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.
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Showing 1 to 13 of 13 for “"Phenotype prediction"”.
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Foundation Models for Protein Phenotype Prediction
… for modeling, generating, and predicting protein phenotypes across five interrelated knowledge domains: molecular functions, therapeutic mechanisms, disease associations, functional protein domains, and molecular interactions. To support this, we created ProCyon-Instruct, a dataset of 33 million …
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Phenotype prediction and feature selection in genome-wide association studies
… (SNPs) in a subject genome and an observed phenotype. GWAS can be used to generate models for predicting phenotype based on genotype, as well as aiding in identification of specific genes affecting the biological mechanism underlying the phenotype. In this investigation, phenotype prediction …
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Rice and mouse quantitative phenotype prediction in genome-wide association studies with support vector regression
Quantitative phenotypes prediction from genotype data is significant for pathogenesis, crop yields, and immunity tests. The scientific community conducted many studies to find unobserved quantitative phenotype high predictive ability models. Early genome-wide association studies (GWAS) focused on …
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A penalized linear mixed model with generalized method of moments estimators for complex phenotype prediction
… have long been the method of choice for risk prediction analysis on high-dimensional data, where random effect terms are used to capture predictive effects from multiple markers. However, it remains computationally challenging to simultaneously model a large number of variables that can be …
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Enhancing genomic data quality through deep learning methods
… human disease risk to agricultural performance. Phenotype prediction lies at the heart of this effort, with applications in precision medicine, where it informs genetic risk models and polygenic scores; in agriculture, where it guides breeding for yield and resilience; and in evolutionary …
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scPhen: Single-Cell Phenotype Predictor for Alzheimer’s Disease
… circuitry. However, predicting patient-level phenotypes from scRNA-seq remains challenging due to limited sample sizes, variable cell counts, and the computational burden of modeling long-context dependencies. We present scPhen, a flexible, parametric deep-learning framework for phenotype …
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Statistical methods to infer biological interactions
… interactions and the link between genotypes and phenotypes. In the first part of the thesis, we introduce methods to infer protein-protein interactions from affinity purification mass spectrometry (AP-MS) and from luminescence-based mammalian interactome mapping (LUMIER). Our work reveals novel …
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Characterisation of weak and null phenotypes in the KEL and JK blood group systems
… aberrant antigen expression as in null and weak phenotypes, or with a phenotype that does not correspond to genotype. With the increasing use of DNA assays based on single nucleotide polymorphisms for blood group prediction, it is important to characterize the blood-groupencoding genes. …
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Scalable methods for the discovery of autophagy and disease genes
… to condense large, complex data into testable predictions. We exploit these tools to develop a model that predicts new autophagy genes by analysing systematic datasets. Top predictions were screened using the SRAI-LC3B assay, resulting in eighteen new candidate autophagy genes. Predicted genes …
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Modelling the structural, functional and phenotypic consequences of protein coding mutations
… the effect on protein structure, function and phenotype. In this thesis I perform three large scale variant analyses. First, I use the consequences of variation to learn about protein structure and function. I compile a dataset from 28 deep mutational scanning studies, covering 6291 positions …
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Robust time-varying functional connectivity estimation and its relevance for depression
… These benchmarks include simulations, subject phenotype prediction, test-retest studies, brain state analyses, external task prediction, and a range of qualitative method comparisons. Furthermore, I introduce a benchmark based on cross-validation, that can be run on any data set. The WP model …
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Exploring topological data analysis in gene expression data topology-driven biomarker discovery and clinical outcome prediction in oncology
… challenges in cancer research: clinical outcome prediction and biomarker discovery. In this study, we employ Weighted Gene Topological Data Analysis (WGTDA) to extract topological features from gene expression data, which serve as prognostic biomarkers for cancer classification, staging, and …
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Tools for investigating cellular signaling networks by mass spectrometry
… Growth Factor Receptor (EGFR) signaling and phenotype prediction. The quantity of proteomic mass spectrometry data available from a single analysis has increased exponentially as new generations of instruments become quicker and more sensitive. This deluge of data leaves many tempted to …