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Identifying Core Genes in Estimation of Missing Gene Expressions

Darvish Shafighi, Shadi | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50715 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Motahari, Abolfazl
  7. Abstract:
  8. Characterizing cellular states in response to various disease conditions is an important issue which is addressed by different methods such as Large-scale gene expression profiling. One of the most important challenges in front of bioinformaticians is the loss of data because expression profiling is still very expensive. It is understood that profiling a group of selected genes could be enough for understanding all of the gene expression profile.In this research, we propose a fast method for estimation of the missing values inlow-rank matrices. We consider the highly correlated expression profiles as a low-rank matrix. Then, we used this new method in a proposed algorithm which will select the landmark genes and also estimate the target genes iteratively. The algorithm tries to enhance the representation of the landmark genes in each iteration.The proposed algorithm was successful compared to the related works. It could help in the process of lowering the expenses of the Large-scale gene-expression profiling. The improvement of the estimation error was 3.2 percent compare to the best method which is D-GEX.Also we capture the errors which are significant in both methods and find that we could reduce the significant errors 21 percent in comparison with D-GEX
  9. Keywords:
  10. Estimation ; Gene Expression Data ; Bioloical Data ; Retrofiting ; Landmark Genes ; Target Genes

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