Gesine Reinert’s Publications

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 1:1, 93-114.
O. Kley, C. Klüppelberg, and G. Reinert (2018). Conditional risk measures in a bipartite market structure. Scandinavian Actuarial Journal 2018 (4) (2018), 328-355.
A.E. Wegner, L. Ospina-Forero, R.E. Gaunt, C.M. Deane, and G. Reinert, G. (2018). Identifying networks with common organizational principles. Journal of Complex Networks, Apr 2.
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(3): ARTN 032310
A. Elliott, E. Leicht, A. Whitmore, G. Reinert, and F. Reed-Tsochas (2017). A nonparametric significance test for sampled networks. Bioinformatics 34(1), 64-71.
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(1):216-241.
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(2), 720-756.
A. Anastasiou and G. Reinert (2017). Bounds for the normal approximation of the maximum likelihood estimator. Bernoulli 23(1) , 191-218.
C.Ley, G. Reinert and Y. Swan (2017). Stein’s method for comparison of univariate distributions. Probability Surveys 14, 1-52.
M. E. J. Newman and G. Reinert (2016). Estimating the number of communities in a network. Phys. Rev. Lett. 117, 078301.
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..
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.
O. Kley, C. Klüppelberg, and G. Reinert (2016). Risk in a Large Claims Insurance Market with Bipartite Graph Structure. Operations Research 64(5), 1159-1176.
Ren, J., Song, K., Deng, M., Reinert, G., Cannon, C.H., & Sun, F. (2015). Inference of Markovian Properties of Molecular Sequences from NGS Data and Applications to Comparative Genomics. Bioinformatics.
C. Ley, G. Reinert and Y. Swan (2014). Approximate computation of expectations : a canonical Stein operator. Preprint.
L. Goldstein and G. Reinert (2013) Stein’s method for the Beta distribution and the Pòlya-Eggenberger Urn. Journal of Applied Probability 4
A.D. Barbour and G. Reinert (2013) Asymptotic behaviour of gossip processes and small-world networks. Advances in Applied Probability 45, 895-1201.
K. Song, J. Ren, G. Reinert, M. Deng, M. S. Waterman and F. Sun (2013) New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. Briefings in Bioinformatics, 10.1093/bib/bbt067.
J. Ren, K. Song, F. Sun, M. Deng and G. Reinert (2013) Multiple Alignment-free Sequence Comparison. Bioinformatics, Vol 29, Issue 21, 2690-2698.
A.D. Barbour and G. Reinert (2013 issue 18) Approximating the epidemic curve. Electronic Journal of Probability, No. 54, ISSN: 1083-6489.
Q. Luo, R. Hamer, G. Reinert and C.M. Deane (2013 issue 8(3)) Local Network Patterns in Protein-Protein Interfaces. PLOS ONE, e5703.
M. Gomes, R. Hamer, G. Reinert, C.M. Deane. (2012) Mutual information and variants for protein domain-domain contact prediction. BMC Research Notes 2012, 5:472. DOI: 10.1186/1756-0500-5-472.
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(6): 785-795.
Z. Zhai., G. Reinert, K. Song, M.S. Waterman, Y. Luan, and F. Sun. (2012) Normal and Compound Poisson Approximations for Pattern Occurences in NGS Reads. Journal of Computational Biology. 19(6):839-854.
K. Lin and G. Reinert. (2012) Joint vertex degrees in the inhomogeneous random graph model G(n, {P_ij.}), Adv. Applied Probability 44, 139-165.
A.D.Barbour and G. Reinert (2011) The shortest distance in random multi-type intersection graphs. Random Structures and Algorithms, 39, 179-209.
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
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.*nbsp;
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.
I. Nourdin, G. Peccati and G.Reinert (2010) Stein’s method and stochastic analysis of Rademacher functionals.
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.
G. Reinert and A. Röllin (2010) U-statistics and random subgraph counts: Multivariate normal approximation via exchangeable pairs and embedding. J. Appl. Probab. 47 (2010). In Press.
T. Rito, Z. Wang, G. Reinert and C.M. Deane (2010) How threshold behaviour affects the use of subgraphs for network comparison. Bioinformatics, 26 (18), vi611-7.
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 (13), 2781-97.
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 2010, 4:3 (11 January 2010)
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(4):581-592.
