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 10 of 10 for “"Bioactivity data"”.
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Integration and analysis of protein evolutionary relationships and small molecule bioactivity data
… of biology. Likewise, chemical and biological data have been stored and maintained separately. The aim of my thesis was to integrate the ChEMBL database, a public repository of small molecule bioactivity measurements, with resources of protein evolutionary relationships, and exploit these new …
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Computational analyses of small molecules activity from phenotypic screens
… for target deconvolution in phenotypic screening datasets was investigated. A computational workflow is presented in Chapter 2, that allows to improve the coverage of mechanism of action hypotheses obtained by combining two conceptually different target prediction algorithms. These models rely on …
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Using Heterogeneous Information Sources for Understanding and Predicting Biological Effects of Compounds
… and the increasing deposition of high throughput data in public databases. There are different types of information/data which can be used and as the volume of this data increases, so too does their potential to deepen our understanding. Therefore, key questions remain around which ML …
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Synthesis of glycolipids inspired by Fucus distichus and natural product isolation and characterization of Euphorbia lancifolia
… well as eight other analogues were synthesized. Bioactivity data for some of the compounds is described. In a second project, an investigation into the major constituents of Euphorbia lancifolia (Ixbut) was undertaken. Although there have been no in-depth reported chemical studies of E. …
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Metabolomic comparison of selected Helichrysum species to predict their antiviral properties
… the HIV-1 RT enzyme by 63.78 % at 200 μg/ml. The bioactivity data and the spectral nuclear magnetic resonance (NMR) data of al the Helichrysum species from this study was analysed using the SIMCA-P software to discriminate between the different species on the basis of their bioactivity and …
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Transfer learning in small-molecule drug discovery: From physics-based in-silico scores to realistic preclinical endpoints
… drug discovery. Attempts to learn from molecular datasets are often hindered by the low availability of labeled datapoints. In the context of drug discovery, this limitation becomes especially severe due to the high cost of collecting experimental data. The common theme of this thesis is to …
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TOWARDS UNDERSTANDING MODE-OF-ACTION OF TRADITIONAL MEDICINES BY USING IN SILICO TARGET PREDICTION
… (MOAs) remain unclear. Given the increasing data of chemical ingredients of traditional medicines and the availability of large-scale bioactivity data linking chemical structures to activities against protein targets, we are now in a position to propose computational hypotheses for the MOAs …
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Improved In Silico Methods for Target Deconvolution in Phenotypic Screens
… existing methods do not utilize the wealth of bioactivity information held for orthologue species. We therefore also focused on an in-depth analysis of orthologue bioactivity data and its relevance and applicability towards expanding compound and target bioactivity space for predictive studies. …
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Addressing the ongoing threat of antimicrobial resistance: synthetic investigations of novel amicetin and B-lactam antibiotics
… antimicrobial activity. Although the preliminary bioactivity data of the synthesized 2-azetidinones against WT Staphylococcus aureus ATCC 49775 was disappointing, it should be noted that the project is still well in its infancy, and further investigation and evaluation is warranted to assess …
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Accelerating the Design-Make-Test cycle of Drug Discovery with Machine Learning
… synthesising them, and measuring their bioactivity, which informs the next cycle of compound designs. The challenges associated with each step lead to the long timeline of preclinical pharmaceutical development. This thesis focuses on how we can use machine learning tools to accelerate …