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Guido Sanguinetti

Researcher at International School for Advanced Studies

Publications -  232
Citations -  7619

Guido Sanguinetti is an academic researcher from International School for Advanced Studies. The author has contributed to research in topics: Inference & Model checking. The author has an hindex of 47, co-authored 220 publications receiving 6342 citations. Previous affiliations of Guido Sanguinetti include University of Oxford & University of Manchester.

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Journal ArticleDOI

scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells.

TL;DR: This work reports the first single-cell method for parallel chromatin accessibility, DNA methylation and transcriptome profiling and validate scNMT-seq by applying it to differentiating mouse embryonic stem cells, finding links between all three molecular layers and revealing dynamic coupling between epigenomic layers during differentiation.
Journal ArticleDOI

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

TL;DR: An introduction to basic modelling concepts as well as an overview of state of the art methods for stochastic chemical kinetics is given, including the chemical Langevin equation, the system size expansion, moment closure approximation, time-scale separation approximations and hybrid methods.
Book ChapterDOI

Missing data in kernel PCA

TL;DR: The probabilistic interpretation of linear PCA is exploited together with recent results on latent variable models in Gaussian Processes in order to introduce an objective function for KPCA, and this new approach can be extended to reconstruct corrupted test data using fixed kernel feature extractors.
Journal ArticleDOI

Approximation and inference methods for stochastic biochemical kinetics - a tutorial review

TL;DR: In this article, a self-contained introduction to modeling, approximations and inference methods for stochastic chemical kinetics is given, as well as a comparison of several of these methods by means of a numerical case study.