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| Author(s): |
Juan Manuel Vidal Garcia
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) |
| Defense date: | 2016-10-13 |
| Examining board members: |
André Fujita;
Benilton de Sá Carvalho;
Silvia Yumi Bando Takahara
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| Advisor: | André Fujita |
| Abstract | |
One of the theoretical and methodological foundations of systems biology is the search and interpretation of the relationships between biomolecules that take place inside the cell and that maintains its functioning. Those relationships may exist either, between molecules of the same nature, for example between proteins, or between molecules of a different nature such as DNA-protein. Of all possible relationships, gene-gene relationships have been extensively studied using two methods: correlating genetic expression values from different measures of statistical dependence, or using biotechnological techniques such as genetic interactions that identify relationships between genes by measuring the phenotypic effect of mutations or deletions of target genes. Regardless of whether they are different techniques, what is sought in both cases are to identify functional relationships that may exist between a pair of genes. This conceptual similarity makes it possible to compare the results of this two strategies in order to assess the proportion of functional relationships that are simultaneously identified by measures of dependence and genetic interactions. To carry out such a comparison, the Pearson and Spearman dependency measures were used here to obtain the co-expression networks of three sets of Saccharomyces cerevisiae gene expression data. The functional relations obtained in the previous step were compared with those relations obtained by the technique of genetic interactions that are available in the two main databases. As a result of these comparisons, it was observed that although the two techniques are designed with the same objective (to identify functional relations between genes), the number of relations that are common to the two methodologies studied is very low. Both the difference in the techniques of obtaining relationships and the absence of a specific definition about what is a functional relationship can be the main causes of the low level of relationship between this two strategies. (AU) | |
| FAPESP's process: | 12/25460-1 - Deciphering gene regulatory networks: interpreting correlations, dependence and causality in biological networks |
| Grantee: | Juan Manuel Vidal García |
| Support Opportunities: | Scholarships in Brazil - Master |