Gesine Reinert

Professor of Statistics

Department of Statistics
University of Oxford
24-29 St Giles’
Oxford OX1 3LB
UK
Tel. ++44 1865 281541
Fax ++44 1865 272595
email reinert@stats.ox.ac.uk


I am a University Professor in Statistics, and also a Fellow of Keble College. I am also a Fellow of the Alan Turing Institute.

Currently I hold an EPSRC Fellowship for CHARMNET- CHARacterising Models for NETworks.

Since January 1, 2020, I am Editor-in-chief for
SpringerBriefs in Probability and Mathematical Statistics. Other professional activities include Chair of the Applied Probability Section of the Royal Statistical Society , Vice-chair of the European Cooperation for Statistics of Network Data Science associate editor for the Bernoulli journal and I serve on the editorial board of the Journal of Computational Biology. I am Council member of the IMS and of the Bernoulli Society. I also serve on the Council of the Royal Statistical Society.

My Curriculum Vitae is available here.

On this web site you can find a list of papers, software and talks.

Here is a link to a short general audience video on anomaly detection in networks; Normal or not? How to detect anomalies in networks which was produced with help from Science Animated.

For more information also visit my departmental website.




Papers

 

Behme, Anita, Claudia Klüppelberg, and Gesine Reinert. "Ruin probabilities for risk processes in a bipartite network." Stochastic Models (2020): 1-26. Pdf file.

 

Bozhilova, Lyuba V., Javier Pardo-Diaz, Gesine Reinert, and Charlotte M. Deane. "COGENT: evaluating the consistency of gene co-expression networks." To appear, Bioinformatics (2020). Pdf file.

 

Elliott, Andrew, Angus Chiu, Marya Bazzi, Gesine Reinert, and Mihai Cucuringu. "Core–periphery structure in directed networks." Proceedings of the Royal Society A 476, no. 2241 (2020): 20190783. Pdf file.

 

Klimm, Florian, Charlotte M. Deane, and Gesine Reinert. "Hypergraphs for predicting essential genes using multiprotein complex data." To appear, Journal of Complex Networks (2020). Pdf file.

 

Klimm, Florian, Enrique M. Toledo, Thomas Monfeuga, Fang Zhang, Charlotte M. Deane, and Gesine Reinert. "Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks." BMC Genomics (2020): 21(1), 1-10. Pdf file.

 

M. Ernst, G. Reinert, and Y. Swan (2020) First order covariance inequalities via Stein's method. arXiv preprint arXiv:1906.08372. Bernoulli, 26(3), pp.2051-2081. Pdf file.

 

G. Reinert and C. Yang, (2020) A bound on the rate of convergence in the Central Limit Theorem for renewal processes under second moment conditions. arXiv preprint arXiv:1807.08672. Accepted for publication in Journal of Applied Probability. Pdf file.

 

A. Anastasiou, and G. Reinert (2020) Bounds for the asymptotic distribution of the likelihood ratio. arXiv preprint arXiv:1806.03666. Annals of Applied Probability 30, no. 2 (2020): 608-643. Pdf file.

 

H. M. Byrne, H.A. Harrington, R. Muschel, G. Reinert, B.J. Stolz, B.J. and U. Tillmann, U. (2019) Topological Methods for Characterising Spatial Networks: A Case Study in Tumour Vasculature. Mathematics Today. Pdf file.

 

L.V. Bozhilova, A.V. Whitmore, J. Wray, G. Reinert, and C.M. Deane (2019) Measuring rank robustness in scored protein interaction networks. BMC Bioinformatics, 20(1), p.446. Pdf file.

 

G. Reinert and N. Ross (2019) Approximating stationary distributions of fast mixing Glauber dynamics, with applications to exponential random graphs. The Annals of Applied Probability 29, no. 5 (2019): 3201-3229. Pdf file.

 

M. Coulson, R.E. Gaunt, and G. Reinert (2018) Compound Poisson approximation of subgraph counts in stochastic block models with multiple edges. Advances in Applied Probability 50, 759--782. Pdf file.

 

X. Xu and G. Reinert (2018) Triad-based comparison and signatures of directed networks. In International Conference on Complex Networks and their Applications (pp. 590-602). Springer. Pdf file.

