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 7 of 7 for “"Protein Language Model"”.
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Structure, Function, and Interaction in Protein Language Models
… This approach has been extended to the realm of protein sequences through pretrained protein language models, which have excelled in various protein engineering tasks. In this thesis, we investigate a pre-trained protein language model’s ability to predict protein structure and the effects of …
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Source identification for exosomal communication via protein language models
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-08-01
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Genomic Language Models for Protein Function and Property Prediction
In the field of natural language processing (NLP), large language models (LLMs) trained on enormous corpora of unlabeled sequence data have demonstrated state-of-the-art performance on a variety of downstream tasks. This approach is appealing because one model can be easily adapted to do well in …
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Evolution-Inspired Design of Bacterial Biosensors
… cognate response regulators (RRs) using the protein language model ESM2. We show that the model is able to identify highly coevolving residues at the SK-RR interface. We then train a dedicated pairing model to predict TCS interactions from their amino acid sequences. We experimentally test …
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Explainable Machine Learning Prediction of Antimicrobial Peptide Targeting Streptococcus mutans
… and benchmarked classification and regression models across physicochemical descriptors, protein language model embeddings, and combined feature representations. Descriptor-based classical models performed best for binary potency classification, whereas combined representations performed best …
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Engineering TEV Protease Specificity: An Exploration of Machine Learning and High-Throughput Experimentation for Protein Design
… learning (ML) methods for highly effective protein engineering. The first portion of this thesis focuses on generating fitness landscapes from high-throughput experiments. Most machine learning models do not account for experimental noise, harming model performance and changing model …
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Discovering Viral Hosts, Mutations, and Diseases using Machine Learning
… computational virology. (i) We develop a viral protein language model for predicting the host infected by a virus, given only the sequence of one of its proteins. Our approach, 'Hierarchical Attention for Viral protEin-based host iNference (HAVEN)', includes a novel architecture comprising …