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Single cell tracking on polymer microarray reveals the impact of surface chemistry on Pseudomonas aeruginosa twitching speed and biofilm development
(The University of Nottingham, 2020-09-01)
Dataset contains raw and processed data used for the creation of figures in publication entitled 'Single cell tracking on polymer microarray reveals the impact of surface chemistry on Pseudomonas aeruginosa twitching speed ...
Validating a predictive structure–property relationship by discovery of novel polymers which reduce bacterial biofilm formation
(The University of Nottingham, 2020-06-26)
Dataset contains raw and processed data used for the creation of figures in publication entitled 'Validating a Predictive Structure – Property Relationship by Discovery of Novel Polymers which Reduce Bacterial Biofilm Formation'
Fungal biofilm formation on potential anti-attachment materials
(The University of Nottingham, 2020-06-02)
(Meth)acrylate polymers showing the lowest fungal attachment (from a preceding microarray-spot screen) were assayed by scale-up to coat the 6.4-mm diameter wells of 96-well plates. Polymers showing surface cracking were ...
Design and evaluation of new quinazolin-4(3H)-one derived PqsR antagonists as quorum sensing quenchers in Pseudomonas aeruginosa
(The University of Nottingham, 2022-04-22)
A study focused on the design, synthesis and evaluation of pqs quorum sensing inhibitors
Molecular nanomachines for photoactivated biofilm disruption
(The University of Nottingham, 2024-01-01)
Study on the impact of molecular nanodrills on bacterial viability and biofilm formation
Biofilm disruption activity of absorbent sustained action alginate and iodine combined wound dressings
(The University of Nottingham, 2024-01-01)
Test new wound dressing formulations against clinically relevant polymicrobial biofilms
A linear, binary classifier to predict bacterial biofilm formation on polyacrylates
(The University of Nottingham, 2022-09-08)
Datafiles, in Microsoft Excel format, associated with the manuscript "A linear, binary classifier to predict bacterial biofilm formation on polyacrylates"
These files contain ToF-SIMS ion peaks and the bacterial attachment ...
A linear, binary classifier to predict bacterial biofilm formation on polyacrylates
(The University of Nottingham, 2022-12-21)
Research data and Python code to undertake machine learning to predict bacterial attachment to polyacrylates.
Development of a polymicrobial colony biofilm model
(The University of Nottingham, 2023-08-17)
The main aim of this study was to develop and optimise a polymicrobial colony biofilm model to test commercial wound dressings