World's Best Scientists 2026 revealed!

Overview

Gesine Reinert is affiliated with the University of Oxford in the United Kingdom. Their research spans multiple fields, primarily focused on Computer Science and Mathematics, with significant contributions in Statistics and Probability, Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics, and Economics and Econometrics.

Their scholarly work covers a wide range of topics, including:

  • Complex Network Analysis Techniques
  • Bioinformatics and Genomic Networks
  • Random Matrices and Applications
  • Statistical Methods and Bayesian Inference
  • Bayesian Methods and Mixture Models
  • Advanced Graph Neural Networks
  • Complex Systems and Time Series Analysis

Reinert has published extensively in several venues, with a strong presence in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Complex Networks
  • SSRN Electronic Journal
  • Bioinformatics

Their recent published papers illustrate a diverse research portfolio. Selected works include:

  • "Core-periphery structure in directed networks," 2020, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • "Lead-lag detection and network clustering for multivariate time series with an application to the US equity market," 2022, Machine Learning
  • "Hypergraphs for predicting essential genes using multiprotein complex data," 2020, Journal of Complex Networks
  • "Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks," 2020, BMC Genomics
  • "Stein's Method Meets Computational Statistics: A Review of Some Recent Developments," 2022, Statistical Science

They have collaborated frequently with multiple researchers, including:

  • Mihai Cucuringu (26 coauthored works)
  • Charlotte M. Deane (13 coauthored works)
  • Andrew Elliott (8 coauthored works)
  • Javier Pardo-Diaz (7 coauthored works)
  • Robert E. Gaunt (5 coauthored works)

Best Publications

  • Probabilistic and Statistical Properties of Words: An Overview

    Gesine Reinert;Sophie Schbath;Michael S. Waterman

  • Alignment-free sequence comparison (I): statistics and power.

    Gesine Reinert;David Chew;Fengzhu Sun;Michael S. Waterman

  • Stein's method and the zero bias transformation with application to simple random sampling

    Larry Goldstein;Gesine Reinert

  • Multivariate normal approximation with Stein’s method of exchangeable pairs under a general linearity condition

    Gesine Reinert;Adrian Röllin

  • Estimating the Number of Communities in a Network.

    M. E. J. Newman;M. E. J. Newman;Gesine Reinert

  • Use of exchangeable pairs in the analysis of simulations

    Charles Stein;Persi Diaconis;Susan Holmes;Gesine Reinert

  • Stein's method for comparison of univariate distributions

    Christophe Ley;Gesine Reinert;Yvik Swan

  • Invariance Principles for Homogeneous Sums: Universality of Gaussian Wiener Chaos

    Ivan Nourdin;Giovanni Peccati;Gesine Reinert

  • Alignment-free sequence comparison (II): theoretical power of comparison statistics.

    Lin Wan;Gesine Reinert;Fengzhu Sun;Michael S. Waterman

  • Small worlds

    A. D. Barbour;Gesine Reinert

  • Compound Poisson and Poisson Process Approximations for Occurrences of Multiple Words in Markov Chains

    Gesine Reinert;Sophie Schbath

  • Approximating the epidemic curve

    Andrew David Barbour;Gesine Reinert

  • Second order Poincaré inequalities and CLTs on Wiener space

    Ivan Nourdin;Giovanni Peccati;Gesine Reinert

  • Poisson Process Approximation for Sequence Repeats, and Sequencing by Hybridization

    Richard Arratia;Daniela Martin;Gesine Reinert;Michael S. Waterman

  • Three general approaches to Stein's method

    Gesine Reinert

  • Chi-square approximation by Stein's method with application to Pearson's statistic

    Robert E. Gaunt;Alastair M. Pickett;Gesine Reinert

  • Stein's method for the Beta distribution and the Pólya-Eggenberger urn

    Larry Goldstein;Gesine Reinert

  • Efficient method for estimating the number of communities in a network

    Maria A. Riolo;George T. Cantwell;Gesine Reinert;Mark E. J. Newman

  • Discussion on the paper by Handcock, Raftery and Tantrum

    Tom A. B. Snijders;Tony Robinson;Anthony C. Atkinson;Marco Riani

  • Second order Poincar'e inequalities and CLTs on Wiener space

    Ivan Nourdin;Giovanni Peccati;Gesine Reinert

Frequent Co-Authors

Charlotte M. Deane
Charlotte M. Deane University of Oxford
Fengzhu Sun
Fengzhu Sun University of Southern California
Michael S. Waterman
Michael S. Waterman University of Southern California
Claudia Klüppelberg
Claudia Klüppelberg Technical University of Munich
Jukka-Pekka Onnela
Jukka-Pekka Onnela Harvard University
Giovanni Peccati
Giovanni Peccati University of Luxembourg
Ivan Nourdin
Ivan Nourdin University of Luxembourg
Judith P. Armitage
Judith P. Armitage University of Oxford
Philip S. Poole
Philip S. Poole University of Oxford
Helen M. Byrne
Helen M. Byrne University of Oxford

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