In preparation or submitted

[30] K. Flanagan, A. Baradaran-Heravi, K. Dao Duc, Q. Yin, A. C. Spradling, and E. J. Greenblatt, FMRP-dependent production of large dosage-sensitive proteins is highly conserved

[29] K. Flanagan, E. Greenblatt, K. Dao Duc, End-to-end pipeline for differential analysis of pausing in ribosome profiling data

[28] S. Yu, S. Srebnik, K. Dao DucImpact of the Ribosomal Exit Tunnel Geometry on the Nascent Protein Escape

[27] A. Tajmir Riahi, G. Woollard, F. Poitevin, A. Condon, K. Dao Duc, Alignment of 3D Grids Reconstructed from Cryo-EM with Wasserstein distances

[26] J. Mirone, C. Legrand, K. Dao Duc, Orthogonal Outlier Detection and Dimensionality Reduction for MDS using n-Simplices

[25] A. Kushner, A. Petrov, K. Dao Duc, RiboXYZ: A comprehensive database for ribosome structures (link)

In press or published

[24] A. Ecoffet, G. Woollard, A. Kushner, F. Poitevin, K. Dao Duc, (2021) “Application of transport-based metric for continuous interpolation between cryo-EM density maps” [J]. AIMS Mathematics, 2022, 7(1): 986-999. doi: 10.3934/math.2022059

[23] F. Tuorto, K. Dao Duc, C. Legrand (2021) “Analysis of Ribosome Profiling Data” (book chapter, in press), to appear in The Integrated Stress Response, Methods in Molecular BiologySpringer, link

[22] N. Miolane, et al. (2021) “ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results.”  arXiv:2108.09810 link.

[21] D.D. Erdmann-Pham, W. Son, K. Dao Duc*,  Y.S. Song, (2021), “EGGTART: A computational tool to quantify the dynamics of biophysical transport from the inhomogeneous l-TASEP” (* co-senior author), Biophysical Journal, 120, 1309–1313 arXiv

[20] A. Ecoffet, F. Poitevin, K. Dao Duc, (2020), “MorphOT: Transport-based interpolation between EM maps with UCSF ChimeraX”Bioinformatics, btaa1019, link, biorXiv

[19] F. Poitevin, A. Kushner, X. Li, K. Dao Duc (2020), “Structural heterogeneities of the ribosome: New frontiers and opportunities for cryo-EM”, Molecules, 25, 4262. pdf, link

[18]  D.D. Erdmann-Pham, K. Dao Duc, Y.S. Song (2020), “The key parameters that govern translation efficiency”, Cell Systems, linkarXiv, link 2

[17] K. Dao Duc, S. Batra, N. Bhattacharya, J.H.D. Cate and Y.S. Song (2019) “Differences in the path to exit the ribosome across the three domains of life” Nucleic Acids Research, gkz106, (F1000 recommendationlink

[16] K. Dao Duc, Y.S. Song (2018) “The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation”. PLoS Genetics 14(1): e1007166. link

[15] K. Dao Duc, Z.H. Saleem, Y.S. Song (2018) “Theoretical analysis of the distribution of isolated particles in the TASEP: Application to mRNA translation rate estimation.” Physical Review E 97, 012106  (selected as Editor’s suggestion) link

[14] N. Rouach, K. Dao Duc*, J. Sibille*, D. Holcman (2018) “Dynamics of ion fluxes between neurons, astrocytes and the extracellular space during neurotransmission” (Review), 4(1), 1-18 Opera Medica et Physiologica) (* equal contribution) link

[13] M. Wang, K. Dao Duc, J. Fischer, Y.S. Song (2017) “Operator norm inequalities between tensor unfoldings on the partition lattice.” Linear Algebra and its Applications 520: 44-66 link

[12] K. Dao Duc, Z. Schuss, and D. Holcman (2016) “Oscillatory Survival Probability: Analytical and Numerical Study of a Non-Poissonian Exit Time.” SIAM Multiscale Modeling & Simulation 14.2 : 772-798. link

[11] J. Sibille*, K. Dao Duc*, D. Holcman, N. Rouach (2015) “The Neuroglial Potassium Cycle during Neurotransmission: Role of Kir4.1 Channels.” PLoS Computational Biology 11(3): e1004137. link (* equal contribution)

[10] K. Dao Duc, P. Parutto, X. Chen, J. Epsztein, A. Konnerth, D. Holcman, (2015) “Synaptic Dynamics and Neuronal Network Connectivity are reflected in the Distribution of Times in Up states”, Frontiers in Computational Neuroscience, 9, 96. link

[9] K. Dao Duc, C. Lee, P. Parutto, D. Cohen, M. Segal, N. Rouach, et al. (2015) “Bursting Reverberation as a Multiscale Neuronal Network Process Driven by Synaptic Depression-Facilitation”. PLoS ONE 10(5): e0124694. link

[8] D. Holcman, K. Dao Duc, A. Jones, H. Byrne, K. Burrage, (2015), “Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to treshold (MTT) and narrow escape problem”, Journal of mathematical biology, 70.4: 805-828. link

[7] K. Dao Duc, Z. Schuss, D. Holcman, (2014) “Oscillatory decay of the survival probability of activated diffusion across a limit cycle”, Physical Review E 89.3 (2014): 030101 link

[6] K. Dao Duc, D. Holcman, (2013), “Computing the length of the shortest telomeres”, Physical Review Letters, 111, 228104 (highlighted for a Physics viewpoint) link

[5] Z. Xu, K. Dao Duc, D. Holcman, T. Teixeira (2013), “The length of the shortest telomere as the major determinant of the onset of replicative senescence”, Genetics, 194, pp. 847-857 link

[4] K. Dao Duc (2013), “Leibniz dans l’Encyclopédie”, Recherches sur Diderot et sur l’Encyclopédie, 48, 1, 2013, pp. 123-142. link

[3] K. Dao Duc, D. Holcman (2012), “Using default constraints of the spindle assembly checkpoint to estimate the associated chemical rates”, BMC Biophysics; 5(1):1. link

[2] K. Dao Duc, D. Holcman (2010), “Threshold activation for stochastic chemical reactions in microdomains”, Physical Review E. 81 (4(1)): 041107 link

[1] K. Dao Duc, P. Auger, T. Nguyen Huu (2008), “Predator density dependent prey dispersal in a patchy environment with a refuge for the prey”, South African Journal of Science, vol. 104, no5-6, pp. 180-184 link