Lin Wan, Gesine Reinert, Fengzhu Sun, and Michael S. Waterman. Alignment-free Sequence Comparison (II) : Theoretical Power of Comparison Statistics. Journal of Computational Biology. November 2010, 17(11): 1467-1490
G. Reinert and A. Roellin, Multivariate normal approximation with Stein’s method of exchangeable pairs under a general linearity condition. The 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, arXiv:0811.4485
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 Computational Biology, 4 (2008), e1000118
G Reinert, M.S. Waterman (2008) On the length of the longest exact position match in Markov sequence. IWAP (International Workshop on Applied Probability) 2008 Conference Proceedings, to appear. Pdf file. Extended version
P. Eichelsbacher and G. Reinert, ‘Stein’s method for discrete Gibbs measures’ in The Annals of Probability, 18 (2008), –1618
Johnson, N.F., Spagat, M., Gourley, S., Onnela, J.P., Reinert, G. (2008) Bias in epidemiological studies of conflict mortality. Journal of Peace Research, 45 (5), 653-663.
Crowcroft, J., Allsop, R., Smith, A.P., Varaiya, P., Gibbens, R., Bell, M., Key, P., Borst, S., Reinert, G., Briggs, K., Mondragon, R., Zhou, S., Srikant, R., Wischik, D., Atkinson, R.J., Smith, M., Patriksson, M., Ralph, D., Kirby, H.R., Brooke, J.M., Kelly, F., Odlyzko, A., Raina, G. (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
Pao-Yang Chen, Charlotte M. Deane and Gesine Reinert, A Statistical Approach Using Network Structure in the Prediction of Protein Characteristics Bioinformatics 23 (2007), 2314-2321
G. Reinert and M.S. Waterman,On the length of the longest exact position match in a random sequence, Transactions of Computational Biology and Bioinformatics, 4 (2007), 153-156
Snijders, T.A.B., Robinson, T., Atkinson, A.C., Riani, M., Gormley, I.C., Murphy, T.B., Sweeting, T., Leslie, D.S., Longford, N.T., Kent, J.T., Lawrance, T., Airoldi, E.M., Besag, J., Blei, D., Fienberg, S.E., Breiger, R., Butts, C.T., Doreian, P., Batageli, V., Ferligoj, A., Draper, D., van Duijn M.A.J., Faust, K., Petrescu-Prahova, M., Forster, J.J., Gelman, A., Goodreau, S.M., Greenwood, P.E., Gruenberg, K., Francis, B., Hennig, C., Hoff, P.D., Hunter, D.R., Husmeier, D., Glasbey, C., Krackhardt, D., Kuha, J., Skrondal, A., Lawson, A., Liao, T.F., Mendes, B., Draper, D., Reinert, G., Richardson, S., Lewin, A., Titterington, D.M., Wasserman, S., Werhil, A.V., Ghazal, P. (2007). Discussion on the paper by Handcock, Raftery and Tantrum.J. Roy. Stat. Soc. A STA 170:322-354 Feb 2007
L. Goldstein and G. Reinert, ‘Total Variation Distance for Poisson Subset Numbers’ in Annals of Combinatorics, 10 (2006), 331-341
A.D. Barbour and G. Reinert. Discrete small world networks. Electronic Journal of Probability 11 (2006), 1234—1283. [PDF version]
L. Goldstein and G. Reinert. Distributional transformations, orthogonal polynomials, and Stein characterizations. Journal of Theoretical Probability, 18 (2005), 185-208. [PDF version]
This paper also appeared in Russian translation, Obozr. Prikl. Prom. Mat., (OP&PM Surveys in Applied and Industrial Mathematics) 2006, v. 13, No. 1, pp. 28—50.
L. 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
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. [PDF version]
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., 268-352. [Postscript version]
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
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. Small worlds. Random Structures and Algorithms 19, 54-74.(2001)
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
G. Reinert (2001) Assessing the distance to the Gaussian distribution for random measures via Stein’s method – Unpublished manuscript
A.D. Barbour, R.M. Gerrard and G. Reinert. Iterates of expanding maps. Probab. Theory Rel. Fields116, 151-180. (2000)
G. Reinert, S. Schbath and M.S. Waterman.Probabilistic and statistical properties of words.J. Comp. Biol. 7, 1-46 (2000)
G. Reinert (1999) An introduction to Stein’s method and application to empirical measures.In Modelos Estocasticos. M. Gonzalez and L.G. Gorostiza, eds., Sociedad Matematica Mexicana, 65-120. (Proceedings of the Symposium of Probability and Stochastic Processes, Guanajuato, Mexico). Postscript. Pdf file
G. Reinert and S. Schbath (1999) Compound Poisson approximations for occurences 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 occurences of multiple words in Markov chains. J. Comp. Biol.5, 223-253
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. PostscriptPDF 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.
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
G. Reinert (1995) A weak law of large numbers for empirical measures via Stein’s method. Ann. Probab.5, 23, 334-354
G. Reinert (1995) The asymptotic evolution of the General Stochastic Epidemic. Ann. Appl. Probab.5, 1061-1086.
G. Reinert (1992) A threshold theorem for the general stochastic epidemic via a discrete approach. Statistics & Probability Letters 14, 85-90.