Research Interests

My research interests are twofold.

1. Mathematically, I am interested in:
Symbolic dynamics in general and substitution dynamical systems in particular.

2. Biologically I am interested int:
Applying tools from symbolic dynamics and other mathematical fields to study questions in genomics. I am currently interested in questions from metagenomics/bacterial community reconstruction which I address via convex optimization methods. I also utilize entropy and topological pressure-based techniques to study genomics questions such as coding sequence density estimation, and other biological problems like the decoding problem in neuroscience.
Markov Chain









Publications and Preprints



[17] Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D. et al. Critical Assessment of Metagenome Interpretation − a benchmark of computational metagenomics software.
Under review, Nature Methods, 2017.
Preprint

[16] McClelland, J. and Koslicki, D. EMDUnifrac: Exact linear time computation of the Unifrac metric and identification of differentially abundant organisms
Submitted to SIAM Journal on Applied Math., 2016.
Preprint

[15] Koslicki, D. and Novak, M. Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations
Submitted to J. Mathematical Biology, 2016.
Preprint

[14] Koslicki, D. and Falush, D. MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
mSystems, 1 (3) e00020-16, 2016.
Article

[13] Serghei Mangul, Loes M Olde Loohuis, Anil Ori, Guillaume Jospin, David Koslicki, Harry Taegyun Yang, Timothy Wu, Marco P Boks, Catherine Lomen-Hoerth, Martina Wiedau-Pazos, Rita Cantor, Willem M de Vos, Rene S Kahn, Eleazar Eskin, Roel A. Ophoff. Total RNA Sequencing reveals microbial communities in human blood and disease specific effects
Under revision, 2016.
Preprint

[12] Chatterjee, S., Shahrivar, D., Koslicki, D., Walker, A., Francis, S., Fraser, L., Vehkapera, M., Lan, Y., and Corander, J. ARK: Aggregation of reads by k-means for estimation of bacterial community composition
PLoS ONE 10(10): e0140644, 2015.
Article / Provisional Preprint

[11] Mangul, S. and Koslicki, D. Reference-free comparison of microbial communities via de Bruijn graphs
Accepted, ACM-BCB, 2015.
Article / Preprint

[10] Holzinger, A., Hörtenhuber, M., Mayer, C., Bachler, M., Wassertheurer, S., Pinho, A.J., and Koslicki, D. On entropy-based data mining.
In Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, pages 209--226. Springer, Berlin Heidelberg, 2014.
Article / Preprint

[9] D. Koslicki, S. Foucart, G. Rosen, WGSQuikr: fast whole-genome shotgun metagenomic classification.
PLoS ONE, 9(3), e91784, 2014.
Article / Preprint

[8] S. Foucart, D. Koslicki, Sparse recovery by means of nonnegative least squares.
IEEE Signal Processing Letters, 21(4), 498--502, 2014.
Article / Preprint / Reproducibles

[7] D. Koslicki, M. Denker Substitution Markov chains and Martin boundaries
In print, Rocky Mountain Journal of Mathematics, 2014.
Preprint / Article

[6] S. Chatterjee, D. Koslicki, S. Dong, N. Innocenti, L. Cheng, L., Y. Lan, M. Vehkapera, M. Skoglund, L.K. Rasmussen, E. Aurell, J. Corander SEK: sparsity exploiting k-mer-based estimation of bacterial community composition
Accepted, Bioinformatics, 2014.
Article / Preprint

[5] D. Koslicki, D.J. Thompson Coding sequence density estimation via topological pressure
In press, Journal of Mathematical Biology, 2014.
Article / Preprint

[4] D. Koslicki, S. Foucart, G. Rosen, Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing.
Bioinformatics, 29(17), 2096--2102, 2013.
Article / Preprint

[3] D. Koslicki Substitution Markov chains with applications to molecular evolution.
PhD thesis, Pennsylvania State University, 2012.
Preprint

[2] D. Koslicki An alignment-free indel model of molecular evolution. 2011.
Preprint

[1] D. Koslicki Topological entropy of DNA sequences.
Bioinformatics, 27(8):1061-1067, 2011.
Article / Preprint


Thesis


My dissertation: Substitution Markov chains with applications to molecular evolution.




Software

Quikr speed

Most of the methods I have developed can be access on my github page. Note that some of these projects are works in progress, so may not work yet.