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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 6 showing 101 ~ 120 out of 1,660 results
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  • RRID:SCR_012095

    This resource has 1+ mentions.

https://code.google.com/p/netcoffee/

A fast and accurate algorithm which allows to find a global alignment of multiple protein-protein interaction networks.

Proper citation: NetCoffee (RRID:SCR_012095) Copy   


  • RRID:SCR_012120

https://code.google.com/p/cell-motility/

An open source Java application that provides a clear and concise analysis workbench for large amounts of cell motion data.

Proper citation: Cell motility (RRID:SCR_012120) Copy   


  • RRID:SCR_012125

http://sourceforge.net/projects/isdtool/files/ISDTool-2.0/

Software that implements a computational model for predicting immunosuppressive domains (ISDs). The software could be used to identify typical ISDs in retroviruses including HERV, HTLV, HIV, STLV, SIV and MLV.

Proper citation: ISDTool (RRID:SCR_012125) Copy   


  • RRID:SCR_012148

    This resource has 100+ mentions.

http://sourceforge.net/projects/ngopt/

Software that produces high quality microbial genome assemblies on a laptop computer without any parameter tuning. A5-miseq does this by automating the process of adapter trimming, quality filtering, error correction, contig and scaffold generation, and detection of misassemblies. Unlike the original A5 pipeline, A5-miseq can use long reads from the Illumina MiSeq, use read pairing information during contig generation, and includes several improvements to read trimming.

Proper citation: A5-miseq (RRID:SCR_012148) Copy   


  • RRID:SCR_012132

    This resource has 100+ mentions.

http://sourceforge.net/projects/plek/

An alignment-free software tool which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. It is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data.

Proper citation: PLEK (RRID:SCR_012132) Copy   


  • RRID:SCR_012133

    This resource has 100+ mentions.

https://code.google.com/p/reditools/

A suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data.

Proper citation: REDItools (RRID:SCR_012133) Copy   


  • RRID:SCR_012137

    This resource has 100+ mentions.

https://code.google.com/p/icelogo/

Software that builds on probability theory to visualize significant conserved sequence patterns in multiple peptide sequence alignments against background (reference) sequence sets that can be tailored to the studied system and the used protocol.

Proper citation: iceLogo (RRID:SCR_012137) Copy   


  • RRID:SCR_012140

https://code.google.com/p/automotifserver/

Software that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The source code and precompiled binaries of brainstorming tool are available under Apache licensing.

Proper citation: AMS (RRID:SCR_012140) Copy   


  • RRID:SCR_012142

http://sourceforge.net/projects/phosphosite/

A bioinformatical software tool for analyzing (quantitative) phosphoproteome datasets. The program retrieves kinase-substrate predictions from NetworKIN and contains various statistical modules for futher analysis.

Proper citation: PhosphoSiteAnalyzer (RRID:SCR_012142) Copy   


  • RRID:SCR_008375

http://bioinfo.cipf.es/isacghtrac

Software to analyze CNV that will now normalize arrays CGH and it will visually integrate different genome annotations.

Proper citation: IsaCGH (RRID:SCR_008375) Copy   


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   


  • RRID:SCR_008421

    This resource has 10+ mentions.

http://mothra.ornl.gov/cgi-bin/cat/cat.cgi

A repository of tools for analysis and annotation of CAZYmes (Carbohydrate Active enZYmes)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CAT (RRID:SCR_008421) Copy   


  • RRID:SCR_008870

    This resource has 100+ mentions.

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   


  • RRID:SCR_008906

    This resource has 10+ mentions.

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   


  • RRID:SCR_009212

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   


  • RRID:SCR_008918

    This resource has 10+ mentions.

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   


  • RRID:SCR_008910

http://bioinformatics.fccc.edu/software/OpenSource/FGDP/FGDP.shtml

A Java-based, Microarray or Genechip data analysis system.

Proper citation: FGDP (RRID:SCR_008910) Copy   


  • RRID:SCR_008966

    This resource has 50+ mentions.

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   


  • RRID:SCR_009375

    This resource has 1+ mentions.

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   


  • RRID:SCR_005376

    This resource has 1+ mentions.

https://code.google.com/p/knime4bio/

A set of custom nodes for the KNIME (The Konstanz Information Miner) graphical workbench, for analysing next-generation sequencing (NGS) data without the requirement of programming skills.

Proper citation: Knime4Bio (RRID:SCR_005376) Copy   



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