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Low Frequency Airway Epithelial Cell Mutation Pattern Associated with Lung Cancer RiskCraig, Daniel John 28 August 2019 (has links)
No description available.
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Bayesian Lasso for Detecting Rare Genetic Variants Associated with Common DiseasesZhou, Xiaofei 23 October 2019 (has links)
No description available.
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Comprehensive analysis of full-length transcripts reveals novel splicing abnormalities and oncogenic transcripts in liver cancer / 完全長転写産物の網羅的解析による肝細胞癌における新規スプラシング異常と発がん性転写産物の解明Kiyose, Hiroki 23 May 2023 (has links)
京都大学 / 新制・課程博士 / 博士(医学) / 甲第24783号 / 医博第4975号 / 新制||医||1066(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 村川 泰裕, 教授 波多野 悦朗, 教授 小川 誠司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM
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Grain-Boundary Parameters Controlled Allotriomorphic Phase Transformations in Beta-Processed Titanium AlloysDixit, Vikas 21 May 2013 (has links)
No description available.
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Mining Structural and Functional Patterns in Pathogenic and Benign Genetic Variants through Non-negative Matrix FactorizationPeña-Guerra, Karla A 08 1900 (has links)
The main challenge in studying genetics has evolved from identifying variations and their impact on traits to comprehending the molecular mechanisms through which genetic variations affect human biology, including disease susceptibility. Despite having identified a vast number of variants associated with human traits through large scale genome wide association studies (GWAS) a significant portion of them still lack detailed insights into their underlying mechanisms [1]. Addressing this uncertainty requires the development of precise and scalable approaches to discover how genetic variation precisely influences phenotypes at a molecular level. In this study, we developed a pipeline to automate the annotation of structural variant feature effects. We applied this pipeline to a dataset of 33,942 variants from the ClinVar and GnomAD databases, which included both pathogenic and benign associations. To bridge the gap between genetic variation data and molecular phenotypes, I implemented Non-negative Matrix Factorization (NMF) on this large-scale dataset. This algorithm revealed 6 distinct clusters of variants with similar feature profiles. Among these groups, two exhibited a predominant presence of benign variants (accounting for 70% and 85% of the clusters), while one showed an almost equal distribution of pathogenic and benign variants. The remaining three groups were predominantly composed of pathogenic variants, comprising 68%, 83%, and 77% of the respective clusters. These findings revealed valuable insights into the underlying mechanisms contributing to pathogenicity. Further analysis of this dataset and the exploration of disease-related genes can enhance the accuracy of genetic diagnosis and therapeutic development through the direct inference of variants that are likely to affect the functioning of essential genes.
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The Distribution of Single Nucleotide Polymorphisms in Pyoderma Gangrenosum: Biomarker DiscoveryMercer, Heather Milliken 18 December 2013 (has links)
No description available.
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Estimating the Cost of Raccoon Rabies Variant in OhioDurbak, Leah M. 29 October 2014 (has links)
No description available.
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Impact of Variant Reclassification in the Clinical Setting of Cardiovascular GeneticsSchymanski, Rebecca E. 23 June 2017 (has links)
No description available.
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The Role of CD44 Variant Isoforms in Gastric Regeneration and DiseaseBertaux-Skeirik, Nina 05 December 2017 (has links)
No description available.
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Identifying Novel Disease-associated Variants and Understanding the Role of the STAT1-STAT4 Locus in SLEPatel, Zubin 15 December 2017 (has links)
No description available.
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