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Characterizing novel protease activated receptor 2 compounds for potential use in examining depression-like behavior
Schöpfer:
Coyle, Chelbi
Datum:
2020
Department, School or Faculty:
Strathclyde Institute of Pharmacy and Biomedical Sciences
Lysozyme encapsulated gold nanocluster for studying protein denaturation
Schöpfer:
Alkudaisi, Nora
Datum:
2020
Department, School or Faculty:
Department of Physics
Application of advanced material analyses for the investigation of the role of nano-mechanical properties in cell - scaffold interactions
Schöpfer:
Cardona, Milovan Joe
Datum:
2016
Department, School or Faculty:
Department of Biomedical Engineering
Studies and improvement of molecular docking methods in rigid and flexible receptors
Schöpfer:
Le Gall, Armelle
Datum:
2017
Funder:
GlaxoSmithKline
Department, School or Faculty:
Department of Pure and Applied Chemistry
The design, synthesis and optimisation of kinase inhibitors as potential anti-inflammatory agents
Schöpfer:
Harrison, Zoë A.
Datum:
2014
Funder:
GlaxoSmithKline
Department, School or Faculty:
Department of Pure and Applied Chemistry
Understanding the pharmacological consequence of functional P2Y1- P2Y12 heterodimerisation
Schöpfer:
Safar, Mohammed
Datum:
2020
Department, School or Faculty:
Strathclyde Institute of Pharmacy and Biomedical Sciences
The design and development of a high-throughput ATR-FTIR serum diagnostics platform
Schöpfer:
Finlayson, Duncan E.
Datum:
2020
Department, School or Faculty:
Centre for Doctoral Training in Medical Devices and Health Technologies and Department of Biomedical Engineering
Less is more : the neuromorphic engineering advantage
Schöpfer:
Kirkland, Paul
Datum:
2021 and 2020
Department, School or Faculty:
Department of Electronic and Electrical Engineering and Centre for Signal and Image Processing
The spontaneous symmetry breaking of light in passive Kerr ring resonators
Schöpfer:
Hill, Lewis
Datum:
2020
Department, School or Faculty:
Department of Physics
Spatiotemporal and temporal forecasting of ambient air pollution levels through data-intensive hybrid artificial neural network models
Schöpfer:
Cabaneros, Sheen McLean S.
Datum:
2020
Department, School or Faculty:
Department of Mechanical and Aerospace Engineering
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