 

L. Ospina-Forero, C.M. Deane, and G. Reinert (2018) Assessment of model fit via network comparison methods based on subgraph counts. Journal of Complex Networks, 7, 226-253. Pdf file.

 

J. Ren, X. Bai, Y. Y. Lu, K. Tang, Y. Wang, G. Reinert, F. Sun (2018) Alignment-Free Sequence Analysis and Applications. Annual Review of Biomedical Data Science 1, 93-114 Pdf file.

 

O. Kley, C. Klüppelberg, and G. Reinert (2018) Conditional risk measures in a bipartite market structure. Scandinavian Actuarial Journal 2018, 328-355. Pdf file.

 

A.E. Wegner, L. Ospina-Forero, R.E. Gaunt, C.M. Deane, and G. Reinert (2018) Identifying networks with common organizational principles. Journal of Complex Networks, 6, 887-913. Pdf file.

 

M.A. Riolo, G.T. Cantwell, G. Reinert, and M.E.J. Newman (2017) Efficient method for estimating the number of communities in a network. Physical Review E 96: ARTN 032310 Pdf file.

 

M.D. Luecken, M.J.T. Page, A.J. Crosby, S. Mason, G. Reinert and C.M. Deane (2017) CommWalker: correctly evaluating modules in molecular networks in light of annotation bias. Bioinformatics, 34(6), pp.994-1000. Pdf file.

 

A. Elliott, E. Leicht, A. Whitmore, G. Reinert, and F. Reed-Tsochas (2017) A nonparametric significance test for sampled networks. Bioinformatics 34, 64-71. Pdf file.

 

C. Ley, G. Reinert, and Y. Swan (2017) Distances between nested densities and a measure of the impact of the prior in Bayesian statistics. Annals of Applied Probability 27:216-241. Pdf file.

 

R. Gaunt, A. Pickett, and G. Reinert (2017) Chi-square approximation by Stein's method with application to Pearson's statistic. Annals of Applied Probability 27, 720-756. Pdf file.

 

A. Anastasiou and G. Reinert (2017) Bounds for the normal approximation of the maximum likelihood estimator. Bernoulli 23, 191-218. Pdf file.

 

C.Ley, G. Reinert, and Y. Swan (2017) Stein’s method for comparison of univariate distributions. Probability Surveys 14, 1-52. Pdf file.

 

M. E. J. Newman and G. Reinert (2016) Estimating the number of communities in a network. Phys. Rev. Lett. 117, 078301. Pdf file.

 

W. Ali, A. E. Wegner, R.E. Gaunt, C. M. Deane, and G. Reinert (2016) Comparison of large networks with sub-sampling strategies. Scientific Reports 6, 28955. Pdf file.

 

M. Coulson, R. E. Gaunt, and G. Reinert (2016) Poisson approximation of subgraph counts in stochastic block models and a graphon model. ESAIM: PS 20, 131–142. Pdf file.

 

O. Kley, C. Klüppelberg, and G. Reinert (2016) Risk in a Large Claims Insurance Market with Bipartite Graph Structure. Operations Research 64, 1159-1176. Pdf file.

 

J. Ren, K. Song. M. Deng, G. Reinert, C.H. Cannon, and F. Sun (2015) Inference of Markovian Properties of Molecular Sequences from NGS Data and Applications to Comparative Genomics. Bioinformatics 32, 993-1000. Pdf file.

 

W. Ali, T. Rito, G. Reinert, F. Sun, and C. M. Deane (2014). Alignment-free protein interaction network comparison. Bioinformatics 30, i430-i437. Pdf file.

 

L. Goldstein and G. Reinert (2013) Stein's method for the Beta distribution and the Pòlya-Eggenberger Urn. Journal of Applied Probability 4, 1187-1205. Pdf file.

 

A.D. Barbour and G. Reinert (2013) Asymptotic behaviour of gossip processes and small-world networks. Advances in Applied Probability 45, 895-1201. Pdf file.

 

K. Song, J. Ren, G. Reinert, M. Deng, M. S. Waterman, F. Sun (2013) New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. Briefings in Bioinformatics 10.1093/bib/bbt067. Pdf file.

 

J. Ren, K. Song, F. Sun, M. Deng, and G. Reinert (2013) Multiple Alignment-free Sequence Comparison. Bioinformatics 29, 2690-2698. Pdf file.

 

A.D. Barbour and G. Reinert (2013) Approximating the epidemic curve. Electronic Journal of Probability 18, Article 54. Pdf file.

 

Q. Luo, R. Hamer, G. Reinert and C.M. Deane (2013) Local Network Patterns in Protein-Protein Interfaces. PLOS ONE 8, e5703. Pdf file.

 

M. Gomes, R. Hamer, G. Reinert, C.M. Deane. (2012) Mutual information and variants for protein domain-domain contact prediction. BMC Research Notes 5, 472. Pdf file.

 

T. Rito, C.M. Deane, and G. Reinert (2012) The importance of age and high degree, in Protein-Protein interaction networks. Journal of Computational Biology, 19, 785-795. Pdf file.

 

Z. Zhai, G. Reinert, K. Song, M.S. Waterman, Y. Luan, and F. Sun (2012) Normal and Compound Poisson Approximations for Pattern Occurrences in NGS Reads. Journal of Computational Biology 19, 839-854. Pdf file.

 

K. Lin and G. Reinert. (2012) Joint vertex degrees in the inhomogeneous random graph model G(n, {Pij.}), Adv. Applied Probability 44, 139-165. Pdf file.

 

A.D. Barbour and G. Reinert (2011) The shortest distance in random multi-type intersection graphs. Random Structures and Algorithms 39, 179-209. Pdf file.

 

X. Liu, L.Wan, G. Reinert, M.S. Waterman, F. Sun, J. Li (2011) New powerful statistics for alignment-free sequence comparison under a pattern transfer model. Journal of Theoretical Biology 284, 106-116. Pdf file.

 

W. Ali, C. Deane and G. Reinert (2011) Protein Interaction Networks and Their Statistical Analysis. Handbook of Statistical Systems Biology (eds M.P.H. Stumpf, D.J. Balding and M. Girolami), John Wiley & Sons Ltd, Chichester, UK. Pdf file.

 

G. Reinert (2011) Gaussian approximation of functionals: Malliavin calculus and Stein's method. Surveys in Stochastic Processes (eds: J. Blath, P. Imkeller and S. Roelly), European Mathematical Society Publishing House, Zurich, pp. 107-126. Pdf file.

 

I. Nourdin, G. Peccati and G. Reinert (2010) Stein's method and stochastic analysis of Rademacher functionals. Electronic Journal of Probability 15, 1703-1742. Pdf file.

 

I. Nourdin, G. Peccati and G. Reinert (2010) Invariance principles for homogeneous sums: universality of Gaussian Wiener chaos. The Annals of Probability 38, 1947-1985. Pdf file.

 

G. Reinert and A. Röllin (2010) U-statistics and random subgraph counts: Multivariate normal approximation via exchangeable pairs and embedding. Journal of Applied Probability 47, 378-393. Pdf file.

 

T. Rito, Z. Wang, G. Reinert and C.M. Deane (2010) How threshold behaviour affects the use of subgraphs for network comparison. Bioinformatics 26, vi611-7. Pdf file.

 

R. Hamer, Q. Luo, J. P. Armitage, G. Reinert and C.M. Deane (2010) i-Patch: Inter-Protein Contact Prediction using Local Network Information. Proteins 78, 2781-97. Pdf file.

 

R. Hamer, P-Y. Chen, J.P. Armitage, G. Reinert and C.M. Deane (2010) Deciphering chemotaxis pathways using cross species comparisons. BMC Systems Biology 4 (11 January 2010) Pdf file.

 

Z.Y. Zhai, S.Y. Ku, Y.H. Luan, G. Reinert, M.S. Waterman and F.Z. Sun (2010) The Power of Detecting Enriched Patterns: An HMM Approach. Journal of Computational Biology 17, 581-592. Pdf file.

 

L. Wan, G. Reinert, F. Sun, and M.S. Waterman (2010) Alignment-free Sequence Comparison (II) : Theoretical Power of Comparison Statistics. Journal of Computational Biology 17, 1467-1490. Pdf file.

 

G. Reinert and A. Roellin (2009) Multivariate normal approximation with Stein's method of exchangeable pairs under a general linearity condition. The Annals of Probability 37, 2150-2173. Pdf file.

 

G. Reinert, D. Chew, F. Sun, and M.S. Waterman (2009) Alignment-Free Sequence Comparison (I): Statistics and Power. Journal of Computational Biology 16, 1-20 Pdf file.

 

I. Nourdin, G. Peccati and G. Reinert (2009) Second order Poincaré inequalities and CLTs on Wiener space. Journal of Functional Analysis 257, 593-609. Pdf file.

 

J.-P. Onnela, N.F. Johnson, S. Gourley, G. Reinert and M. Spagat (2009) Sampling bias in systems with structural heterogeneity and limited internal diffusion. Europhysics Letters 85, 28001. Pdf file.

 

P. Eichelsbacher and G. Reinert (2008). Stein’s method for discrete Gibbs measures. The Annals of Probability 18, 1588-1618. Pdf file.

 

J. Crowcroft, R. Allsop, A.P. Smith, P. Varaiya, R. Gibbens, M. Bell, P. Key, S. Borst, G. Reinert, K. Briggs, R. Mondragon, S. Zhou, R. Srikant, D. Wischik, R.J. Atkinson, M. Smith, M. Patriksson, D. Ralph, H.R. Kirby, J.M. Brooke, F. Kelly, A. Odlyzko, G. Raina (2008) Optimal resource allocation for multicast sessions in multi-hop wireless networks - Discussion. Philos. T.R. Soc. A 366 (1872):2075-2092 13 Jun 2008.

 

N.F. Johnson, M. Spagat, S. Gourley, J.-P. Onnela, G. Reinert (2008). Bias in epidemiological studies of conflict mortality. Journal   of Peace Research, 45 (5), September 2008, pp.653-663. Pdf file.

 

G. Reinert, M.S. Waterman (2008).The length of the longest exact position match in a Markov sequence. IWAP (International Workshop on Applied Probability)  2008 Conference Proceedings Pdf file . Extended version.

 

P. Eichelsbacher and G. Reinert (2008). Stein's method for discrete Gibbs measures. The Annals of Applied Probability 2008, 18, No. 4, 1588--1618 font> Pdf file.

 

G. Reinert and M.S. Waterman (2007). On the length of the longest exact position match in a random sequence. Transactions on Computational Biology and Bioinformatics 4,  153 - 156. Pdf file.

 

P. Chen, C. Deane, G. Reinert (2007). A statistical approach using network structure in the prediction of protein characteristics. Bioinformatics 23, 2314-2321.Pdf file.

 

L. Goldstein and G. Reinert (2006). Total Variation Distance for Poisson Subset Numbers. Annals of Combinatorics (2006), vol 10, 333--341.Pdf file.

 

A.D. Barbour and G. Reinert (2006). Discrete small world networks. Electronic J. Probab. 11, 1234--1283 (2006). Pdf file

 

G. Reinert (2005). Three general approaches to Stein's method. In: A Program in Honour of Charles Stein: Tutorial Lecture Notes. A.D. Barbour, L.H.Y. Chen, eds. World Scientific, Singapore (2005), 183-221. Last draft: Pdf file

 

Goldstein and G. Reinert (2005). Zero biasing in one and higher dimensions, and applications. In: Proceedings of the conference in honor of Charles Stein, A.D. Barbour, L.H.Y. Chen, eds. World Scientific, Singapore (2005), 1-18. Last draft: Pdf file

 

L. Goldstein and G. Reinert (2005). Distributional transformations, orthogonal polynomials, and Stein characterizations. Jour. Theor. Probab. vol 18, pp185-208. Pdf file

In Russian: Obozr. Prikl. Prom. Mat., (OP&PM Surveys in Applied and Industrial Mathematics) 2006, v. 13, No. 1, pp. 28--50. Pdf file

 

G. Reinert, S. Schbath, and M.S. Waterman (2005). Probabilistic and Statistical Properties of Finite Words in Finite Sequences. In: Lothaire: Applied Combinatorics on Words, Cambridge University Press, J. Berstel, D. Perrin, eds. Postscript

 

S. Holmes and G. Reinert (2004). Stein's method for the bootstrap. In: Stein's Method: Expository Lectures and Applications. IMS Lecture Notes 46, Hayward, P. Diaconis and S. Holmes, eds., 95-133. Pdf file

 

M. Huber and G. Reinert (2004). The stationary distribution in the antivoter model: Exact Sampling and Approximations. In: Stein's Method: Expository Lectures and Applications. IMS Lecture Notes 46, Hayward, P. Diaconis and S. Holmes, eds., 79-93. Postscript

 

A.D. Barbour and G. Reinert (2003). Small world networks. Extended abstract for MaPhySto and Dynstoch Workshop on Dynamical Stochastic Modelling in Biology, Copenhagen 2003. Pdf file

 

A.D. Barbour and G. Reinert (2001). Small Worlds. Random Structures and algorithms 19, 54 - 74. Postscript Pdf file

 

G. Reinert (2001). Stein's method for epidemic processes. In Complex Stochastic Systems. O.E. Barndorff-Nielsen, D.R. Cox and C. Klueppelberg, eds., Chapman and Hall, Boca Raton etc., 235 -275. Postscript Pdf file

 

A.D. Barbour, R. Gerrard and G. Reinert (2000). Iterates of expanding maps. Probab. Theory Rel. Fields 116, 151 - 180. Postscript Pdf file

 

G. Reinert, S. Schbath, and M.S. Waterman (2000). Probabilistic and Statistical Properties of Words. J. Comp. Bio. 7, 1 - 46. Postscript Pdf file

 

G. Reinert (1999). An introduction to Stein's method and application to empirical measures. In Modelos Estocasticos. M.Gonzalez Barrios and L.G.Gorostiza, eds., Sociedad Matematica Mexicana, 65 - 120. (Proceedings of the Symposium on Probability and Stochastic Processes, Guanajuato, Mexico). Postscript Pdf file

 

G. Reinert and S. Schbath (1999). Compound Poisson approximations for occurrences of multiple words. In Statistics in Molecular Biology and Genetics. F. Seiller-Moiseiwitsch, ed., IMS Lecture Notes, Providence, 257 -275. Postscript

 

G. Reinert and S. Schbath (1998). Compound Poisson and Poisson process approximations for occurrences of multiple words. J. Comp. Bio. 5, 223 - 253. Postscript

 

G. Reinert (1998). Couplings for normal approximations with Stein's method. In Microsurveys in Discrete Probability. D. Aldous, J. Propp eds., Dimacs series. AMS, 193 - 207. Postscript Pdf file

 

L. Goldstein and G. Reinert (1997). Stein's method and the zero bias transformation with application to simple random sampling. Ann. Appl. Probab. 7, 935 - 952. Postscript

 

L. Goldstein and G. Reinert (1997). Stein's method and the zero bias transformation with application to simple random sampling. USC Technical report. Postscript

 

R. Arratia, D. Martin, G. Reinert and M. S. Waterman (1996). Poisson approximation for long repeats in a random sequence with application to sequencing by hybridization. J. Comp. Biol. 3, 425 - 463. Postscript

 

 

G. Reinert (1995) A weak law of large numbers for empirical measures via Stein's method. The Annals of Probability 23, 334-354 Pdf file

 

G. Reinert (1995) The asymptotic evolution of the General Stochastic Epidemic. Annals of Applied Probability 5, 1061-1086. Pdf file

 

G. Reinert (1992) A threshold theorem for the general stochastic epidemic via a discrete approach. Statistics & Probability Letters 14, 85-90. Pdf file





Software

Software supporting the paper A two-component copula with links to insurance, by S. Ismail, G.Yu, G. Reinert and T. Maynard


Software supporting the paper Triad-based Comparison and Signatures of Directed Networks, by X. Xu and G. Reinert


An R package for alignment-free network comparison


COGENT: COnsistency of Gene Expression NeTworks




Talks

Chi-square approximations with Stein's method

(YouTube)

Statistical analysis of networks

(YouTube)

A short introduction to Stein's method

(YouTube)

Bootstrapping in regular graphs


Statistics for Watts-Strogatz Small World networks


Statistical Inference for Networks: graduate lecture


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