Szilárd Páll

Molecular Biology · 2013–2020

A researcher in the Science corpus: 6 papers; trusts 1 researcher and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 55 citations into it; #16,176 of 17,773 by trust here, #4,132 by citations
• Materials Chemistry — 33 citations into it; #10,201 of 11,513 by trust here, #4,019 by citations
• Spectroscopy — 17 citations into it; #682 of 1,674 by trust here, #253 by citations
• Computer Networks and Communications — 14 citations into it
• Hardware and Architecture — 13 citations into it

Whom Szilárd Páll trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Berk Hess
2. James C. Phillips
3. Joshua A. Anderson
4. Mark James Abraham
5. Romelia Salomón-Ferrer
6. S. Plimpton
7. Vijay S. Pande
8. Andreas W. Götz
9. Rosemary Braun
10. Michael R. Shirts

Who trusts Szilárd Páll overall

1. Carsten Kutzner
2. Mark James Abraham

Papers from Szilárd Páll's perspective

Ordered by how strongly the researchers Szilárd Páll trusts endorse each paper. Same corpus, a different order for every researcher.

1. Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters (International Conference on Software Composition)
2. A smooth particle mesh Ewald method
3. How Fast-Folding Proteins Fold (Science)
4. Everything you wanted to know about Markov State Models but were afraid to ask (Methods)
5. General purpose molecular dynamics simulations fully implemented on graphics processing units (Journal of Computational Physics)
6. CHARMM: The biomolecular simulation program
7. CHARMM General Force Field (CGenFF): A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields
8. g_wham—A Free Weighted Histogram Analysis Implementation Including Robust Error and Autocorrelation Estimates
9. The GROMOS software for biomolecular simulation: GROMOS05
10. Polymorphic transitions in single crystals: A new molecular dynamics method

Their papers

• GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers (2015) — 23,273 citations
• GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit (2013) — 7,077 citations
• Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS (2020) — 790 citations
• More bang for your buck: Improved use of GPU nodes for GROMACS 2018 (2019) — 365 citations
• Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS (2015) — 921 citations
• A flexible algorithm for calculating pair interactions on SIMD architectures (2013) — 668 citations