World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
45
Citations
6664
World Ranking
5601
National Ranking
175

Guido Sanguinetti publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Guido Sanguinetti sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 205 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Guido Sanguinetti D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Guido Sanguinetti sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 45 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Guido Sanguinetti is affiliated with the International School for Advanced Studies in Italy. Their research spans primarily the broad field of Biochemistry, Genetics and Molecular Biology, with a focus on several subfields including Molecular Biology, Artificial Intelligence, Genetics, Cancer Research, and Epidemiology.

The main topics covered in their work include:

  • Single-cell and spatial transcriptomics
  • RNA Research and Splicing
  • RNA modifications and cancer
  • Gene Regulatory Network Analysis
  • Gene expression and cancer classification
  • Adversarial Robustness in Machine Learning
  • RNA and protein synthesis mechanisms

Among their recent published papers are:

  • Subclonal reconstruction of tumors by using machine learning and population genetics, 2020, Nature Genetics
  • BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments, 2021, Genome biology
  • The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data, 2020, BMC Bioinformatics
  • Robustness of Bayesian Neural Networks to Gradient-Based Attacks, 2020, arXiv (Cornell University)
  • scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution, 2021, Genome biology

Sanguinetti collaborates frequently with a number of coauthors, including:

  • Luca Bortolussi
  • Ginevra Carbone
  • Yuanhua Huang
  • Ramon Grima
  • Kashyap Chhatbar

The scientist regularly publishes in several venues, with a concentration in:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Genome biology
  • PLoS Genetics
  • Blood

Best Publications

  • Approximation and inference methods for stochastic biochemical kinetics—a tutorial review

    David Schnoerr;Guido Sanguinetti;Ramon Grima

  • Missing data in kernel PCA

    Guido Sanguinetti;Neil D. Lawrence

  • Detecting repeated cancer evolution from multi-region tumor sequencing data

    Giulio Caravagna;Ylenia Giarratano;Daniele Ramazzotti;Ian Tomlinson

  • Point process modelling of the Afghan War Diary

    Andrew Zammit-Mangion;Andrew Zammit-Mangion;Michael Dewar;Visakan Kadirkamanathan;Guido Sanguinetti

  • Single-trial classification of EEG in a visual object task using ICA and machine learning.

    Andrew X. Stewart;Antje Nuthmann;Guido Sanguinetti

  • Combining tree-based and dynamical systems for the inference of gene regulatory networks

    Van Anh Huynh-Thu;Guido Sanguinetti

  • Combining tree-based and dynamical systems for the inference of gene regulatory networks

    Vân Anh Huynh-Thu;Guido Sanguinetti

  • Network of epistatic interactions within a yeast snoRNA.

    Olga Puchta;Botond Cseke;Hubert Czaja;David Tollervey

  • Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities

    Guido Sanguinetti;Neil D. Lawrence;Magnus Rattray

  • Modelling transcriptional regulation using Gaussian Processes

    Neil D. Lawrence;Guido Sanguinetti;Magnus Rattray

  • Comparison of different moment-closure approximations for stochastic chemical kinetics.

    David Schnoerr;Guido Sanguinetti;Ramon Grima

  • Subclonal reconstruction of tumors by using machine learning and population genetics.

    Giulio Caravagna;Timon Heide;Marc J Williams;Luis Zapata

  • Gene Regulatory Network Inference: An Introductory Survey

    Vân Anh Huynh-Thu;Guido Sanguinetti

  • Data-Driven Statistical Learning of Temporal Logic Properties

    Ezio Bartocci;Luca Bortolussi;Guido Sanguinetti

  • Advances in Neural Information Processing Systems 26 (NIPS 2013)

    Botond Cseke;Manfred Opper;Guido Sanguinetti

  • Cells Segmentation From 3-D Confocal Images of Early Zebrafish Embryogenesis

    C. Zanella;M. Campana;B. Rizzi;C. Melani

  • puma: a Bioconductor package for propagating uncertainty in microarray analysis

    Richard D Pearson;Richard D Pearson;Xuejun Liu;Guido Sanguinetti;Marta Milo

  • Smoothed model checking for uncertain Continuous-Time Markov Chains

    Luca Bortolussi;Dimitrios Milios;Guido Sanguinetti

  • A new probabilistic generative model of parameter inference in biochemical networks

    P. Lecca;A. Palmisano;C. Priami;G. Sanguinetti

  • Automatic Determination of the Number of Clusters Using Spectral Algorithms

    G. Sanguinetti;J. Laidler;N.D. Lawrence

  • System design of stochastic models using robustness of temporal properties

    Ezio Bartocci;Luca Bortolussi;Luca Bortolussi;Laura Nenzi;Guido Sanguinetti

  • Variational inference for Markov jump processes

    Manfred Opper;Guido Sanguinetti

  • Accounting for probe-level noise in principal component analysis of microarray data

    Guido Sanguinetti;Marta Milo;Magnus Rattray;Neil D. Lawrence

Frequent Co-Authors

Robert K. Poole
Robert K. Poole University of Sheffield
Neil D. Lawrence
Neil D. Lawrence University of Cambridge
Manfred Opper
Manfred Opper Technical University of Berlin
Jane Hillston
Jane Hillston University of Edinburgh
John C. Marioni
John C. Marioni European Bioinformatics Institute
Wolf Reik
Wolf Reik Babraham Institute
Magnus Rattray
Magnus Rattray University of Manchester
Visakan Kadirkamanathan
Visakan Kadirkamanathan University of Sheffield
Gavin Kelsey
Gavin Kelsey Babraham Institute

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