István Miklós

Studies

• 1992-1998, ELTE TTK, biology-chemistry teacher
• 1993-1998, ELTE TTK, mathematics teacher
• 1998-2001, ELTE TTK, theoretical biology and ecology PhD school
• 2002-2002, University of Oxford, Department of Stochastics, Genome Analysis and Bioinformatics group, postdoctoral fellow

Research area

• Bioinformatics: dynamic programming, stochastic models, genome rearrangement
• Theoretical Computer Science: computational complexity of counting and sampling, #P-completeness, FPRAS, FPAUS.
• Markov chain Monte Carlo, speed of convergence of Markov chains
• Graph degree sequence problems

Teaching

• Budapest Semesters in Mathematics: Algorithms of Bioinformatics, Introduction to Combinatorics
• BMGE: Stochastic models in bioinformatics
• CEU: Theory of Algorithms

Awards, stipends, fellowships

• 2005: Young researcher award of the HAS
• 2006-2009: Bolyai János stipends
• 2010: Gyires Béla award

Organizing conferences

• Bayesian Phylogeny, 2008 Rényi Institute, organizer
• RECOMB Comparative Genomics, 2009 Budapest, co-chair
• Dagstuhl Seminar 16071: Pattern Avoidance and Genome Sorting, co-organizer
• Dagstuhl Seminar 18451: Genomics, Pattern Avoidance and Statistical Physics, co-organizer

Selected publications

• Miklós, I. & Podani, J. (2004) Randomization of presence/absence matrices: comments and new algorithms Ecology, 85:86-92.
• Lunter, G.A., Miklós, I., Drummond, A., Jensen, J.L., & Hein, J. (2005) Bayesian Coestimation of Phylogeny and Sequence Alignment BMC Bioinformatics, 6:83.
• Miklós, I., Lunter, G. A. & Holmes, I. (2004) A 'long indel' model for evolutionary sequence alignment. Mol. Biol. Evol., 21(3):529-540.
• Novák, Á., Miklós, I., Lyngsoe, R., Hein, J. (2008) StatAlign: An Extendable Software Package for Joint Bayesian Estimation of Alignments and Evolutionary Trees. Bioinformatics, 24(20):2403-2404
• Kim, H., Toroczkai, Z., Erdős, P., Miklós, I., Székely, L. (2009) Degree-based graph construction. J. Phys. A., 42(39): 392001.1-392001.10.
• Miklós, I. &Meyer, I.M. (2005) A linear memory algorithm for Baum-Welch training. BMC Bioinformatics 6:231.
• Miklós, I., Erdős, P., Soukup, L. (2013) Towards random uniform sampling of bipartite graphs with given degree sequence Electronic Journal of Combinatorics 20(1):P16
• Erdős, L.P., Miklós, I., Toroczkai, Z. (2015) A decomposition based proof for fast mixing of a Markov chain over balanced realizations of a joint degree matrix. SIAM J. Discr. Math. 29, 481-499
• Erdős, L.P., Miklós, I., Toroczkai, Z. (2018) New classes of degree sequences with fast mixing swap Markov chain sampling Combinatorics, Probability and Computing, 27(2):186-207.
• Miklós, I. (2019) Computational Complexity of Counting and Sampling, Chapman and Hall/CRC, ISBN 9781138035577 - CAT# K31733