World's Best Scientists 2026 revealed!
Carlo Camilloni

Carlo Camilloni

D-Index & Metrics

Chemistry

D-Index
51
Citations
13336
World Ranking
13785
National Ranking
469

Carlo Camilloni 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 Carlo Camilloni 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: 144 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Carlo Camilloni 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 Carlo Camilloni 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: 51 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Carlo Camilloni is affiliated with the University of Milan in Italy and has an extensive publication record primarily in the fields of biochemistry, genetics, and molecular biology.

The main scientific domains in which Camilloni has contributed include:

  • Biochemistry, Genetics and Molecular Biology

Within these domains, Camilloni's work spans several subfields, notably:

  • Molecular Biology
  • Materials Chemistry
  • Computational Theory and Mathematics
  • Atomic and Molecular Physics, and Optics
  • Physiology

Research topics addressed in Camilloni's work include:

  • Protein Structure and Dynamics
  • Enzyme Structure and Function
  • Computational Drug Discovery Methods
  • RNA and protein synthesis mechanisms
  • Alzheimer's disease research and treatments
  • Receptor Mechanisms and Signaling
  • Glycosylation and Glycoproteins Research

Camilloni has published multiple research articles, with recent noteworthy papers including:

  • Small-molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer's disease, 2020, Science Advances
  • Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods, 2021, Frontiers in Molecular Biosciences
  • A kinetic ensemble of the Alzheimer's Aβ peptide, 2021, Nature Computational Science
  • The dynamics of linear polyubiquitin, 2020, Science Advances
  • A Small Molecule Stabilizes the Disordered Native State of the Alzheimer's Aβ Peptide, 2022, ACS Chemical Neuroscience

Their frequent co-authors include:

  • Cristina Paissoni
  • Federico Ballabio
  • Emanuele Scalone
  • Michele Vendruscolo
  • Riccardo Capelli

Camilloni's research has appeared often in several publication venues, such as:

  • Zenodo (CERN European Organization for Nuclear Research)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Biophysical Journal
  • eLife
  • Science Advances

Best Publications

  • PLUMED 2: New feathers for an old bird

    Gareth A. Tribello;Massimiliano Bonomi;Davide Branduardi;Carlo Camilloni

  • PLUMED: a portable plugin for free-energy calculations with molecular dynamics

    Massimiliano Bonomi;Davide Branduardi;Giovanni Bussi;Carlo Camilloni

  • Promoting transparency and reproducibility in enhanced molecular simulations

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

  • Determination of secondary structure populations in disordered states of proteins using nuclear magnetic resonance chemical shifts.

    Carlo Camilloni;Alfonso De Simone;Wim F Vranken;Michele Vendruscolo

  • Principles of protein structural ensemble determination.

    Massimiliano Bonomi;Gabriella T. Heller;Carlo Camilloni;Michele Vendruscolo

  • MobiDB 3.0: more annotations for intrinsic disorder, conformational diversity and interactions in proteins.

    Damiano Piovesan;Francesco Tabaro;Lisanna Paladin;Marco Necci;Marco Necci

  • Molecular dynamics simulations with replica-averaged structural restraints generate structural ensembles according to the maximum entropy principle

    Andrea Cavalli;Carlo Camilloni;Michele Vendruscolo

  • Urea and Guanidinium Chloride Denature Protein L in Different Ways in Molecular Dynamics Simulations

    C. Camilloni;A. Guerini Rocco;I. Eberini;E. Gianazza

  • Small-molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer's disease

    Gabriella T. Heller;Francesco A. Aprile;Francesco A. Aprile;Thomas C. T. Michaels;Thomas C. T. Michaels;Ryan Limbocker

  • Towards a structural biology of the hydrophobic effect in protein folding

    Carlo Camilloni;Daniela Bonetti;Angela Morrone;Rajanish Giri

  • A structural ensemble of a ribosome-nascent chain complex during cotranslational protein folding

    Lisa D Cabrita;Lisa D Cabrita;Anaïs M E Cassaignau;Anaïs M E Cassaignau;Hélène M M Launay;Hélène M M Launay;Christopher A Waudby;Christopher A Waudby

  • Dynamic Binding Mode of a Synaptotagmin-1-SNARE Complex in Solution

    Kyle Daniel Brewer;Taulant Bacaj;Andrea Cavalli;Carlo Camilloni

  • Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics

    Daniele Granata;Carlo Camilloni;Michele Vendruscolo;Alessandro Laio

  • The inverted free energy landscape of an intrinsically disordered peptide by simulations and experiments

    Daniele Granata;Daniele Granata;Fahimeh Baftizadeh;Fahimeh Baftizadeh;Johnny Habchi;Celine Galvagnion

  • Simultaneous quantification of protein order and disorder

    Pietro Sormanni;Damiano Piovesan;Gabriella T Heller;Massimiliano Bonomi

  • Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics.

    Massimiliano Bonomi;Carlo Camilloni;Carlo Camilloni;Michele Vendruscolo

  • The s2D method: simultaneous sequence-based prediction of the statistical populations of ordered and disordered regions in proteins.

    Pietro Sormanni;Carlo Camilloni;Piero Fariselli;Michele Vendruscolo

  • Structural basis for terminal loop recognition and stimulation of pri-miRNA-18a processing by hnRNP A1

    Hamed Kooshapur;Nila Roy Choudhury;Bernd Simon;Max Mühlbauer;Max Mühlbauer

  • In-cell NMR characterization of the secondary structure populations of a disordered conformation of α-synuclein within E. coli cells.

    Christopher A. Waudby;Carlo Camilloni;Anthony W. P. Fitzpatrick;Lisa D. Cabrita

  • Cryo-EM structure of cardiac amyloid fibrils from an immunoglobulin light chain AL amyloidosis patient.

    Paolo Swuec;Francesca Lavatelli;Masayoshi Tasaki;Masayoshi Tasaki;Masayoshi Tasaki;Cristina Paissoni

  • Characterization of the Conformational Equilibrium between the Two Major Substates of RNase A Using NMR Chemical Shifts

    Carlo Camilloni;Paul Robustelli;Paul Robustelli;Alfonso De Simone;Alfonso De Simone;Andrea Cavalli

  • Molecular Recognition by Templated Folding of an Intrinsically Disordered Protein

    Angelo Toto;Carlo Camilloni;Rajanish Giri;Rajanish Giri;Maurizio Brunori

  • Networks of Dynamic Allostery Regulate Enzyme Function

    Michael Joseph Holliday;Carlo Camilloni;Geoffrey Stuart Armstrong;Michele Vendruscolo

Frequent Co-Authors

Michele Vendruscolo
Michele Vendruscolo University of Cambridge
Ricardo A. Broglia
Ricardo A. Broglia University of Milan
Stefano Gianni
Stefano Gianni Sapienza University of Rome
Christopher M. Dobson
Christopher M. Dobson University of Cambridge
Martino Bolognesi
Martino Bolognesi University of Milan
Peter Tompa
Peter Tompa Vrije Universiteit Brussel
Michael Sattler
Michael Sattler Technical University of Munich
Maurizio Brunori
Maurizio Brunori Sapienza University of Rome
Per Jemth
Per Jemth Uppsala University
Vittorio Bellotti
Vittorio Bellotti University College London

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