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Methods for class prediction with high-dimensional gene expression data
Šilhavá, Jana ; Matula, Petr (referee) ; Železný, Filip (referee) ; Smrž, Pavel (advisor)
Dizertační práce se zabývá predikcí vysokodimenzionálních dat genových expresí. Množství dostupných genomických dat významně vzrostlo v průběhu posledního desetiletí. Kombinování dat genových expresí s dalšími daty nachází uplatnění v mnoha oblastech. Například v klinickém řízení rakoviny (clinical cancer management) může přispět k přesnějšímu určení prognózy nemocí. Hlavní část této dizertační práce je zaměřena na kombinování dat genových expresí a klinických dat. Používáme logistické regresní modely vytvořené prostřednictvím různých regularizačních technik. Generalizované lineární modely umožňují kombinování modelů s různou strukturou dat. V dizertační práci je ukázáno, že kombinování modelu dat genových expresí a klinických dat může vést ke zpřesnění výsledku predikce oproti vytvoření modelu pouze z dat genových expresí nebo klinických dat. Navrhované postupy přitom nejsou výpočetně náročné. Testování je provedeno nejprve se simulovanými datovými sadami v různých nastaveních a následně s~reálnými srovnávacími daty. Také se zde zabýváme určením přídavné hodnoty microarray dat. Dizertační práce obsahuje porovnání příznaků vybraných pomocí klasifikátoru genových expresí na pěti různých sadách dat týkajících se rakoviny prsu. Navrhujeme také postup výběru příznaků, který kombinuje data genových expresí a znalosti z genových ontologií.
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The characterisation of organ-specific phytohormone responses to nutrient deficiency and biotic stress
Kramná, Barbara ; Vaňková, Radomíra (advisor) ; Hronková, Marie (referee) ; Plíhalová, Lucie (referee)
Abiotic and biotic stresses lead to crop yield losses and ultimately negatively affect agriculture production. Elucidation of the mechanisms of plant stress responses and their regulation could help to understand plant defence and improve stress tolerance. Phytohormones stand behind both plant growth and developmental changes as well as stress signalling. This thesis summarises the results published in two articles focused on phytohormone dynamics in response to abiotic and biotic stresses, namely phosphate shortage and Plasmodiophora brassicae infection. A review article focuses in depth on strigolactones as master regulators of phosphate deficiency responses. The main emphasis is put on organ-specific reactions and exogenous phytohormone treatment with the potential to convey stress tolerance. In the case of phosphate shortage, the universal reaction in all organs was a decrease in active cytokinin trans-zeatin and gibberellin GA4 with a concurrent elevation of abscisic acid. Also, the high- affinity phosphate transporters (PHT1;4 and PHT1;7) exhibited increased gene expression within the whole plant. Shoot apical meristems showed numerous changes in gene expression and were the most affected organ during the lack of phosphate. Only in roots, we observed a substantial elevation of low active...
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Normality test of the gene expression data
Shokirov, Bobosharif ; Klebanov, Lev (advisor) ; Hušková, Marie (referee) ; Kalina, Jan (referee)
This thesis deals with a test of normality of gene expressions data. Based on characterization theorems of the normal distribution, the test of normality is replaced by a test of spherical uniformity. Due to strong correlations between the gene expression data, the normality test is conducted with $\delta$ sequences. A new characterization theorem of the normal distribution is proven. Based on that, the normality test is conducted using Kolmogorov's test statistic. The obtained characterization results for the normal distribution are extended to the complete type of distributions and based on that, a test is conducted to verify whether the distributions of the two data sets of the gene expressions belong to the same type. Powered by TCPDF (www.tcpdf.org)
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Multidimensional statistics and applications to study genes
Bubelíny, Peter ; Klebanov, Lev (advisor) ; Jurečková, Jana (referee) ; Kalina, Jan (referee)
Title: Multidimensional statistics and applications to study genes Author: Mgr. Peter Bubelíny Department: Department of probability and mathematical statistics Supervisor: prof. Lev Klebanov, DrSc., KPMS MFF UK Abstract: Microarray data of gene expressions consist of thousands of genes and just some tens of observations. Moreover, genes are highly correlated between themselves and contain systematic errors. Hence the magnitude of these data does not afford us to estimate their correlation structure. In many statistical problems with microarray data, we have to test some thousands of hypotheses simultaneously. Due to dependence between genes, p-values of these hypotheses are dependent as well. In this work, we compared conve- nient multiple testing procedures reasonable for dependent hypotheses. The common manner to make microarray data more uncorrelated and partially eliminate systematic errors is normalizing them. We proposed some new normalizations and studied how different normalizations influence hypothe- ses testing. Moreover, we compared tests for finding differentially expressed genes or gene sets and identified some interesting properties of some tests such as bias of two-sample Kolmogorov-Smirnov test and interesting behav- ior of Hotelling's test for dependent components of observations. In the end of...
