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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

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   

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http://www.fruitfly.org

Database on the sequence of the euchromatic genome of Drosophila melanogaster In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community. Resources * Universal Proteomics Resource: Search for clones for expression and tissue culture * Materials: Request genomic or cDNA clones, library filters or fly stocks * Download Sequence data sets and annotations in fasta or xml format by http or ftp * Publications: Browse or download BDGP papers * Methods: BDGP laboratory protocols and vector maps * Analysis Tools: Search sequences for CRMs, promoters, splice sites, and gene predictions * Apollo: Genome annotation viewer and editor September 15, 2009 Illumina RNA-Seq data from 30 developmental time points of D. melanogaster has been submitted to the Short Read Archive at NCBI as part of the modENCODE project. The data set currently contains 2.2 billion single-end and paired reads and over 201 billion base pairs.

Proper citation: Berkeley Drosophila Genome Project (RRID:SCR_013094) Copy   

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http://pingstudy.ucsd.edu/

A large multi-site pediatric MRI and genetics data resource to facilitate studies of the genomic landscape of the developing human brain. It includes information about the developing mental and emotional functions of the children to understand the genetic basis of individual differences in brain structure and connectivity, cognition, and personality. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined. Investigators interested in the effects of a particular gene will be able to search the database for any brain areas or connections between areas that differ as a function of variation in a particular gene, and also to determine if the genes appear to affect the course of brain development at some point during childhood. A data exploration tool has been created for mapping and analyzing MRI data sets collected for PING and related developmental studies. Approved investigators will be able to view raw image sets and derived 3D brain maps of MRI and DTI data, conduct hypothesis testing, and graph brain area measures as they change across the time course of development. PING Cores * Coordinating Core: Functions include project management, screening of participants and maintaining the database * Neuroimaging Core: applying a standardized high-resolution structural MRI protocol involving 3-D T1-weighted scans, a T2-weighted volume, and a set of diffusion-weighted scans with multiple b values and diffusion directions, scans to estimate MRI relaxation rates, and gradient echo EPI scans for resting state fMRI. Importantly, adaptive motion compensation, using ����??PROMO����??, a novel real-time motion correction algorithm will be used. Specific PING protocols for each scanner manufacturer: ** PING MRI Protocol - GE ** PING MRI Protocol - Philips ** PING MRI Protocol - Siemens * Assessment Core: Cognitive assessments for the PING project are conducted using the NIH Toolbox for Cognition. * Genomics Core: functions as a central repository for receipt of saliva samples collected for each study participant. Once received, samples are catalogued, maintained, and DNA is extracted using state-of-the-field laboratory techniques. Ultimately, genome-wide genotyping is performed on the extracted DNA using the Illumina Human660W-Quad BeadChip. PING involves 10 sites throughout the country including UCSD, University of Hawaii, Scripps Genomics, UCLA, UC Davis, Kennedy Krieger Institute/Johns Hopkins, Sacker Institute/Cornell University, University of Massachusetts, Massachusetts General Hospital/Harvard, and Yale. Families who may want to participate in the study, or others who want to know more about it, may email questions to ping (at) ucsd.edu.

Proper citation: Pediatric Imaging Neurocognition and Genetics (RRID:SCR_008953) Copy   

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http://netage-project.org/

Database that contains gene sets and microRNA-regulated protein-protein interaction networks for longevity, age-related diseases and aging-associated processes.

Proper citation: NetAge Database (RRID:SCR_010224) Copy   

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http://www.snps3d.org/

A website which assigns molecular functional effects of non-synonymous SNPs based on structure and sequence analysis.

Proper citation: SNPs3D (RRID:SCR_010787) Copy   

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http://www.cancerrxgene.org/

A genomics database project is an academic research program to identify molecular features of cancers that predict response to anti-cancer drugs.

Proper citation: Genomics of Drug Sensitivity in Cancer (RRID:SCR_011956) Copy   

•   Source: SciCrunch Registry

http://cbbiweb.uthscsa.edu/KMethylomes/

Datbase and web-based system for visualization and analysis of genome-wide methylation data of human cancers.

Proper citation: Cancer Methylome System (RRID:SCR_012013) Copy   

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http://tcm.lifescience.ntu.edu.tw/index.html

TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.

