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| Author(s): |
Amanda Rusiska Piovezani
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) |
| Defense date: | 2017-12-14 |
| Examining board members: |
Marcos Silveira Buckeridge;
Igor Cesarino;
Ronaldo Fumio Hashimoto;
Gabriel Rodrigues Alves Margarido;
Milton Yutaka Nishiyama Junior
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| Advisor: | Marcos Silveira Buckeridge; Fabricio Martins Lopes |
| Abstract | |
Plant are sessile organisms, and their responses to environmental stimuli are orchestrated by genetic factors, as well as by their metabolic flexibility. Inside the cell, there are genetic and metabolic patterns responsible for cell redundancy, and that reflects on different organizational levels (cell, tissue, organ, until a whole organism). Thus, to understand plant responses to certain conditions, it is important to understanding different regulatory levels. Recently, there was a large increase in availability of biological data. This happened due to the advance in next-generation sequencing techniques, which now enables more profound system biology studies. Despite the availability of several integration tools for analysis of biological data, these were developed for organism modeling. However, such tools are partially effective for sugarcane, for which there are large amounts of data, but has incomplete genome data. Due to the economic importance of sugarcane and aiming at understanding cell wall degradation process, we develop the software Systems Integration Tool (SIT). The tool integrates available data (transcriptomics, proteomics, and enzymatic activity). The implementation was performed in Perl and Java. SIT has a graphical interface, standalone execution, enabling integration until six layers of data. Integration results are generated as complex networks, allowing the users to visualize and dynamically edit the networks. The present study allowed the identification of key cell wall regulatory elements present on different data sets pointing out to potential targets for experimental validation. SIT can be applied to various data sets being capable of helping future studies in different areas of knowledge. (AU) | |
| FAPESP's process: | 13/24205-0 - Development of a bioinformatic tool for integration of transcriptomics, proteomics and physiology using sorghum and sugarcane as model systems |
| Grantee: | Amanda Rusiska Piovezani |
| Support Opportunities: | Scholarships in Brazil - Doctorate |