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on page 1 showing 20 out of 99 results from 1 sources

Cite this (APID: Agile Protein Interaction DataAnalyzer, RRID:SCR_008871)

URL: http://bioinfow.dep.usal.es/apid

Resource Type: Resource, data analysis service, database, analysis service resource, production service resource, service resource, data or information resource

An interactive bioinformatics web tool developed to integrate and analyze in a unified and comparative platform known information about protein-protein interactions demonstrated by specific small-scale or large-scale experimental methods. At present, the application includes information coming from five main source databases enclosing an unified sever to explore more than 40000 different proteins and close to 150000 different proven interactions. The website includes search tools to query and browse upon the data, allowing selection of the interaction pairs based in calculated parameters that weight and qualify the reliability of each given protein interaction. Parameters for the proteins are connectivity, cluster coefficient, Gene Ontology (GO) functional environment, GO environment enrichment; for the interactions: number of methods, GO overlapping, Pfam domain-domain interaction. APID also includes a graphic interactive tool to visualize selected sub-networks and to navigate on them or along the whole interaction network. Platform: Online tool

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Cite this (BiNGO: A Biological Networks Gene Ontology tool, RRID:SCR_005736)

URL: http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html

Resource Type: Resource, software resource

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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    BioPerl

Cite this (BioPerl, RRID:SCR_002989)

URL: http://www.bioperl.org

Resource Type: Resource, wiki, source code, narrative resource, software repository, software resource, software toolkit, data or information resource

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (Blip: Biomedical Logic Programming, RRID:SCR_005733)

URL: http://www.blipkit.org/

Resource Type: Resource, software resource

Biomedical Logical Programming (Blip) is a research-oriented deductive database and prolog application library for handling biological and biomedical data. It includes packages for advanced querying of ontologies and annotations. Blip underpins the Obol tool. Here are some distinguishing characteristics of Blip * Lightweight. Bloat-free: Blip only has as many modules as it needs to do its job. * Fast. * Declarative. Say what you want to do, not how you want to do it * Blip can be Query-oriented: specify your data sources and ask your query * Blip can be Application-oriented: it is designed to be used as an application library used by other bioinformatics tools * Mature and fully functional ontology module for handling both OBO-style ontologies and OWL ontologies. * Modules for handling biological sequences and sequence features. (currently limited functionality, added as needed) * A systems biology module for querying pathway and interaction data. (currently limited functionality, added as needed) * Relational database integration. SQL can be viewed as a highly restricted dialect of Prolog. Although the SWI-Prolog in-memory database is fast and scalable, sometimes it is nice to be able to fetch data from an external database. Blip contains a generic SQL utility module and predicate mappings for the GO database, Ensembl and Chado * Integration with a variety of bioinformatics file formats. SWI-Prolog has a variety of fast libraries for dealing with XML, RDF and tabular data files. Blip provides bridges from bio file formats encoded using these syntaxes into its native models. For other syntaxes, Blip seamlessly integrates other packages such as BioPerl and go-perl. Although these dependencies require extra installation, there is no point reinventing the wheel * Rapid development of web applications. Blip extends SWI-Prolog''''s excellent http support with a simple and powerful logical-functional-programming style application server, serval. This has been used to prototype a fully-featured next-generation replacement for the GO project amigo browser. * Scalable. Blip is not intended to be a toy system on toy data (although it is happy to be used as a toy if you like!). It is intended to be used as an application component and a tool operating on real-world biological and biomedical data Blip is written in SWI-Prolog, a fast, robust and scalable implementation of ISO Prolog. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (CateGOrizer, RRID:SCR_005737)

URL: http://www.animalgenome.org/bioinfo/tools/catego/

Resource Type: Resource, analysis service resource, data analysis service, service resource, production service resource

CateGOrizer takes batch input of GO term IDs in a list format or unformatted plain text file, allows users to choose one of the available classifications such as GO_slim, GOA, EGAD, MGI_GO_slim, GO-ROOT, or a self-defined classification list, find its parental branch and performs an accumulative classification count, and returns the results in a sorted table of counts, percentages, and a pie chart (if it takes longer than standard time out period, it will email the user with a URL link to the results). This tool is comprised with a set of perl CGI programs coupled with a MySQL DBMS that stores the GO terms DAG data. Platform: Online tool