Proper citation: TCMGeneDIT (RRID:SCR_013396) Copy   

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http://www.treefam.org

A database of phylogenetic trees of animal genes. It aims at developing a curated resource that gives reliable information about ortholog and paralog assignments, and evolutionary history of various gene families. TreeFam defines a gene family as a group of genes that evolved after the speciation of single-metazoan animals. It also tries to include outgroup genes like yeast (S. cerevisiae and S. pombe) and plant (A. thaliana) to reveal these distant members.TreeFam is also an ortholog database. Unlike other pairwise alignment based ones, TreeFam infers orthologs by means of gene trees. It fits a gene tree into the universal species tree and finds historical duplications, speciations and losses events. TreeFam uses this information to evaluate tree building, guide manual curation, and infer complex ortholog and paralog relations.The basic elements of TreeFam are gene families that can be divided into two parts: TreeFam-A and TreeFam-B families. TreeFam-B families are automatically created. They might contain errors given complex phylogenies. TreeFam-A families are manually curated from TreeFam-B ones. Family names and node names are assigned at the same time. The ultimate goal of TreeFam is to present a curated resource for all the families. phylogenetic tree, animal, vertebrate, invertebrate, gene, ortholog, paralog, evolutionary history, gene families, single-metazoan animals, outgroup genes like yeast (S. cerevisiae and S. pombe), plant (A. thaliana), historical duplications, speciations, losses, Human, Genome, comparative genomics

Proper citation: Tree families database (RRID:SCR_013401) Copy   

•   Source: SciCrunch Registry

http://tubic.tju.edu.cn/greglist/

A database listing potential G-quadruplex regulated genes. G-rich DNA sequences can form G-quadruplexes, a four-stranded structure that is stabilized by planar arrays of four guanines associated with hydrogen bonds. Promoter G-quadruplexes have emerged as a new way to regulate gene transcription, such as in c-MYC expression. Further, G-quadruplex motifs are highly enriched in gene promoter regions in humans and other mammals. Greglist contains genes whose promoter regions have G-quadruplex motifs, and these genes are highly likely to be regulated by G-quadruplexes.

Proper citation: Greglist (RRID:SCR_013407) Copy   

•   Source: SciCrunch Registry

http://www.fugu-sg.org/

THIS RESOURCE IS NO LONGER IN SERVICE,documented on August 16, 2019. Fugu genome is among the smallest vertebrate genomes and has proved to be a valuable reference genome for identifying genes and other functional elements such as regulatory elements in the human and other vertebrate genomes, and for understanding the structure and evolution of vertebrate genomes. This site presents version 4 of the Fugu genome, released in October 2004 by the International Fugu Genome Consortium. Fugu rubripes has a very compact genome, with less than 15 consisting of dispersed repetitive sequence, which makes it ideal for gene discovery. A draft sequence of the fugu genome was determined by the International Fugu Genome Consortium in 2002 using the ''whole-genome shotgun'' sequencing strategy. Fugu is the second vertebrate genome to be sequenced, the first being the human genome. This webpage presents the annotation made on the fourth assembly by the IMCB team using the Ensembl annotation pipeline. We are continuing with the gap filling work and linking of the scaffolds to obtain super-contigs.

Proper citation: Fugu Genome Project (RRID:SCR_013014) Copy   

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http://dorina.mdc-berlin.de/rbp_browser/dorina.html

In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.

Proper citation: doRiNA (RRID:SCR_013222) Copy   

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http://agem.cnb.csic.es/VisualOmics/aGEM/

Database platform of an integrated view of eight databases (mouse gene expression resources: EMAGE, GXD, GENSAT, BioGPS, ABA, EUREXPRESS; human gene expression databases: HUDSEN, BioGPS and Human Protein Atlas) that allows the experimentalist to retrieve relevant statistical information relating gene expression, anatomical structure (space) and developmental stage (time). Moreover, general biological information from databases such as KEGG, OMIM and MTB is integrated too. It can be queried using gene and anatomical structure. Output information is presented in a friendly format, allowing the user to display expression maps and correlation matrices for a gene or structure during development. An in-depth study of a specific developmental stage is also possible using heatmaps that relate gene expression with anatomical components. This is a powerful tool in the gene expression field that makes easy the access to information related to the anatomical pattern of gene expression in human and mouse, so that it can complement many functional genomics studies. The platform allows the integration of gene expression data with spatial-temporal anatomic data by means of an intuitive and user friendly display., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: aGEM (RRID:SCR_013349) Copy   

