World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
45
Citations
6664
World Ranking
5599
National Ranking
175

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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