Cryo-EM, as it is currently practiced in many laboratories, is limited to the visualization of molecules that are in thermal equilibrium at the time before freezing. A further limitation is that the existing software does not fully exploit the information that is contained in the images of large ensembles of molecules in thermal equilibrium. This book is a collection of recent articles by the author, reprinted with introductions, and they mainly describe two novel methods in cryo-EM, one computational and the other experimental that requires the use of a microfluidic device. Both methods have the capacity to shed light on the dynamic behavior of biomolecules. Combined, they greatly expand the range of applications of cryo-EM.
The book describes a successful approach in which, based on cryo-EM data, all states visited by the molecule in thermal equilibrium are mapped by manifold embedding—a method of geometric machine learning—and the energy landscape of the molecule is derived. It also discusses methods and biological results of time-resolved cryo-EM, following a reaction in a non-equilibrium system over a short period of time and resulting in the capture of short-lived states that have been inaccessible by standard methods of cryo-EM.
Betal enkelt med kort, Klarna, Apple Pay eller Google Pay. Ikke fornøyd? Du har alltid 14 dagers angrerett. Les mer i våre vilkår. Har du spørsmål, send oss en e-post på hello@memmo.org.
Memmo gjør det enklere å studere – uansett hvor du er i verden. Hos oss samler du pensumbøker og smarte studieverktøy på ett og samme sted: sammendrag, quizer, podkaster og flashcards. Og så Ted, din studiekompis som svarer på alt du lurer på. Over 50 000 studenter studerer allerede her – bygget for at du skal lære raskere og stresse mindre.