•   Source: SciCrunch Registry

http://proline.bic.nus.edu.sg/dedb/

Database on Drosophila melanogaster exons presented in a splicing graph form. Data is based on release 3.2 of the Drosophila melanogaster genome annotations available at FlyBase. The gene structure information extracted from the annotations were checked, clustered and transformed into splicing graph. The splicing graph form of the gene constructs were then used for classification of the various types of alternative splicing events. In addition, Pfam domains were mapped onto the gene structure. Users can query the database using the query page using BLAST, FlyBase Gene Name, FlyBase Gene Symbol, Pfam Accession Number and Pfam Identifier. This allows users to determine the Drosophila melanogaster homology of their gene using a BLAST search and to visualize the alternative splicing variants if any. Users can also determine genes containing a particular domain using the Pfam Accession Numbers and Identifiers.

Proper citation: Drosophila melanogaster Exon Database (RRID:SCR_013441) Copy   

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http://rarge.psc.riken.jp/rartf/

Database of complete sets of Arabidopsis transcription factors with a variety of information on Arabidopsis thaliana transcription factor families including: full-length cDNA sequences, Ds-tagged mutants, multiple sequences alignments of family members, phylogenic trees, functional motifs, and so on. In addition, expression profiles of all transcription factor genes are available.

Proper citation: RARTF (RRID:SCR_013457) Copy   

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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://interactome-cmp.ucsf.edu/

This database currently holds E-MAP scores (individual interactions and correlation coefficients) for budding yeast genes involved in the early secretory pathway and chromosome function (including DNA damage and repair, transcriptional control, chromosome segregation and telomere regulation). E-MAPs (Epistatic Mini Array Profiles) are formed by creating and quantifying high-density genetic interaction maps. With this method, observed double mutant colony sizes are compared to those that would be expected from a distribution of typical double mutant colonies of each strain. Each interaction is assigned a score, which indicates the magnitude of the difference from the expected value and the certainty of the score. Negative (or aggravating) scores (< -2.5) correspond to synthetic sick/lethal interactions while positive (or alleviating) scores (> +2.5) corresponds to epistatic or suppressor interactions.

Proper citation: Krogan Lab Interactome Database (RRID:SCR_008121) Copy   

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http://escience.invitrogen.com/ipath/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. LINNEA Pathways is a user-friendly comprehensive online resource for gene- or protein-based scientific research. It is based on a total of 248 signaling and metabolic human biological pathway maps created for Invitrogen by GeneGo. The current version of iPath features 225 maps displaying human regulatory and metabolic pathways established in experimental literature produced by MetaCore from GeneGo, Inc. The map objects (proteins, genes, EC functions, and compounds) are connected via metabolic transformations and physical protein interactions, which were assembled by the GeneGo team of experienced annotators, geneticists, and biochemists. The pathways are organized in a vertical fashion following the general signaling path from signaling molecules and membrane receptors, via signal transduction cascades, to transcription factors and their gene targets. Following the natural organization of cellular machinery with highly interconnected pathways and modules, many maps are linked together via hyperlinked box symbols. Such linkage allows the reconstruction of a big picture view of human cell biology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Invitrogen iPath (RRID:SCR_008120) Copy   

•   Source: SciCrunch Registry

http://itfp.biosino.org/itfp/

ITFP is an integrated transcription factor (TF) platform, which included abundant TFs and targets message of mammalian. Support vector machine (SVM) algorithm combined with error-correcting output coding (ECOC) algorithm was utilized to identify and classify transcription factor from protein sequence of Human, Mouse and Rat. For transcription factor targets, a reverse engineering method named ARACNE was used to derive potential interaction pairs between transcription factor and downstream regulated gene from Human, Mouse and Rat gene expression profile data. Detailed information of gene expression profile data can be found in help page. Moreover, all data provided by the platform is free for non-commercial users and can be downloaded through links on help page.

Proper citation: Intergrated Transcription Factor Platform (RRID:SCR_008119) Copy   

•   Source: SciCrunch Registry