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Cite this (CGAP GO Browser, RRID:SCR_005676)

URL: http://cgap.nci.nih.gov/Genes/GOBrowser

Resource Type: Resource, data set, service resource, data or information resource

With the CGAP GO browser, you can browse through the GO vocabularies, and find human and mouse genes assigned to each term. GO data updated every few months. Platform: Online tool

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Cite this (CLASSIFI - Cluster Assignment for Biological Inference, RRID:SCR_005752)

URL: http://www.utsouthwestern.edu/education/medical-school/departments/pathology/pathdb/classifi.html

Resource Type: Resource, analysis service resource, data analysis service, service resource, production service resource

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 10, 2012. Cluster Assignment for Biological Inference (CLASSIFI) is a data-mining tool that can be used to identify significant co-clustering of genes with similar functional properties (e.g. cellular response to DNA damage). Briefly, CLASSIFI uses the Gene Ontology gene annotation scheme to define the functional properties of all genes/probes in a microarray data set, and then applies a cumulative hypergeometric distribution analysis to determine if any statistically significant gene ontology co-clustering has occurred. Platform: Online tool

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    CLENCH

Cite this (CLENCH, RRID:SCR_005735)

URL: http://www.stanford.edu/~nigam/cgi-bin/dokuwiki/doku.php?id=clench

Resource Type: Resource, software resource, software application, data processing software, source code

Cluster Enrichment (CLENCH) allows A. thaliana researchers to perform automated retrieval of GO annotations from TAIR and calculate enrichment of GO terms in gene group with respect to a reference set. Before calculating enrichment, CLENCH allows mapping of the returned annotations to arbitrary coarse levels using GO slim term lists (which can be edited by the user) and a local installation of GO. Platform: Windows compatible, Linux compatible,

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    ClueGO

Cite this (ClueGO, RRID:SCR_005748)

URL: http://www.ici.upmc.fr/cluego/

Resource Type: Resource, software resource

A Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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    COBrA

Cite this (COBrA, RRID:SCR_005677)

URL: http://www.xspan.org/

Resource Type: Resource, software resource

COBrA is a Java-based ontology editor for bio-ontologies that distinguishes itself from other editors by supporting the linking of concepts between two ontologies, and providing sophisticated analysis and verification functions. In addition to the Gene Ontology and Open Biology Ontologies formats, COBrA can import and export ontologies in the Semantic Web formats RDF, RDFS and OWL. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (DBD - Slim Gene Ontology, RRID:SCR_005728)

URL: http://www.dbfordummies.com/go.asp

Resource Type: Resource, software resource, software application, data or information resource, database

Db for Dummies! is a small database that imports the Generic GO Slim. It allows data to be viewed in a tree. The Gene Ontology describes gene products in terms of their associated biological processes, cellular components and molecular functions. The Generic Slim Gene Ontology is a subset of the whole Gene Ontology. The slim version gives a broad overview and leaves out specific/fine grained terms. This example stores the slim version of the Gene Ontology (goslim_generic_obo) that can be downloaded from www.geneontology.org/GO.slims.shtml. Platform: Windows compatible

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    DynGO

Cite this (DynGO, RRID:SCR_007009)

URL: http://www.softpedia.com/get/Science-CAD/DynGO.shtml

Resource Type: Resource, software resource

DynGO is a client-server application that provides several advanced functionalities in addition to the standard browsing capability. DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations (which requires more disk and memory to handle the semantic retrieval). The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Requirements: Java Platform: Windows compatible, Linux compatible, Unix compatible

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Cite this (elk-reasoner, RRID:SCR_008913)

URL: http://code.google.com/p/elk-reasoner/

Resource Type: Resource, software resource

ELK is an ontology reasoner with the goal of supporting the OWL 2 EL profile. ELK is a specialized reasoner for the lightweight ontology language OWL EL. The practical utility of ELK is in its combination of high performance and comprehensive support for language features. At its core, ELK employs a consequence-based reasoning engine that can take advantage of multi-core and multi-processor systems. A modular architecture allows ELK to be used as a stand-alone application, Protege plug-in, or programming library (either with or without the OWL API).

