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Optimising The Carcass Merit Of Irish Beef Cattle Using Genetic And Non-Genetic Information At The Animal And Herd Level, David Kenny
Theses
Failure of beef carcasses to achieve desirable carcass specifications represent inefficiencies within the supply chain, namely greater carcass processing costs and the inability of the resulting primal cuts to conform to high-value market specifications. Analysis of a representative sample of prime Irish beef cattle conducted in this thesis determined that 59% of cattle fail to achieve the desired carcass specifications of the supply chain at slaughter. The objective of this thesis was to use readily available information to define strategies that could help to reduce this statistic. Firstly, the likelihood of Irish beef carcasses achieving the desired carcass specifications was …
New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger
New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger
Theses
Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …
Cancer Risk Prediction With Next Generation Sequencing Data Using Machine Learning, Nihir Patel
Cancer Risk Prediction With Next Generation Sequencing Data Using Machine Learning, Nihir Patel
Theses
The use of computational biology for next generation sequencing (NGS) analysis is rapidly increasing in genomics research. However, the effectiveness of NGS data to predict disease abundance is yet unclear. This research investigates the problem in the whole exome NGS data of the chronic lymphocytic leukemia (CLL) available at dbGaP. Initially, raw reads from samples are aligned to the human reference genome using burrows wheeler aligner. From the samples, structural variants, namely, Single Nucleotide Polymorphism (SNP) and Insertion Deletion (INDEL) are identified and are filtered using SAMtools as well as with Genome Analyzer Tool Kit (GATK). Subsequently, the variants are …