World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
43
Citations
9329
World Ranking
17068
National Ranking
90

Pavel Banáš publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Pavel Banáš sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 107 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

Pavel Banáš D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Pavel Banáš sits on this spectrum.

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 43 D-Index — 5th percentile

5% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Overview

Pavel Banáš is affiliated with Palacký University, Olomouc in the Czech Republic. Their research primarily focuses on various aspects of biochemistry, genetics, and molecular biology, with a particular emphasis on molecular biology as a subfield.

The scientist has contributed extensively to topics including:

  • RNA and protein synthesis mechanisms
  • DNA and nucleic acid chemistry
  • RNA modifications and cancer
  • Advanced biosensing and bioanalysis techniques
  • RNA research and splicing
  • Bacteriophages and microbial interactions
  • RNA interference and gene delivery

The publication record of Pavel Banáš features several articles in well-known scientific venues. Frequent publication outlets include:

  • Journal of Chemical Theory and Computation
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Small
  • Journal of Chemical Information and Modeling

Their recent scholarly papers include the following:

  • Toward Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Modifications, 2022, Journal of Chemical Theory and Computation
  • Fine-Tuning of the AMBER RNA Force Field with a New Term Adjusting Interactions of Terminal Nucleotides, 2020, Journal of Chemical Theory and Computation
  • UUCG RNA Tetraloop as a Formidable Force-Field Challenge for MD Simulations, 2020, Journal of Chemical Theory and Computation
  • W-RESP: Well-Restrained Electrostatic Potential-Derived Charges. Revisiting the Charge Derivation Model, 2021, Journal of Chemical Theory and Computation
  • Sensitivity of the RNA Structure to Ion Conditions as Probed by Molecular Dynamics Simulations of Common Canonical RNA Duplexes, 2023, Journal of Chemical Information and Modeling

Frequent coauthors in their research include:

  • Michal Otyepka
  • Jiří Šponer
  • Petra Kührová
  • Vojtěch Mlýnský
  • Miroslav Krepl

Best Publications

  • Refinement of the Cornell et al. Nucleic Acids Force Field Based on Reference Quantum Chemical Calculations of Glycosidic Torsion Profiles

    Marie Zgarbová;Michal Otyepka;Michal Otyepka;Jiří Šponer;Jiří Šponer;Arnošt Mládek

  • Promoting transparency and reproducibility in enhanced molecular simulations

    M. Bonomi;M. Bonomi;B. Giovanni;C. Camilloni;G.A. Tribello

  • CAVER: a new tool to explore routes from protein clefts, pockets and cavities

    Martin Petřek;Michal Otyepka;Pavel Banáš;Pavlína Košinová

  • RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview.

    Jiří Šponer;Giovanni Bussi;Miroslav Krepl;Miroslav Krepl;Pavel Banáš

  • Performance of Molecular Mechanics Force Fields for RNA Simulations: Stability of UUCG and GNRA Hairpins

    Pavel Banáš;Daniel Hollas;Marie Zgarbová;Petr Jurečka

  • MOLE 2.0: advanced approach for analysis of biomacromolecular channels

    David Sehnal;David Sehnal;Radka Svobodová Vařeková;Karel Berka;Lukáš Pravda

  • Redesigning Dehalogenase Access Tunnels as a Strategy for Degrading an Anthropogenic Substrate.

    Martina Pavlova;Martin Klvana;Zbynek Prokop;Radka Chaloupkova

  • Reference simulations of noncanonical nucleic acids with different χ variants of the AMBER force field: quadruplex DNA, quadruplex RNA and Z-DNA

    Miroslav Krepl;Marie Zgarbová;Petr Stadlbauer;Michal Otyepka

  • Molecular Dynamics Simulations of Nucleic Acids. From Tetranucleotides to the Ribosome.

    Jiří Šponer;Jiří Šponer;Pavel Banáš;Petr Jurečka;Marie Zgarbová

  • MOLEonline 2.0: interactive web-based analysis of biomacromolecular channels

    Karel Berka;Ondřej Hanák;David Sehnal;Pavel Banáš

  • Computer Folding of RNA Tetraloops: Identification of Key Force Field Deficiencies.

    Petra Kührová;Robert B. Best;Sandro Bottaro;Giovanni Bussi

  • Explicit Water Models Affect the Specific Solvation and Dynamics of Unfolded Peptides While the Conformational Behavior and Flexibility of Folded Peptides Remain Intact

    Petra Florová;Petr Sklenovský;Pavel Banáš;Michal Otyepka

  • Improving the Performance of the Amber RNA Force Field by Tuning the Hydrogen-Bonding Interactions.

    Petra Kührová;Vojtěch Mlýnský;Marie Zgarbová;Miroslav Krepl

  • Nature and magnitude of aromatic base stacking in DNA and RNA: Quantum chemistry, molecular mechanics, and experiment.

    Jiří Šponer;Jiří Šponer;Judit E. Šponer;Judit E. Šponer;Arnošt Mládek;Arnošt Mládek;Petr Jurečka

  • Anatomy of Enzyme Channels

    Lukáš Pravda;Karel Berka;Radka Svobodová Vařeková;David Sehnal;David Sehnal

  • Reactivity of Fluorographene: A Facile Way toward Graphene Derivatives.

    Matúš Dubecký;Eva Otyepková;Petr Lazar;František Karlický

  • Folding of guanine quadruplex molecules-funnel-like mechanism or kinetic partitioning? An overview from MD simulation studies.

    Jiří Šponer;Jiří Šponer;Giovanni Bussi;Petr Stadlbauer;Petra Kührová

  • Theoretical studies of RNA catalysis: hybrid QM/MM methods and their comparison with MD and QM.

    Pavel Banáš;Petr Jurečka;Petr Jurečka;Nils G. Walter;Jiří Šponer;Jiří Šponer

  • Free Energy Landscape of GAGA and UUCG RNA Tetraloops

    Sandro Bottaro;Pavel Banáš;Jiří Šponer;Jiří Šponer;Giovanni Bussi

  • Extensive molecular dynamics simulations showing that canonical G8 and protonated A38H+ forms are most consistent with crystal structures of hairpin ribozyme.

    Vojtěch Mlýnský;Pavel Banáš;Daniel Hollas;Kamila Réblová

  • Can We Execute Stable Microsecond-Scale Atomistic Simulations of Protein-RNA Complexes?

    Miroslav Krepl;Marek Havrila;Petr Stadlbauer;Pavel Banáš

Frequent Co-Authors

Jiří Šponer
Jiří Šponer Masaryk University
Michal Otyepka
Michal Otyepka Palacký University, Olomouc
Petr Jurečka
Petr Jurečka Palacký University, Olomouc
Nils G. Walter
Nils G. Walter University of Michigan–Ann Arbor
Jaroslav Koča
Jaroslav Koča Central European Institute of Technology
Robert B. Best
Robert B. Best National Institutes of Health
Thomas E. Cheatham
Thomas E. Cheatham University of Utah
Yuji Nagata
Yuji Nagata Tohoku University
Stephen Neidle
Stephen Neidle University College London
Qiang Li
Qiang Li Brookhaven National Laboratory

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