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The role of evolutionarily conserved proteins BIR-1/Survivin and SKP-1 in the regulation of gene expression
Kostrouch, David ; Kostrouch, Zdeněk (advisor) ; Dráber, Pavel (referee) ; Pacák, Karel (referee)
SKIP and BIR/Survivin are evolutionarily conserved proteins. SKIP is a known transcription and splicing cofactor while BIR-1/Survivin regulates cell division, gene expression and development. Loss of function of C. elegans SKIP (SKP-1) and BIR-1 induces overlapping developmental phenotypes. In order to uncover the possible interactions of SKP-1 and BIR-1 on the protein level, we screened the complete C. elegans mRNA library using the yeast two-hybrid system. These experiments identified partially overlapping categories of proteins as SKP-1 and BIR-1 interactors. The interacting proteins included ribosomal proteins, transcription factors, translation factors and cytoskeletal and motor proteins suggesting involvement of the two studied proteins in multiple protein complexes. To visualize the effect of BIR-1 on the proteome of C. elegans we induced a short time pulse BIR-1 overexpression in synchronized L1 larvae. This led to a dramatic alteration of the whole proteome pattern indicating that BIR-1 alone has the capacity to alter the chromatographic profile of many target proteins including proteins found to be interactors in yeast two hybrid screens. The results were validated for ribosomal proteins RPS-3, RPL-5, non-muscle myosin and TAC-1, a transcription cofactor and a centrosome associated...
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The characterisation of organ-specific phytohormone responses to nutrient deficiency and biotic stress
Kramná, Barbara ; Vaňková, Radomíra (advisor) ; Hronková, Marie (referee) ; Plíhalová, Lucie (referee)
Abiotic and biotic stresses lead to crop yield losses and ultimately negatively affect agriculture production. Elucidation of the mechanisms of plant stress responses and their regulation could help to understand plant defence and improve stress tolerance. Phytohormones stand behind both plant growth and developmental changes as well as stress signalling. This thesis summarises the results published in two articles focused on phytohormone dynamics in response to abiotic and biotic stresses, namely phosphate shortage and Plasmodiophora brassicae infection. A review article focuses in depth on strigolactones as master regulators of phosphate deficiency responses. The main emphasis is put on organ-specific reactions and exogenous phytohormone treatment with the potential to convey stress tolerance. In the case of phosphate shortage, the universal reaction in all organs was a decrease in active cytokinin trans-zeatin and gibberellin GA4 with a concurrent elevation of abscisic acid. Also, the high- affinity phosphate transporters (PHT1;4 and PHT1;7) exhibited increased gene expression within the whole plant. Shoot apical meristems showed numerous changes in gene expression and were the most affected organ during the lack of phosphate. Only in roots, we observed a substantial elevation of low active...
