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- 2-oxoglutarate-dependent enzymes (1)
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Cancer/Testis Gene Expression Changes In Metastatic Cancer, Clara M. Mosentine
Cancer/Testis Gene Expression Changes In Metastatic Cancer, Clara M. Mosentine
Dissertations, Master's Theses and Master's Reports
Metastasis is the movement of cancerous cells to new parts of the body, often through the blood or lymph systems. Metastasis is classified as stage IV cancer, a prognosis that is significantly more difficult to effectively treat compared to earlier cancer stages. We are interested in assessing whether expression of Cancer/testis (CT) genes, a class of genes that are predominantly expressed in germ cells while also being abnormally expressed in a large percentage of cancers, is associated with cancer metastasis. Germ cells make up an organism’s reproductive system, such as the testis and ovaries, and exhibit cellular immortality and, in …
Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao
Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao
Dissertations, Master's Theses and Master's Reports
This dissertation includes five Chapters. A brief description of each chapter is organized as follows.
In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.
In Chapter Two, we first illustrate the proposed GPN …
Multiscale Molecular Modeling Studies Of The Dynamics And Catalytic Mechanisms Of Iron(Ii)- And Zinc(Ii)-Dependent Metalloenzymes, Sodiq O. Waheed
Multiscale Molecular Modeling Studies Of The Dynamics And Catalytic Mechanisms Of Iron(Ii)- And Zinc(Ii)-Dependent Metalloenzymes, Sodiq O. Waheed
Dissertations, Master's Theses and Master's Reports
Enzymes are biological systems that aid in specific biochemical reactions. They lower the reaction barrier, thus speeding up the reaction rate. A detailed knowledge of enzymes will not be achievable without computational modeling as it offers insight into atomistic details and catalytic species, which are crucial to designing enzyme-specific inhibitors and impossible to gain experimentally. This dissertation employs advanced multiscale computational approaches to study the dynamics and reaction mechanisms of non-heme Fe(II) and 2-oxoglutarate (2OG) dependent oxygenases, including AlkB, AlkBH2, TET2, and KDM4E, involved in DNA and histone demethylation. It also focuses on Zn(II) dependent matrix metalloproteinase-1 (MMP-1), which helps …
Prediction Of Sumoylation Sites In Proteins From Language Model Representations, Evgenii Sidorov
Prediction Of Sumoylation Sites In Proteins From Language Model Representations, Evgenii Sidorov
Dissertations, Master's Theses and Master's Reports
Sumoylation is an essential post-translational modification intimately involved in a diverse range of eukaryotic cellular mechanisms and plays a significant role in DNA repair. Some researchers hypothesize that a high level of SUMOylation events in cancer cells improves cells' chances for survival under stress conditions by regulating tumor-related proteins.
This study belongs to a booming field of harnessing computational power to the domain of life. Prediction of protein structure, its molecular function, and the design of new drugs are just a few examples of the applications within this exciting area of research. By leveraging computational power, researchers can analyze vast …
Machine Learning Methods For Prediction Of Human Infectious Virus And Imputation Of Hla Alleles, Xiaoqing Gao
Machine Learning Methods For Prediction Of Human Infectious Virus And Imputation Of Hla Alleles, Xiaoqing Gao
Dissertations, Master's Theses and Master's Reports
This dissertation contains three Chapters. The following is a concise description of each Chapters.
In Chapter 1, we introduced the Random Forest, a machine learning method, to foresee whether a virus is capable of infecting humans. The Covid pandemic informs us the importance of predicting the ability of a zoonotic virus that can infect humans from its genomic sequence. We used the -mer with and as features of a virus to predict if it can affect humans. We further employed the Boruta algorithm to select the important features, then fed those important features into the Random Forest method to train …