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1.
Nucleic Acids Res ; 46(W1): W503-W509, 2018 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-29800320

RESUMO

The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org.


Assuntos
Regulação da Expressão Gênica , Redes e Vias Metabólicas/genética , Transdução de Sinais/genética , Software , Transcriptoma , Linhagem Celular Transformada , Reprogramação Celular , Gráficos por Computador , Fibroblastos/citologia , Fibroblastos/metabolismo , Genômica/métodos , Humanos , Internet , Metabolômica/métodos , Anotação de Sequência Molecular , Proteômica/métodos
2.
PLoS Comput Biol ; 13(9): e1005616, 2017 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-28910280

RESUMO

Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.


Assuntos
Pesquisa Biomédica/educação , Biologia Computacional/educação , Biologia Computacional/métodos , Software , África , Pesquisa Biomédica/organização & administração , Biologia Computacional/organização & administração , Computadores , Países em Desenvolvimento , Humanos , Interface Usuário-Computador
3.
BMC Syst Biol ; 8 Suppl 2: S9, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25033091

RESUMO

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures.


Assuntos
Biologia Computacional/métodos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Metabolômica , Proteômica , Software , Estatística como Assunto
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