A Linear Model of Genetic Transcription Regulation that Combines Microarray and Genome Sequence Data
Name
Konstantin Tretjakov
Abstract
The thesis proposes a novel method for the analysis of microarray data based on fitting a specific linear model that combines microarray data with DNA sequence information. The model is both descriptive and predictive: its coefficients provide insight into the structure of the genetic regulatory networks, and its predictive performance may be used to find a set of genes that play important role in transcription regulation (transcription factors). An efficient algorithm is proposed for calculating the least-squares fit for the parameters of the model.
The proposed method is tested on a synthetic dataset and the results indicate that the approach is capable of detecting interesting relations in the data.
Graduation Thesis language
English
Graduation Thesis type
Bachelor (4a) Computer Science/Information Technology*
Supervisor(s)
Jaak Vilo
Defence year
2005