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    ErmineJ

Cite this (ErmineJ, RRID:SCR_006450)

URL: http://bioinformatics.ubc.ca/ermineJ/

Resource Type: Resource, software resource, software application, data analysis software, data processing software

Data analysis software for gene sets in expression microarray data or other genome-wide data that results in rankings of genes. A typical goal is to determine whether particular biological pathways are doing something interesting in the data. The software is designed to be used by biologists with little or no informatics background. A command-line interface is available for users who wish to script the use of ermineJ. Major features include: * Implementation of multiple methods for gene set analysis: ** Over-representation analysis ** A resampling-based method that uses gene scores ** A rank-based method that uses gene scores ** A resampling-based method that uses correlation between gene expression profiles (a type of cluster-enrichment analysis). * Gene sets receive statistical scores (p-values), and multiple test correction is supported. * Support of the Gene Ontology terminology; users can choose which aspects to analyze. * User files use simple text formats. * Users can modify gene sets or create new ones. * The results can be visualized within the software. * It is simple to compare multiple analyses of the same data set with different settings. * User-definable hyperlinks are provided to external sites to allow more efficient browsing of the results. * For programmers, there is a command line interface as well as a simple application programming interface that can be used to plug ermineJ functionality into your own code Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (Expression Profiler, RRID:SCR_005821)

URL: http://www.ebi.ac.uk/expressionprofiler/

Resource Type: Resource, analysis service resource, data analysis service, service resource, production service resource

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

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Cite this (FastSemSim, RRID:SCR_006919)

URL: http://sourceforge.net/p/fastsemsim/home/Home/

Resource Type: Resource, software resource, software toolkit, software library

A package that implements several semantic similarity measures. It is both a library and an end-user application, featuring an intuitive graphical user interface (GUI). It has been implemented with the aim of being fast, expandable, and easy to use. It allows the user to work with the most updated version of GO database and customizable annotation corpora. It provides a set of logically-organized classes that can be easily exploited to both integrate semantic similarity into different analysis pipelines and extend the library with new measures. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (FIVA - Functional Information Viewer and Analyzer, RRID:SCR_005776)

URL: http://bioinformatics.biol.rug.nl/standalone/fiva/

Resource Type: Resource, software resource, software application, data processing software

Functional Information Viewer and Analyzer (FIVA) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software is able to assist in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes. Currently, seven different modules containing functional information have been implemented: (i) gene regulatory interactions, (ii) cluster of orthologous groups (COG) of proteins, (iii) gene ontologies (GO), (iv) metabolic pathways (v) Swiss Prot keywords, (vi) InterPro domains - and (vii) generic functional categories. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Cite this (Flash Gviewer, RRID:SCR_012870)

URL: http://gmod.org/wiki/Flash_GViewer

Resource Type: Resource, software resource

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

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Cite this (FuncExpression, RRID:SCR_005773)

URL: http://www.plexdb.org/plex.php?database=Barley/funcexpression.php

Resource Type: Resource, analysis service resource, data analysis service, service resource, production service resource

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 11, 2012. FuncExpression is a web-based resource for functional interpretation of large scale genomics data. FuncExpression can be used for the functional comparison of plant, animal, and fungal gene name lists generated from genomics and proteomics experiments. Multiple gene lists can be classified, compared and visualized. FuncExpression supports two way-integration of plant gene functional information and the gene expression data, which allows for further cross-validation with plant microarray data from related experiments at BarleyBase. Platform: Online tool

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Cite this (FunCluster, RRID:SCR_005774)

URL: http://corneliu.henegar.info/FunCluster.htm

Resource Type: Resource, software resource, software application, data analysis software, data processing software

FunCluster is a genomic data analysis algorithm which performs functional analysis of gene expression data obtained from cDNA microarray experiments. Besides automated functional annotation of gene expression data, FunCluster functional analysis aims to detect co-regulated biological processes through a specially designed clustering procedure involving biological annotations and gene expression data. FunCluster''''s functional analysis relies on Gene Ontology and KEGG annotations and is currently available for three organisms: Homo Sapiens, Mus Musculus and Saccharomyces Cerevisiae. FunCluster is provided as a standalone R package, which can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix). Download it from the FunCluster website, or from the worldwide mirrors of CRAN. FunCluster is provided freely under the GNU General Public License 2.0. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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