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Protein / RNA Folding by Learning

von der Lehr, Fabrice and Knechtges, Philipp and Rüttgers, Alexander (2022) Protein / RNA Folding by Learning. Transformers for Environmental Science, 22.-23. Sep. 2022, Magdeburg, Deutschland.

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Abstract

Life is orchestrated via an interplay of many biomolecules. Any understanding of biomolecular function relies on detailed knowledge of their three-dimensional structure, whose determination is experimentally often very challenging. An orthogonal theoretical approach is the set of structure prediction techniques. The Helmholtz funded project ProFiLe aims to predict structures by using untapped information in the exponentially growing genomic databases via deep learning methods on high-performance computers. By this data-driven approach we want to accurately infer pairs of residues in spatial contact within biomolecules, as well as to guide structure prediction in a tailored open source software. ProFiLe employs transformer networks and their attention mechanism to learn in a self-supervised way the complex processes leading to protein or RNA folding.

Item URL in elib:https://elib.dlr.de/188381/
Document Type:Conference or Workshop Item (Speech, Poster)
Title:Protein / RNA Folding by Learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
von der Lehr, FabriceFabrice.Lehr (at) dlr.deUNSPECIFIED
Knechtges, PhilippPhilipp.Knechtges (at) dlr.dehttps://orcid.org/0000-0002-4849-0593
Rüttgers, AlexanderAlexander.Ruettgers (at) dlr.dehttps://orcid.org/0000-0001-6347-9272
Date:2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:RNA, Protein, Structure Prediction, Deep Learning, Transformer
Event Title:Transformers for Environmental Science
Event Location:Magdeburg, Deutschland
Event Type:Workshop
Event Dates:22.-23. Sep. 2022
Organizer:Arbeitsgruppe Earth System Data Exploration (Forschungszentrum Jülich)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology > High-Performance Computing
Institute for Software Technology
Deposited By: von der Lehr, Fabrice
Deposited On:03 Nov 2022 08:58
Last Modified:03 Nov 2022 08:58

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