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Agnieszka G. Lipska

dblp:188/8286 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-8390-8473ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Computational science and engineering · 72% Bioinformatics and computational biology · 28%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
GPUs and heterogeneous computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering › computational chemistry › molecular simulation › molecular dynamics
coarse-grained simulation
0.712023
UNRES-GPU for physics-based coarse-grained simulations of protein systems at biological time- and size-scales · Bioinform. 2023
Bioinformatics and computational biology
protein structure prediction
0.212016
Performance of protein-structure predictions with the physics-based UNRES force field in CASP11 · Bioinform. 2016
GPUs and heterogeneous computing
GPU computing
0.212023
UNRES-GPU for physics-based coarse-grained simulations of protein systems at biological time- and size-scales · Bioinform. 2023

Methods — techniques the papers use, named apart from their topics

coarse-grained molecular dynamics · 1.3UNRES · 1.3replica-exchange molecular dynamics · 0.2parallelization · 0.2coarse-grained force field · 0.2
YearPublicationVenuePosition
2023 UNRES-GPU for physics-based coarse-grained simulations of protein systems at biological time- and size-scales
abstract
SUMMARY: The UNited RESisdue (UNRES) package for coarse-grained simulations, which has recently been optimized to treat large protein systems, has been implemented on Graphical Processor Units (GPUs). An over 100-time speed-up of the GPU code (run on an NVIDIA A100) with respect to the sequential code and an 8.5 speed-up with respect to the parallel Open Multi-Processing (OpenMP) code (run on 32 cores of 2 AMD EPYC 7313 Central Processor Units (CPUs)) has been achieved for large proteins (with size over 10 000 residues). Due to the averaging over the fine-grain degrees of freedom, 1 time unit of UNRES simulations is equivalent to about 1000 time units of laboratory time; therefore, millisecond time scale of large protein systems can be reached with the UNRES-GPU code. AVAILABILITY AND IMPLEMENTATION: The source code of UNRES-GPU along with the benchmarks used for tests is available at https://projects.task.gda.pl/eurohpcpl-public/unres.
Krzysztof M. Ocetkiewicz, Cezary Czaplewski, Henryk Krawczyk, Agnieszka G. Lipska, Adam Liwo, Jerzy Proficz, Adam K. Sieradzan, Pawel Czarnul
Bioinform.4
2016 Performance of protein-structure predictions with the physics-based UNRES force field in CASP11
abstract
Participating as the Cornell-Gdansk group, we have used our physics-based coarse-grained UNited RESidue (UNRES) force field to predict protein structure in the 11th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP11). Our methodology involved extensive multiplexed replica exchange simulations of the target proteins with a recently improved UNRES force field to provide better reproductions of the local structures of polypeptide chains. All simulations were started from fully extended polypeptide chains, and no external information was included in the simulation process except for weak restraints on secondary structure to enable us to finish each prediction within the allowed 3-week time window. Because of simplified UNRES representation of polypeptide chains, use of enhanced sampling methods, code optimization and parallelization and sufficient computational resources, we were able to treat, for the first time, all 55 human prediction targets with sizes from 44 to 595 amino acid residues, the average size being 251 residues. Complete structures of six single-domain proteins were predicted accurately, with the highest accuracy being attained for the T0769, for which the CαRMSD was 3.8 Å for 97 residues of the experimental structure. Correct structures were also predicted for 13 domains of multi-domain proteins with accuracy comparable to that of the best template-based modeling methods. With further improvements of the UNRES force field that are now underway, our physics-based coarse-grained approach to protein-structure prediction will eventually reach global prediction capacity and, consequently, reliability in simulating protein structure and dynamics that are important in biochemical processes. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.unres.pl/ CONTACT: [email protected].
Pawel Krupa, Magdalena A. Mozolewska, Marta Wisniewska, Yanping Yin, Adam K. Sieradzan, Robert Ganzynkowicz, Agnieszka G. Lipska, Agnieszka S. Karczynska, Magdalena Slusarz, Rafal Slusarz, Artur Gieldon, Cezary Czaplewski, Dawid Jagiela, Bartlomiej Zaborowski, Harold A. Scheraga, Adam Liwo
Bioinform.8