Publicação
Development of web-based tools for spectral data analysis and mining
| Resumo: | The recent advances in different analytical techniques able to produce spectral data, including Raman, Infrared (IR) or Ultraviolet-Visible (UV-vis) spectroscopies, have provided novel approaches for many research issues in the biological and chemical fields. Indeed, they have allowed to address tasks in functional genomics, sample characterization and classification, or drug discovery. To take full advantage of these data, advanced bioinformatics methods are required for data analysis and mining. A number of methods and tools for spectral data analysis have been put forward recently, being one of the major limitations still faced the lack of integrated frameworks for extracting relevant knowledge from these data and being able to integrate these data with previous biochemical knowledge. Also, the lack of reproducibility in many data analysis or data mining processes is a strong obstacle for biological discovery, being common the lack of data and data analysis pipelines in the published work. In recent work from the host group, specmine, a metabolomics and spectral data analysis/ mining framework, in the form of a package for the R system, has been developed to address some of these issues. In this thesis, the main aim was to design and develop an integrated web-based platform for spectral data analysis and mining, based on the specmine package, providing an easier and more user friendly interface, but also addressing some of the package’s current limitations. The developed platform contains features that cover the main steps of the metabolomics data analysis workflow, with modules for data reading and dataset creation, data preprocessing and a variety of analysis types. It includes an authentication system, allowing the user to have his own personal workspace where projects can be stored and accessed later, with the option to share projects with other users. The different modules were validated using real data from previously published studies in the host group, related to the analysis of the characteristics and potential of natural products, addressing as well the exploration and integration of data from distinct experimental techniques, attesting the platform’s robustness and utility. |
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| Autores principais: | Afonso, Telma Adriana Pereira |
| Assunto: | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The recent advances in different analytical techniques able to produce spectral data, including Raman, Infrared (IR) or Ultraviolet-Visible (UV-vis) spectroscopies, have provided novel approaches for many research issues in the biological and chemical fields. Indeed, they have allowed to address tasks in functional genomics, sample characterization and classification, or drug discovery. To take full advantage of these data, advanced bioinformatics methods are required for data analysis and mining. A number of methods and tools for spectral data analysis have been put forward recently, being one of the major limitations still faced the lack of integrated frameworks for extracting relevant knowledge from these data and being able to integrate these data with previous biochemical knowledge. Also, the lack of reproducibility in many data analysis or data mining processes is a strong obstacle for biological discovery, being common the lack of data and data analysis pipelines in the published work. In recent work from the host group, specmine, a metabolomics and spectral data analysis/ mining framework, in the form of a package for the R system, has been developed to address some of these issues. In this thesis, the main aim was to design and develop an integrated web-based platform for spectral data analysis and mining, based on the specmine package, providing an easier and more user friendly interface, but also addressing some of the package’s current limitations. The developed platform contains features that cover the main steps of the metabolomics data analysis workflow, with modules for data reading and dataset creation, data preprocessing and a variety of analysis types. It includes an authentication system, allowing the user to have his own personal workspace where projects can be stored and accessed later, with the option to share projects with other users. The different modules were validated using real data from previously published studies in the host group, related to the analysis of the characteristics and potential of natural products, addressing as well the exploration and integration of data from distinct experimental techniques, attesting the platform’s robustness and utility. |
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