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Normality test of the gene expression data
Shokirov, Bobosharif ; Klebanov, Lev (advisor) ; Hušková, Marie (referee) ; Kalina, Jan (referee)
This thesis deals with a test of normality of gene expressions data. Based on characterization theorems of the normal distribution, the test of normality is replaced by a test of spherical uniformity. Due to strong correlations between the gene expression data, the normality test is conducted with $\delta$ sequences. A new characterization theorem of the normal distribution is proven. Based on that, the normality test is conducted using Kolmogorov's test statistic. The obtained characterization results for the normal distribution are extended to the complete type of distributions and based on that, a test is conducted to verify whether the distributions of the two data sets of the gene expressions belong to the same type. Powered by TCPDF (www.tcpdf.org)
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Multidimensional statistics and applications to study genes
Bubelíny, Peter ; Klebanov, Lev (advisor) ; Jurečková, Jana (referee) ; Kalina, Jan (referee)
Title: Multidimensional statistics and applications to study genes Author: Mgr. Peter Bubelíny Department: Department of probability and mathematical statistics Supervisor: prof. Lev Klebanov, DrSc., KPMS MFF UK Abstract: Microarray data of gene expressions consist of thousands of genes and just some tens of observations. Moreover, genes are highly correlated between themselves and contain systematic errors. Hence the magnitude of these data does not afford us to estimate their correlation structure. In many statistical problems with microarray data, we have to test some thousands of hypotheses simultaneously. Due to dependence between genes, p-values of these hypotheses are dependent as well. In this work, we compared conve- nient multiple testing procedures reasonable for dependent hypotheses. The common manner to make microarray data more uncorrelated and partially eliminate systematic errors is normalizing them. We proposed some new normalizations and studied how different normalizations influence hypothe- ses testing. Moreover, we compared tests for finding differentially expressed genes or gene sets and identified some interesting properties of some tests such as bias of two-sample Kolmogorov-Smirnov test and interesting behav- ior of Hotelling's test for dependent components of observations. In the end of...
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The role of evolutionarily conserved proteins BIR-1/Survivin and SKP-1 in the regulation of gene expression
Kostrouch, David ; Kostrouch, Zdeněk (advisor) ; Dráber, Pavel (referee) ; Pacák, Karel (referee)
SKIP and BIR/Survivin are evolutionarily conserved proteins. SKIP is a known transcription and splicing cofactor while BIR-1/Survivin regulates cell division, gene expression and development. Loss of function of C. elegans SKIP (SKP-1) and BIR-1 induces overlapping developmental phenotypes. In order to uncover the possible interactions of SKP-1 and BIR-1 on the protein level, we screened the complete C. elegans mRNA library using the yeast two-hybrid system. These experiments identified partially overlapping categories of proteins as SKP-1 and BIR-1 interactors. The interacting proteins included ribosomal proteins, transcription factors, translation factors and cytoskeletal and motor proteins suggesting involvement of the two studied proteins in multiple protein complexes. To visualize the effect of BIR-1 on the proteome of C. elegans we induced a short time pulse BIR-1 overexpression in synchronized L1 larvae. This led to a dramatic alteration of the whole proteome pattern indicating that BIR-1 alone has the capacity to alter the chromatographic profile of many target proteins including proteins found to be interactors in yeast two hybrid screens. The results were validated for ribosomal proteins RPS-3, RPL-5, non-muscle myosin and TAC-1, a transcription cofactor and a centrosome associated...
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Methods for class prediction with high-dimensional gene expression data
Šilhavá, Jana ; Matula, Petr (referee) ; Železný, Filip (referee) ; Smrž, Pavel (advisor)
Dizertační práce se zabývá predikcí vysokodimenzionálních dat genových expresí. Množství dostupných genomických dat významně vzrostlo v průběhu posledního desetiletí. Kombinování dat genových expresí s dalšími daty nachází uplatnění v mnoha oblastech. Například v klinickém řízení rakoviny (clinical cancer management) může přispět k přesnějšímu určení prognózy nemocí. Hlavní část této dizertační práce je zaměřena na kombinování dat genových expresí a klinických dat. Používáme logistické regresní modely vytvořené prostřednictvím různých regularizačních technik. Generalizované lineární modely umožňují kombinování modelů s různou strukturou dat. V dizertační práci je ukázáno, že kombinování modelu dat genových expresí a klinických dat může vést ke zpřesnění výsledku predikce oproti vytvoření modelu pouze z dat genových expresí nebo klinických dat. Navrhované postupy přitom nejsou výpočetně náročné. Testování je provedeno nejprve se simulovanými datovými sadami v různých nastaveních a následně s~reálnými srovnávacími daty. Také se zde zabýváme určením přídavné hodnoty microarray dat. Dizertační práce obsahuje porovnání příznaků vybraných pomocí klasifikátoru genových expresí na pěti různých sadách dat týkajících se rakoviny prsu. Navrhujeme také postup výběru příznaků, který kombinuje data genových expresí a znalosti z genových ontologií.
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