Photo of David Koslicki

David Koslicki

Associate Professor

Affiliation(s):

  • School of Electrical Engineering and Computer Science
  • Computer Science and Engineering
  • Eberly College of Science
  • Huck Institutes of the Life Sciences

W354 Westgate

dmk333@psu.edu

814-865-1611

Research Areas:

Computational Science; Data Science and Artificial Intelligence; Theoretical Computer Science

 
 

 

Education

Publications

Book, Chapters

  • Andreas Holzinger, H\"ortenhuber, Matthias, Christopher Mayer, Martin Bachler, Siegfried Wassertheurer, Armando J Pinho and David Koslicki, 2014, On entropy-based data mining, Springer, Berlin, Heidelberg, pp. 209--226

Journal Articles

  • Fernando Meyer, Andreas Bremges, Peter Belmann, Stefan Janssen, Alice C McHardy and David Koslicki, 2019, "Assessing taxonomic metagenome profilers with OPAL", Genome biology, 20, (1), pp. 51
  • David Koslicki and Hooman Zabeti, 2019, "Improving MinHash via the containment index with applications to metagenomic analysis", Applied Mathematics and Computation, 354, pp. 206--215
  • Nathan LaPierre, Serghei Mangul, Mohammed Alser, Igor Mandric, Nicholas C Wu, David Koslicki and Eleazar Eskin, 2019, "MiCoP: microbial community profiling method for detecting viral and fungal organisms in metagenomic samples", BMC genomics, 20, (5), pp. 423
  • Jason McClelland and David Koslicki, 2018, "EMDUniFrac: exact linear time computation of the unifrac metric and identification of differentially abundant organisms", Journal of mathematical biology, 77, (4), pp. 935--949
  • David Koslicki and Mark Novak, 2018, "Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations", Journal of mathematical biology, 76, (4), pp. 877--909
  • Daniel McDonald, V\'azquez-Baeza, Yoshiki, David Koslicki, Jason McClelland, Nicolai Reeve, Zhenjiang Xu, Antonio Gonzalez and Rob Knight, 2018, "Striped UniFrac: enabling microbiome analysis at unprecedented scale", Nature methods, 15, (11), pp. 847
  • David Koslicki, 2018, "The Biomedical Data Translator Program: Conception, Culture, and Community", Clinical and Translational Science, (https://doi.org/10.1111/cts.12592), pp. 1--4
  • David Koslicki, 2018, "Toward a universal biomedical data translator", Clinical and Translational Science, (doi.org/10.1111/cts.12591), pp. 1--5
  • Loes M Olde Loohuis, Serghei Mangul, Anil Ori, Guillaume Jospin, David Koslicki, Harry Taegyun Yang, Timothy Wu, Marco P Boks, Catherine Lomen-Hoerth, Martina Wiedau-Pazos and others, 2018, "Transcriptome analysis in whole blood reveals increased microbial 1 diversity in schizophrenia", Nature Translational Psychiatry, 8, (96), pp. 9
  • Alexander Sczyrba, Peter Hofmann, Peter Belmann, David Koslicki, Stefan Janssen, Dr\"oge, Johannes, Ivan Gregor, Stephan Majda, Jessika Fiedler, Eik Dahms and others, 2017, "Critical assessment of metagenome interpretation—a benchmark of metagenomics software", Nature methods, 14, (11), pp. 1063
  • Mitra Ansariola, Molly Megraw and David Koslicki, 2017, "IndeCut evaluates performance of network motif discovery algorithms", Bioinformatics, 34, (9), pp. 1514--1521
  • David Koslicki and Daniel Falush, 2016, "MetaPalette: A K-mer painting approach for metagenomic taxonomic profiling and quantification of novel strain variation", MSystems, 1, (3), pp. e00020--16
  • David Koslicki, Manfred H Denker and others, 2016, "Substitution Markov chains and Martin boundaries", Rocky Mountain Journal of Mathematics, 46, (6), pp. 1963--1985
  • David Koslicki, Saikat Chatterjee, Damon Shahrivar, Alan Walker, Suzanna C Francis, Louise J Fraser, Vehkaper\"a, Mikko, Yueheng Lan and Jukka Corander, 2015, "ARK: Aggregation of Reads by k-Means for estimation of bacterial community composition", PloS one, 10, (10), pp. e0140644
  • David Koslicki and Daniel James Thompson, 2015, "Coding sequence density estimation via topological pressure", Journal of mathematical biology, 70, (1-2), pp. 45--69
  • Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Vehkaper\"a, M, Mikael Skoglund, Lars K Rasmussen, Erik Aurell and others, 2014, "SEK: Sparsity exploiting k-mer-based estimation of bacterial community composition", Bioinformatics; accepted with Minor Revision on 18-03-2014
  • Simon Foucart and David Koslicki, 2014, "Sparse recovery by means of nonnegative least squares", IEEE Signal Processing Letters, 21, (4), pp. 498--502
  • David Koslicki, Simon Foucart and Gail Rosen, 2014, "WGSQuikr: fast whole-genome shotgun metagenomic classification", PloS one, 9, (3), pp. e91784
  • David Koslicki, Simon Foucart and Gail Rosen, 2013, "Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing", Bioinformatics, 29, (17), pp. 2096--2102
  • David Koslicki, 2011, "Topological entropy of DNA sequences", Bioinformatics, 27, (8), pp. 1061--1067

Conference Proceedings

  • Soha Hassoun, Yasser El-Manzalawy, Georg Gerber, David Koslicki and Gail Rosen, 2019, "Workshop on Microbiomics, Metagenomics, and Metabolomics", pp. 618--618
  • Serghei Mangul and David Koslicki, 2016, "Reference-free comparison of microbial communities via de Bruijn graphs", (http://doi.acm.org/10.1145/2975167.29751), pp. 68--77

Other

  • David Koslicki, 2012, "SUBSTITUTION MARKOV CHAINS WITH APPLICATIONS TO MOLECULAR EVOLUTION"

Research Projects

Honors and Awards

Service

Service to Penn State:

Service to External Organizations:

 


 

About

The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research in fields.

We offer B.S. degrees in electrical engineering, computer science, computer engineering and data science and graduate degrees (master's degrees and Ph.D.'s) in electrical engineering and computer science and engineering. EECS focuses on the convergence of technologies and disciplines to meet today’s industrial demands.

School of Electrical Engineering and Computer Science

The Pennsylvania State University

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Department of Computer Science and Engineering

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Department of Electrical Engineering

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