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1.
Nucleic Acids Res ; 46(D1): D1181-D1189, 2018 01 04.
Artigo em Inglês | MEDLINE | ID: mdl-29165610

RESUMO

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.


Assuntos
Bases de Dados Genéticas , Regulação da Expressão Gênica de Plantas , Genômica/métodos , Bases de Conhecimento , Plantas/genética , Epigênese Genética , Ontologia Genética , Pesquisa em Genética , Variação Genética , Genoma de Planta , Redes e Vias Metabólicas/genética , Anotação de Sequência Molecular , Plantas/metabolismo , Software , Interface Usuário-Computador
2.
Nucleic Acids Res ; 45(D1): D985-D994, 2017 01 04.
Artigo em Inglês | MEDLINE | ID: mdl-27899665

RESUMO

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.


Assuntos
Biologia Computacional/métodos , Terapia de Alvo Molecular , Ferramenta de Busca , Software , Bases de Dados Factuais , Humanos , Terapia de Alvo Molecular/métodos , Reprodutibilidade dos Testes , Navegador , Fluxo de Trabalho
3.
Comput Struct Biotechnol J ; 19: 4336-4344, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34429851

RESUMO

A fundamental issue related to the understanding of the molecular mechanisms, is the way in which common pathways act across different biological experiments related to complex diseases. Using network-based approaches, this work aims to provide a numeric characterization of pathways across different biological experiments, in the prospect to create unique footprints that may characterise a specific disease under study at a pathway network level. In this line we propose PathExNET, a web service that allows the creation of pathway-to-pathway expression networks that hold the over- and under expression information obtained from differential gene expression analyses. The unique numeric characterization of pathway expression status related to a specific biological experiment (or disease), as well as the creation of diverse combination of pathway networks generated by PathExNET, is expected to provide a concrete contribution towards the individualization of disease, and further lead to a more precise personalised medicine and management of treatment. PathExNET is available at: https://bioinformatics.cing.ac.cy/PathExNET and at https://pathexnet.cing-big.hpcf.cyi.ac.cy/.

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