Tools   Select Another Resource Report Type

http://enhancer.lbl.gov/

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/genbank/dbest/

Database as a division of GenBank that contains sequence data and other information on single-pass cDNA sequences, or Expressed Sequence Tags, from a number of organisms.

Proper citation: dbEST (RRID:SCR_008132) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

•   Source: SciCrunch Registry

http://www.baderlab.org/Software/ActiveDriver

A statistical method for interpreting variations in protein sequence (e.g. coding SNPs in the population, SNVs in cancer genomes) in the context of protein post-translational signaling modifications.

Proper citation: ActiveDriver (RRID:SCR_008104) Copy   

•   Source: SciCrunch Registry

http://qiime.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.

Proper citation: QIIME (RRID:SCR_008249) Copy   

•   Source: SciCrunch Registry

http://griffin.cbrc.jp/

Griffin (G-protein-receptor interacting feature finding instrument) is a high-throughput system to predict GPCR - G-protein coupling selectively with the input of GPCR sequence and ligand molecular weight. This system consists of two parts: 1) HMM section using family specific multiple alignment of GPCRs, 2) SVM section using physico-chemical feature vectors in GPCR sequence. G-protein coupled receptors (GPCR), which is composed of seven transmembrane helices, play a role as interface of signal transduction. The external stimulation for GPCR, induce the coupling with G-protein (Gi/o, Gq/11, Gs, G12/13) followed by different kinds of signal transduction to inner cell. About half of distributed drugs are intending to control this GPCR - G-protein binding system, and therefore this system is important research target for the development of effective drug. For this purpose, it is necessary to monitor, effectively and comprehensively, of the activation of G-protein by identifying ligand combined with GPCR. Since, at present, it is difficult to construct such biochemical experiment system, if the answers for experimental results can be prepared beforehand by using bioinformatics techniques, large progress is brought to G-protein related drug design. Previous works for predicting GPCR-G protein coupling selectivity are using sequence pattern search, statistical models, and HMM representations showed high sensitivity of predictions. However, there are still no works that can predict with both high sensitivity and specificity. In this work we extracted comprehensively the physico-chemical parameters of each part of ligand, GPCR and G-protein, and choose the parameters which have strong correlation with the coupling selectivity of G-protein. These parameters were put as a feature vector, used for GPCR classification based on SVM.

Proper citation: G protein receptor interaction feature finding instrument (RRID:SCR_008343) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=gma

Software package to perform Granger mediation analysis for time series. Includes single level GMA model and two-level GMA model, for time series with hierarchically nested structure.

Proper citation: GMA (RRID:SCR_009212) Copy   

•   Source: SciCrunch Registry

http://clipserve.clip.ubc.ca/topfind

An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data

Proper citation: TopFIND (RRID:SCR_008918) Copy   

•   Source: SciCrunch Registry

http://go.princeton.edu/cgi-bin/GOTermFinder

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://pages.stat.wisc.edu/~yandell/qtl/software/qtlbim/

Software library for QTL Bayesian Interval Mapping that provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits. (entry from Genetic Analysis Software)

Proper citation: R/QTLBIM (RRID:SCR_009375) Copy   

•   Source: SciCrunch Registry

https://dogma.ccbb.utexas.edu/

Web-based annotation tool for plant chloroplasts and animal mitochondrial genomes. DOGMA allows the use of BLAST searches against a custom database, and conservation of basepairing in the secondary structure of animal mitochondrial tRNAs to identify and annotate genes.

Proper citation: DOGMA (RRID:SCR_015060) Copy   

•   Source: SciCrunch Registry

http://www.mybiosoftware.com/seaview-4-2-12-sequence-alignment-phylogenetic-tree-building.html

Graphical user interface for multiple sequence alignment and molecular phylogeny. SeaView also generates phylogenetic trees.

Proper citation: SeaView (RRID:SCR_015059) Copy   

•   Source: SciCrunch Registry

http://busco.ezlab.org/

Software tool to quantitatively measure genome assembly and annotation completeness based on evolutionarily informed expectations of gene content.

Proper citation: BUSCO (RRID:SCR_015008) Copy   

•   Source: SciCrunch Registry

http://floresta.eead.csic.es/primers4clades

Web application for the design of PCR primers for cross-species amplification of novel sequences from metagenomic DNA or from uncharacterized organisms belonging to user-specified phylogenetic lineages. It implements an extended CODEHOP strategy and evaluates thermodynamic properties of the oligonucleotide pairs.

Proper citation: primers4clades (RRID:SCR_015714) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/clustergrammer/

Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps. Clustergrammer enables intuitive exploration of high-dimensional data and has several optional biology-specific features.

Proper citation: clustergrammer (RRID:SCR_015681) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/oligo.html

Software package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

Proper citation: oligo (RRID:SCR_015729) Copy   

•   Source: SciCrunch Registry

https://github.com/BGI-SZ/BSVF

Software code for bisulfite sequencing virus integration. This finder is for directional libraries only and does not support PBAT and indirectional libraries.

Proper citation: BSVF (RRID:SCR_015727) Copy   

•   Source: SciCrunch Registry

http://www.genepattern-notebook.org/

Interactive analysis notebook environment that streamlines genomics research by interleaving text, multimedia, and executable code into unified, sharable, reproducible “research narratives.” It integrates the dynamic capabilities of notebook systems with an investigator-focused, simple interface that provides access to hundreds of genomic tools without the need to write code.

Proper citation: GenePattern Notebook (RRID:SCR_015699) Copy   

•   Source: SciCrunch Registry