prof. Ing. Valentine Provazník, Ph.D.

1. Acquisition and analysis of experimental ultrasound image sequences

   This project is focused on application of high-end ultrasound scanner on animal models. It includes all aspects of processing – setting the acquisition parameters, contrast dose optimization, advanced processing of time sequences and extraction of specific physiological parameters, depending on application. Main part will be focused on perfusion quantification. This topic is under support of FNUSA-ICRC project CZ.1.05/1.1.00/02.0123 and with cooperation of Academy of Science.

   Tutor: Kolář Radim, doc. Ing., Ph.D.

2. Methods of Genome-Wide Association Studies

   Genome-wide association studies are used to investigate genetic variability among individuals of selected type of organism. The subject is also exploring a possible relationship between variability (e.g. single-nucleotide polymorphism) and various characteristics (typically genetic diseases). The work will be focused on optimizing numerical representation of extremely large genetic sequences (up to the level of the whole genome) in order to efficiently search for and compare polymorphisms representing intra-species variability by methods of digital signal processing. The methods will be verified using publicly available data from genome-wide studies which employes next-generation sequencing methods. The work will be supported by the grant project GAČR P102/11/1068 "Nano-Electro-Bio-Tools for Biochemical and Molecularly-Biological Studies of Eukaryotic Cells (NanoBioTECell)".

   Tutor: Provazník Valentine, prof. Ing., Ph.D.

3. Network from neuronal cells created on a chip and its electrical characterization

   The main aim of the thesis is to develop a methodology for application of neural cells on a microelectronic chip and examine conditions for their interconnection. Further the work will be oriented to research of ability of cells to transmit electrical signals and to the possibility of targeted programming of created network. The work will be supported by the project "CEITEC - Central European Institute of Technology" No. CZ.1.05/1.1.00/02.0068.

   Tutor: Hubálek Jaromír, prof. Ing., Ph.D.

4. Structural Classification of Proteins Using Support Vector Machine Based Methods

   Issues concerning structural classification of proteins are still an important part of todays bioinformatics. A number of prestigious biotechnology centers are constantly working on the creating new, more efficient and effective methods for classification in genomics and proteomics. The thesis proposes the use of a relatively modern method applying support vector machine (SVM) and then comparative analysis leading to higher efficiency of classification. The investigated methods will be tested on data from public proteomic databases and verified on selected protein families of eukaryotic organisms. The work will be supported by the grant project GAČR P102/11/1068 "Nano-Electro-Bio-Tools for Biochemical and Molecularly-Biological Studies of Eukaryotic Cells (NanoBioTECell)".

   Tutor: Tkacz Ewaryst, prof., Ph.D.,D.Sc.