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His research focuses on modeling proteins with biophysics and bioinformatics. In biophysics, his interests are in developing algorithms to extend time scales of simulations. Critical time scales in molecular biophysics cover 15 orders of magnitude, from femtoseconds (light absorption and initiation of vision) to hours (slow permeation processes through membranes). He has developed an algorithm (Milestoning) that extracts information from short-time dynamics and constructs a model for long-time processes. Elber’s theories and algorithms are implemented in the software package MOIL.
On the bioinformatics front, he has developed machine-learning approaches to model protein structures from sequences, implemented in his web server LOOPP. These techniques investigate the network of sequence flow between protein structures and model protein-protein interactions.
Elber has published more than 130 papers and books in the field of theoretical and computational biochemistry. He is a fellow of the American Physical Society. He was formerly a Camille and Henry Dreyfus Faculty and Alon Fellow.
On the bioinformatics front, he has developed machine-learning approaches to model protein structures from sequences, implemented in his web server LOOPP. These techniques investigate the network of sequence flow between protein structures and model protein-protein interactions.
Elber has published more than 130 papers and books in the field of theoretical and computational biochemistry. He is a fellow of the American Physical Society. He was formerly a Camille and Henry Dreyfus Faculty and Alon Fellow.
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Elsevier eBookspp.401-453, (2024)
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The journal of physical chemistry. Bno. 41 (2023): 8796-8808
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The journal of physical chemistry lettersno. 28 (2023): 6349-6354
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