Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 98 for “"Omics data"”.
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Bayesian Integrative Analysis of Omics Data
… innovations have produced large multi-modal datasets that range in multiplatform genomic data, pathway data, proteomic data, imaging data and clinical data. Integrative analysis of such data sets have potentiality in revealing important biological and clinical insights into complex diseases …
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High-dimensional Mediation Analysis of Multi-Omics Data
… have made mediation analysis of multi-omics data critical to gain groundbreaking insights into the biological mechanisms underlying the disease etiology. This dissertation aims to develop mediation analysis methods that utilize the enormous amount of multi-omics data in assessing …
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Linear mixed model for multi-level omics data
… and family structure have provided unprecedented data resources for predictive studies, few related analytical approaches were developed in predicting the risk of complex traits. In the first project, I developed a Bayesian linear mixed model (BLMM), where genetic effects were modelled using a …
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Algorithms for discovering disease genes by integrating 'omics data
… comes from different types of “-omic” data, including genomic sequences, gene expression, and molecular interactions. Genome Wide Association Studies (GWAS) compare genomic sequences from healthy and affected populations to identify genetic variants that are potentially associated with …
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Characterization of cancer and aging using multi-omics data
노화는 암을 포함한 많은 질병의 원인이 된다. 인간의 다양한 조직으로부터 추출한 DNA 메틸값을 이용해 실제 나이를 예측할 수 있다. 이는 DNA 메틸화가 노화의 지표가 될 수 있다는 의미이기도 하다. 하지만, 여러 조직의 정상과 종양 샘플의 많은 데이터 셋을 통합하여 노화 관련 DNA 메틸화 영역의 특징에 대해 밝힌 연구는 아직 많이 없는 실정이다. 본 연구에서는 16개 독립적인 연구의 DNA메틸화 및 유전자 발현 데이터를 통합하여 말초 혈액뿐만 아니라 유방, 자궁경부, 전립선, 뇌, 간, 대장 조직 등 다양한 조직의 대략 …
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Computational methods for functional interpretation of diverse omics data
… in an explosive growth of various types of "omics" data, including genomic, transcriptomic, proteomic, and metagenomic data. Functional interpretation of these data is key to elucidating the potential role of different molecular levels (e.g., genome, transcriptome, proteome, metagenome) in …
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Understanding and stratifying brain health through blood-based omics data
Brain health across the lifespan is dynamic and influenced by a complex interplay of genetics and the environment. Age-related neurological diseases are a growing burden on healthcare systems and society. Individuals that do not have overt diagnoses of neurological diseases will still experience …
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Joint Network Modeling of Omics Data for Understanding Complex Diseases
… important for the analysis of molecular data due to their ability to represent complex interplay within biological sys- tems. The availability of diverse molecular data sources, stemming from advancements in high-throughput genomic technologies, encourages the development of more …
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Prognostic biomarker discovery from omics data using machine learning approaches
Prognostic biomarker discovery from omics data using machine learning approaches by Manik Garg Prognostic biomarkers can help clinicians identify high-risk patients to administer appropriate therapies. The omics data from patient samples can be used to find such biomarkers. Moreover, molecular …
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Multi-omics Data Integration for Identifying Disease Specific Biological Pathways
… a large amount of quantitative gene expression data have been continuously acquired. The springing up omics data sets such as proteomics has facilitated the investigation on disease relevant pathways. Although much work has previously been done to explore the single omics data, little work has …
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Non-linear Multi Omics Data Integration Method Using Conditional Variational Autoencoders
… have enabled the study of diseases through multi-omics data, which combines information from genome, epigenome, transcriptome, proteome, and metabolome levels. Unlike single-omics approaches that provide limited insights, multi-omics integration offers a comprehensive understanding of biological …
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Characterizing and analyzing disease-related omics data using network modeling approaches
… to characterize and analyze multiple types of omics data using existing and novel network-based approaches to better understand disease development mechanisms and improve disease diagnosis and prognosis. The transcriptome reflects the expression level of mRNAs in single cells or a population of …
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Generalization of kernel machine methods for association testing of multi-omics data
… of trait etiology. Studies utilizing omics, including transcriptomics, proteomics, metabolomics, etc, are gaining popularity, and, used in conjunction with genomics, may aid in providing insight into complex trait etiology and disease pathogenesis. To fully harness the availability of …
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Multiple Testing Embedded in an Aggregation Tree With Applications to Omics Data
… inference, motivated by the analysis of omics data. This dissertation is divided into two parts. The first part of this dissertation is motivated by flow cytometry data analysis, where a key goal is to identify sparse cell subpopulations that differ be- tween two groups. I have developed …
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Statistical methods for the integrative analysis of single-cell multi-omics data
… the increasing availability of multi-modal data sets needs to be accompanied by the development of suitable integrative strategies to fully exploit the data generated. In this thesis I worked in collaboration with different research groups to introduce innovative experimental and …
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