Branch Details

Biomedical technologies and bioinformatics

Original title in Czech: Biomedicínské technologie a bioinformatikaFEKTAbbreviation: PP-BTBAcad. year: 2016/2017

Programme: Biomedical technologies and bioinformatics

Length of Study: 4 years

Accredited from: 20.12.2012Accredited until: 31.12.2020

Guarantor

Issued topics of Doctoral Study Program

2. round (applications submitted from 04.07.2016 to 20.07.2016)

  1. Tracking of transplanted cells - methods of labeling and detection of cells

    The thesis deals with the research methods of labeling and detecting cells, which are used in routine or experimental transplantation (mesenchymal stromal cells, dendritic cells, hematopoietic cell, chondroblasts). The trend in recent years is to label the cells by more independent labels or integrated multimodal labels. Thesis summarizes current knowledge and compares different labels from point of view of combination of options, long-term detectability, stability in the cell, cell biocompatibility and possibilites of quantification of a set of cells in a unit volume of tissue. The work tests the possibility of cell labeling different by commercial and experimental labels, their biocompatibility and subsequent possibility to detect labeled cells and the detection limits of cells in both the idealized in-vitro conditions and in the model of the real tissue iand also in the real tissue.

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

1. round (applications submitted from 01.04.2016 to 15.05.2016)

  1. Analysis of movement stereotypes in sports performance

    Motion analysis in sports is irreplaceable. A detailed analysis of movement stereotypes leads to improved quality of training plans and improve sports results. Analysis can also be used for diagnostic purposes - monitoring faulty movement patterns after injuries in order to clarify procedures for rehabilitation treatments. This work will be focused on monitoring specific movement stereotypes, selection of appropriate parameters and subsequent analysis of data from the camera VICON system, which will be performed in order to describe the motion stereotypes in sports performance. The study will be carried out in cooperation with the Centre of Sports Activities of BUT.

    Tutor: Kolářová Jana, doc. Ing., Ph.D.

  2. Gait analysis in rehabilitation

    Gait analysis in rehabilitation is irreplaceable. In clinical practice applies a subjective rating walk to diagnose the severity of the disease or injury. This work will focus on the selection of appropriate parameters and analysis of data from VICON camera system that will be conducted in order to evaluate the effectiveness of selected rehabilitation process. The study will will be carried out in collaboration with the University Hospital in Brno (Children's Medical Center). The results will be applied to the evaluation of rehabilitation procedures of persons with mobility disabilities.

    Tutor: Kolářová Jana, doc. Ing., Ph.D.

  3. Image analysis from multimodal holographic microscope in cancer cells study

    This topic is focused on study of cell entosis and its relation to polyploid cells and resistance of tumor cell against treatment. This process will be studied mainly using a multimodal holographic microscope, which enables real morphology imaging together with properties and process imaging in fluorescent mode. The main part of this topic is the multimodal image analysis, which will cover cell detection, cell tracking, evaluation of selected parameters and cell classification. This topic will be solved in close cooperation with Department of Physiology, Faculty of Medicine, MU.

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

  4. Image analysis from multimodal holographic microscope in cancer cells study

    This topic is focused on study of cell entosis and its relation to polyploid cells and resistance of tumor cell against treatment. This process will be studied mainly using a multimodal holographic microscope, which enables real morphology imaging together with properties and process imaging in fluorescent mode. The main part of this topic is the multimodal image analysis, which will cover cell detection, cell tracking, evaluation of selected parameters and cell classification. This topic will be solved in close cooperation with Department of Physiology, Faculty of Medicine, MU.

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

  5. Image processing of the retinal video-sequences

    This topic is focused on analysis of image sequences from experimental experimental video ophthalmoscope aimed at retina imaging. It will cover the laboratory work - work with experimental camera, data acquisition and implementation of acquisition software. The next part of this topic is focused on processing and analysis of retinal sequences – frame registration, blood-vessel pulsation estimation, optic disc segmentation or eye movement extraction. Advanced methods from image and signal processing area will be used. The project should improve the applications of video-ophthalmoscope in eye and neurological diseases. This project is solved in cooperation with Erlangen University, Germany.

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

  6. Image processing of the retinal video-sequences

    This topic is focused on analysis of image sequences from experimental experimental video ophthalmoscope aimed at retina imaging. It will cover the laboratory work - work with experimental camera, data acquisition and implementation of acquisition software. The next part of this topic is focused on processing and analysis of retinal sequences – frame registration, blood-vessel pulsation estimation, optic disc segmentation or eye movement extraction. Advanced methods from image and signal processing area will be used. The project should improve the applications of video-ophthalmoscope in eye and neurological diseases. This project is solved in cooperation with Erlangen University, Germany.

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

  7. Methods of comprehensive genomic characterization of carcinoma

    The dissertation focuses on research methods for comprehensive genomic characterization of carcinomas by bioinformatics analysis of multi-platform data. A large database of NIH The Cancer Genome Atlas project will be used as a data source. It contains annotated samples of 11000 patients covering 33 types of tumors and whole-genome sequences of 1000 tumor samples. The methods will include analysis of gene copy number alternance, structural aberations, recurrent deletions and other types of gene somatic mutations. These genetic alterations will be correlated with other parameters (the patient's health status, tissue identification, mutation localization, etc.). Results dissertation will contribute to knowledge in the field of integrated genomic analysis and description of the genesis of tumors. The applicant is expected being highly interested in research work in the topic of dissertation, to be capable to learn bioinformatics methods, programming in appropriate environment and mastering basic methodology of processing and analysis of genomic data.

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

  8. Utilization of machine learning techniques for the analysis of signal representations of bacterial genomes

    The dissertation is focused on development of methods for detection and classification of repetitive segments and specific sequence motifs of mobile genetic elements (MGE) in bacterial genomes. Innovative connection of genomic signal processing methods with machine learning techniques contributes to the localization of known and discovery of new MGE which are responsible for transfer of antibiotic resistance eg. gene cassettes, conjugative and mobile transposons, bacteriophages etc. or genes coding toxins. The applicant is expected being mastering basic methodology of processing and analysis of genomic data and should also have an overview on the field of processing and analysis of 1D signals. The programming in appropriate environment is commonplace. The topic will be solved in cooperation with the Children's Hospital - University Hospital Brno.

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


Course structure diagram with ECTS credits

1. year of study, winter semester
AbbreviationTitleL.Cr.Com.Compl.Hr. rangeGr.Op.
DBT5Modern methods in electrophysiology researchcs4Optional specializedDrExS - 39yes
DBT4Modern approaches of biomedical image analysiscs4Optional specializedDrExS - 39yes
DBT3Advanced microscopic techniques in biologycs4Optional specializedDrExS - 39no
DJA6English for post-graduatescs4General knowledgeDrExCj - 26yes
DRIZSolving of innovative taskscs2General knowledgeDrExS - 39yes
1. year of study, summer semester
AbbreviationTitleL.Cr.Com.Compl.Hr. rangeGr.Op.
DBT2New trends in the analysis and classification of biomedical datacs4Optional specializedDrExS - 39no
DBT1Advanced analysis of large genomic datacs4Optional specializedDrExS - 39yes
DJA6English for post-graduatescs4General knowledgeDrExCj - 26yes
DRIZSolving of innovative taskscs2General knowledgeDrExP - 52 / Cp - 52yes