AI3SD Video: DNA: coding blocks for biocompatible assembly & disassembly

Buurma, Niek (2021) AI3SD Video: DNA: coding blocks for biocompatible assembly & disassembly. Kanza, Samantha, Frey, Jeremy G. and Hooper, Victoria (eds.) Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom. 06 Jul - 24 Aug 2021. (doi:10.5258/SOTON/P0129).

Record type: Conference or Workshop Item (Other)

Abstract

This talk forms part of the ML4MC (Machine Learning for Materials and Chemicals Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Directed Assembly Network. This series ran over summer 2021 and covers topics that encompass our overlapping Network interests of AI, Machine Learning, Artificial Photosynthesis, Biomimetic Materials, Crystal Design & Engineering, Materials, Molecules, Photochemistry, Photocatalysis and Supramolecular Chemistry. This video was the second talk in the ML4MC series and formed part of the session "Research Talks".

Video

ML4MC-NiekBuurma-200721 - Version of Record

Available under License Creative Commons Attribution.

Download (938MB)

More information

Published date: 20 July 2021

Additional Information: Niek grew up in the Netherlands, surrounded by water, and it is therefore not surprising that research in our group is aimed at understanding reactions and interactions in aqueous solutions. Our research is focused on two main areas. The first area is the development of conjugated DNA-binders with useful optoelectronic properties for application as sensitisers in molecular diagnostics and biosensors, for use in forensics, as well as for use in self-assembled nanobioelectronic systems. Our contributions to this area include the synthesis of new DNA-binding compounds and studies of their DNA-binding properties using a variety of biophysical techniques. To support these studies, we also develop data-analysis software, in particular software for the analysis of isothermal titration calorimetry (ITC) data for complex coupled equilibria. The second area of interest involves the study of organic reactions in aqueous solutions. We focus on 1) pharmaceutically relevant racemisation processes, 2) kinetic and mechanistic studies of surfactant-assisted metal-catalysed as well as nanoparticle-catalysed reactions, 3) reactivity studies using automated reaction optimisers based on artificial intelligence (AI), and 4) micellar medium effects. The group is involved in international collaborations as well as collaborations with industry.

Venue - Dates: Machine Learning for Materials & Chemicals Seminar Series 2021, , Southampton, United Kingdom, 2021-07-06 - 2021-08-24

Related URLs: