Academics

Welcome

Welcome. Here is some information about what I am doing. Please do not hesitate to contact me if you have any questions!

Research Interests

Have you heard about the phenomenon that everyone is six handshakes away from the President? The six degrees of separation hypothesis relates to a model of social interactions that is phrased in terms of a network - individuals are nodes, and two individuals are linked if they know each other. Networks pop up in a variety of contexts, and recently much attention has been given to the randomness in such networks. My main research interest at the moment are network statistics to investigate such networks in a statistically rigorous fashion. Often this will require some approximation, and approximations in statistics are another of my research interests. It turns out that there is an excellent method to derive distances between the distributions of random quantities, namely Stein's method, a method I have required some expertise in over the years. The general area of my research falls under the category Applied Probability and many of the problems and examples I study are from the area of Computational Biology (or bioinformatics, if you prefer that name).

Recent Publications

• A.D. Barbour and G. Reinert , 'The shortest distance in random multi-type intersection graphs' in Random Structures and Algorithms, 39 (2011), 179-209
• Xuemei Liu; Lin Wan; Gesine Reinert; Michael S Waterman; Fengzhu Sun; Jing Li , 'New powerful statistics for alignment-free sequence comparison under a pattern transfer model' in Journal of Theoretical Biolog, 284 (2011), 106-116
• 'Protein Interaction Networks and Their Statistical Analysis' in Handbook of Statistical Systems Biology, ed. M. P. H. Stumpf, D. J. Balding and M. Girolami (John Wiley & Sons, Ltd, 2011)
• 'Gaussian approximation of functionals: Malliavin calculus and Stein’s method' in Surveys in Stochastic Processes, ed. Blath,J, Imkeller, P, and Roelly, S. (European Mathematical Society Publishing House,, 2011)
• I. Nourdin, G. Peccati, and G. Reinert , 'Stein's method and stochastic analysis of Rademacher functionals' in Elect. J. Probab., 15 (2010), 1703-1742
• G. Reinert and A. Roellin, 'U-statistics and random subgraph counts: Multivariate normal approximation via exchangeable pairs and embedding' in J. Appl. Probab., 47 (2010), 378-393
• I. Nourdin, G. Peccati, and G. Reinert , ' Invariance principles for homogeneous sums: universality of Gaussian Wiener chaos' in The Annals of Probability , 38 (2010), 1947-1985
• T. Rito, Z. Wang. C.M. Deane and G. Reinert , ' How threshold behaviour affects the use of subgraphs for network comparison' in Bioinformatics, 26 (2010), vi611-7
• Hamer R, Luo Q, Armitage JP, Reinert G, Deane CM, ' i-Patch: Inter-Protein Contact Prediction using Local Network Information' in Proteins , 78 (2010), 2781-97
• Hamer R, Chen PY, Armitage JP, Reinert G, Deane CM, 'Deciphering chemotaxis pathways using cross species comparisons' in BMC Syst Biol., 4 (2010), 3
• G. Reinert and A. Roellin, 'Multivariate normal approximation with Stein's method of exchangeable pairs under a general linearity condition' in Annals of Probability, 37 (2009), 2150-2173
• Gesine Reinert, David Chew, Fengzhu Sun, Michael S. Waterman, 'Alignment-Free Sequence Comparison (I): Statistics and Power' in Journal of Computational Biology, 16 (2009), 1-20
• I. Nourdin, G. Peccati and G. Reinert, 'Second order Poincaré inequalities and CLTs on Wiener space' in Journal of Functional Analysis, 257 (2009), 593-609
• J.-P. Onnela, N. F. Johnson, S. Gourley, G. Reinert, and M. Spagat, 'Sampling bias in systems with structural heterogeneity and limited internal diffusion' in Europhysics Letters, 85 (2009), 28001
• Pao-Yang Chen, Charlotte M. Deane and Gesine Reinert, 'Predicting and Validating Protein Interactions Using Network Structure' in PLoS Computuational Biology, 4 (2008), e1000118
• N.F. Johnson, M. Spagat, S. Gourley, J.-P. Onnela, G. Reinert, 'Bias in epidemiological studies of conflict mortality' in Journal of Peace Research, 45 (2008), 653-663
• P. Eichelsbacher and G. Reinert, 'Stein's method for discrete Gibbs measures' in The Annals of Applied Probability, 18 (2008), --1618
• Pao-Yang Chen, Charlotte M. Deane and Gesine Reinert, 'A Statistical Approach Using Network Structure in The Prediction of Protein Characteristics' in Bioinformatics, 23 (2007), 2314–2321
• G. Reinert and M.S. Waterman, 'On the length of the longest exact position match in a random sequence' in Transactions on Computational Biology and Bioinformatics, 4 (2007), 153-156
• L. Goldstein and G. Reinert, 'Total Variation Distance for Poisson Subset Numbers' in Annals of Combinatorics, 10 (2006), 333-341
• A.D. Barbour and G. Reinert, 'Discrete small world networks' in Electronic J. Probab., 11 (2006), 1234-1283
• 'Three general approaches to Stein's method' in A Program in Honour of Charles Stein: Tutorial Lecture Notes, ed. A.D. Barbour, L.H.Y. Chen (World Scientific, Singapore, 2005)
• 'Zero biasing in one and higher dimensions, and applications' in Proceedings of the conference in honor of Charles Stein, ed. A.D. Barbour, L.H.Y. Chen (World Scientific, Singap, 2005)
• L. Goldstein and G. Reinert, 'Distributional transformations, orthogonal polynomials, and Stein characterizations' in Journal of Theoretical Probability, 18 (2005), 185-208
• 'Probabilistic and Statistical Properties of Finite Words in Finite Sequences' in Lothaire: Applied Combinatorics on Words, ed. J. Berstel, D. Perrin (Cambridge University Press, 2005)
• 'Stein's method for the bootstrap' in Stein's Method: Expository Lectures and Applications, ed. P. Diaconis and S. Holmes (IMS Lecture Notes 46, Hayward, 2004)

Academic Biography

• University Lecturer, Department of Statistics, Oxford, and Fellow at Keble College, Oxford (2000 - present)
• Senior Research Fellow, King’s College, Cambridge (1998 - 2000)
• Adjunct Assistant Professor, Department of Mathematics, UCLA, Los Angeles (1996 - 1998)
• Ph.D. in Mathematics, University of Zurich, Title: A weak law of large numbers for empirical measures via Stein's method. Advisor: Prof. A.D. Barbour, D.Phil (1994 - present)
• Lecturer, Department of Mathematics, USC, Los Angeles (1994 - 1996)