB is a platform for further study of comparative pathogenomics. Major features include tabular comparison of pathogenomic composition in terms of virulence, multiple alignments and statistic analysis of homologous virulence genes, and graphical comparison of pathogenomic organization of VFs. Category: Genomics Databases (non-vertebrate) Subcategory: Prokaryotic genome databases

Proper citation: VFDB - Virulence Factors of Bacterial Pathogens (RRID:SCR_007969) Copy   



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