Computational biology

Many different ways to create mutants have been established. This research
demonstrates yet another variation of the promoter tagging technique that allows for a
single step selection of the putative transgenic plants that have a mutation in
constitutively expressed genes. While tomato transformants have not yet been
convincingly confirmed, tobacco transformation resulted in seven transgenic lines
showing resistance to high concentrations of kanamycin. Two transgenic lines were
further investigated and three putative promoters isolated. Transient expression analysis
of leaves transformed by particle bombardment with vectors carrying beta-glucuronidase
gene driven by these putative promoters suggests two of them to be functional. Further
investigation is needed to confirm the expression in the stably transformed plants as well
as cloning of the genes downstream of the functional promoters and research of their
functions.

Possibly the largest problem when working in bioinformatics is the large amount of data to sift through to find useful information. This thesis shows that the use of feature selection (a method of removing irrelevant and redundant information from the dataset) is a useful and even necessary technique to use in these large datasets. This thesis also presents a new method in comparing classes to each other through the use of their features. It also provides a thorough analysis of the use of various feature selection techniques and classifier in different scenarios from bioinformatics. Overall, this thesis shows the importance of the use of feature selection in bioinformatics.