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 “"PPI prediction"”.
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Structure-based algorithms for protein-protein interaction prediction
Protein-protein interactions (PPIs) play a central role in all biological processes. Akin to the complete sequencing of genomes, complete descriptions of interactomes is a fundamental step towards a deeper understanding of biological processes, and has a vast potential to impact systems biology, …
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Net-PPI : mapping the human interactome with machine learned models
… known as protein-protein interactions or PPIs, which sustain the fundamental role of proteins in all living organisms. PPIs are also central to the study of diseases and development of therapeutics. Aberrant human PPIs are the primary cause of many life-threatening conditions, such as …
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Predicting the Interactions of Viral and Human Proteins
… extensive prior knowledge is available. The two prediction frameworks in this dissertation, DeNovo and DeNovo-Human, make it possible for the first time to predict the interactions between any viral protein and human proteins. They further helped to answer critical questions about the Zika virus. …
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Statistical Relational Learning for Proteomics: Function, Interactions and Evolution
… multi-task learning and structured output prediction, which natively handle relational data, noise, and partial information. Statistical-relational methods rely on some First- Order Logic as a general, expressive formal language to encode both the data instances and the relations or …
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Protein-Protein Interaction Network Alignment
… through adding protein interactions to existing PPI networks. In order to assess the improvement, we devise four groups of experiments and compare their results. The quality of PPI network alignment is assessed through the number of known protein complexes that are discovered. Significant …
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Inference frameworks in computational biology: from protein-protein interaction networks using machine learning to carbon footprint estimation.
Protein-protein interactions (PPIs) are essential to understanding biological pathways and their roles in development and disease. Computational tools have been successful at predicting PPIs in silico, but the lack of consistent and reliable frameworks for this task has led to network models that …
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Machine learning for the prediction of protein-protein interactions
The prediction of protein-protein interactions (PPI) has recently emerged as an important problem in the fields of bioinformatics and systems biology, due to the fact that most essential cellular processes are mediated by these kinds of interactions. In this thesis we focussed in the prediction of …