Mixed Materials
In pursuit of gene variation of consequence to human health and disease
| Τίτλος: | In pursuit of gene variation of consequence to human health and disease |
|---|---|
| Additional Titles: | From the invention of Sanger sequencing, to the birth of current highthroughput and long-read methodologies, sequencing technology has become an vital tool for scientific research. Biologists released the first version of the human genome in 2001, and continued to refine it over the following years until the complete and final genome sequence was published in 2022. In parallel, the 1000 Genome project has revealed the extent of human genetic variation and polymorphisms, filling a gap in our knowledge about the diversity of the human mutational landscape. Transcriptome sequencing provides a means to study the changes in gene expression patterns and related signaling pathways affected by diseases and other biological processes. With the advancement of computer science, machine learning has been introduced into the field of biological and medical research. Using ML approaches scientists hope to find the biological signals and patterns hidden within massive datasets. The first chapter of this thesis provides an overview of the human genome, transcriptome research and different machine learning algorithms, including their applications in biological and medical research. The last chapter centers around two projects I worked on during my Ph.D. In the first project, simply called DNA prediction, we employed a Central model, a Markov model and a bi-directional Markov model to estimate the probability of the occurrence of four nucleotide types at a site based on its context sequence - the input for these models were the human reference genome. The results show that the base prediction of the human genome was above 50% on average, which should be compared to random guessing (25%). We applied the predicted results to SNP databases, and found that the alternative alleles showed higher probabilities than reference bases for somatic SNPs. In addition, we developed a substitution model to calculate the base mutability. Here, we found that the α matrix relies on a much smaller conte |
| Συγγραφείς: | Liang, Yuhu |
| Πηγή: | Liang , Y 2023 , ' In pursuit of gene variation of consequence to human health and disease ' . |
| Στοιχεία εκδότη: | Department of Computer Science, Faculty of Science, University of Copenhagen 2023 |
| Τύπος εγγράφου: | Mixed materials |
| Όροι ευρετηρίου: | other |
| Σύνδεσμος: | |
| Διαθεσιμότητα: | Open access content. Open access content info:eu-repo/semantics/closedAccess |
| Σημείωση: | English |
| Other Numbers: | DAV oai:pure.atira.dk:publications/955ed63a-56ff-4724-8336-1b07587d2055 1479126095 |
| Πηγή συνεισφοράς: | UNIV OF COPENHAGEN From OAIster®, provided by the OCLC Cooperative. |
| Αριθμός Καταχώρησης: | edsoai.on1479126095 |
| Βάση Δεδομένων: | OAIster |
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