David Koslicki

Associate Professor of Computer Science and Engineering and Biology

David Koslicki

Research Summary

Developing efficient algorithms to extract insight from high-throughput sequencing data.

Huck Graduate Students

Huck Affiliations

Links

Publication Tags

Entropy Metagenomics Genes Genome Databases Sampling Methodology Metagenome Painting Viruses Health Matlab Method Linux Availability Bioinformatics Microbiota Classifiers Microorganisms Datasets Profiler Dna Sequences Chemical Analysis Data Mining Need

Most Recent Papers

Application of MCAT Questions as a Testing Tool and Evaluation Metric for Knowledge Graph-based Reasoning Systems

Karamarie Fecho, James Balhoff, Chris Bizon, William Byrd, Sui Hang, David Koslicki, Stefano Rensi, Patrick Schmitt, Mathias Wawer, Mark Williams, Stanley Ahalt, Clinical and Translational Science

The statistics of k-mers from a sequence undergoing a simple mutation process without spurious matches

A Blanca Pimentel, R Harris, David Koslicki, P Medvedev, 2021, RECOMB

Tutorial: Assessing metagenomics software with the CAMI benchmarking toolkit

Fernando Meyer, Till Lesker, David Koslicki, Adrian Fritz, Alexey Gurevich, Aaron Darling, Alexander Sczyrba, Andreas Bremges, Alice McHardy, 2021, Nature Protocols

Metalign

Nathan Lapierre, Mohammed Alser, Eleazar Eskin, David Koslicki, Serghei Mangul, 2020, Genome Biology

Erratum

Caitlin Loeffler, Aaron Karlsberg, Lana S. Martin, Eleazar Eskin, David Koslicki, Serghei Mangul, 2020, BMC Biology

Improving the usability and comprehensiveness of microbial databases

Caitlin Loeffler, Aaron Karlsberg, Lana S. Martin, Eleazar Eskin, David Koslicki, Serghei Mangul, 2020, BMC Biology

Improving MinHash via the containment index with applications to metagenomic analysis

David Koslicki, Hooman Zabeti, 2019, Applied Mathematics and Computation on p. 206-215

MiCoP

Nathan Lapierre, Serghei Mangul, Mohammed Alser, Igor Mandric, Nicholas C. Wu, David Koslicki, Eleazar Eskin, 2019, BMC Genomics

Assessing taxonomic metagenome profilers with OPAL

Fernando Meyer, Andreas Bremges, Peter Belmann, Stefan Janssen, Alice C. McHardy, David Koslicki, 2019, Genome Biology on p. 51

Workshop on Microbiomics, Metagenomics, and Metabolomics

Soha Hassoun, Yasser El-Manzalawy, Georg Gerber, David Koslicki, Gail Rosen, 2019, on p. 618--618

Most-Cited Papers

Critical Assessment of Metagenome Interpretation - A benchmark of metagenomics software

Alexander Sczyrba, Peter Hofmann, Peter Belmann, David Koslicki, Stefan Janssen, Johannes Dröge, Ivan Gregor, Stephan Majda, Jessika Fiedler, Eik Dahms, Andreas Bremges, Adrian Fritz, Ruben Garrido-Oter, Tue Sparholt Jørgensen, Nicole Shapiro, Philip D. Blood, Alexey Gurevich, Yang Bai, Dmitrij Turaev, Matthew Z. Demaere, Rayan Chikhi, Niranjan Nagarajan, Christopher Quince, Fernando Meyer, Monika Balvočiutė, Lars Hestbjerg Hansen, Søren J. Sørensen, Burton K.H. Chia, Bertrand Denis, Jeff L. Froula, Zhong Wang, Robert Egan, Dongwan Don Kang, Jeffrey J. Cook, Charles Deltel, Michael Beckstette, Claire Lemaitre, Pierre Peterlongo, Guillaume Rizk, Dominique Lavenier, Yu Wei Wu, Steven W. Singer, Chirag Jain, Marc Strous, Heiner Klingenberg, Peter Meinicke, Michael D. Barton, Thomas Lingner, Hsin Hung Lin, Yu Chieh Liao, Genivaldo Gueiros Z. Silva, Daniel A. Cuevas, Robert A. Edwards, Surya Saha, Vitor C. Piro, Bernhard Y. Renard, Mihai Pop, Hans Peter Klenk, Markus Göker, Nikos C. Kyrpides, Tanja Woyke, Julia A. Vorholt, Paul Schulze-Lefert, Edward M. Rubin, Aaron E. Darling, Thomas Rattei, Alice C. McHardy, 2017, Nature Methods on p. 1063-1071

Topological entropy of DNA sequences

David Koslicki, 2011, Bioinformatics on p. 1061-1067

Sparse recovery by means of nonnegative least squares

Simon Foucart, David Koslicki, 2014, IEEE Signal Processing Letters on p. 498-502

On entropy-based data mining

Andreas Holzinger, Matthias Hörtenhuber, Christopher Mayer, Martin Bachler, Siegfried Wassertheurer, Armando J. Pinho, David Koslicki, 2014, Lecture Notes in Computer Science on p. 209-226

Quikr

David Koslicki, Simon Foucart, Gail Rosen, 2013, Bioinformatics on p. 2096-2102

WGSQuikr

David Koslicki, Simon Foucart, Gail Rosen, 2014, PLoS One on p. e91784

MetaPalette

David Koslicki, Daniel Falush, 2016, mSystems on p. e00020--16

Transcriptome analysis in whole blood reveals increased microbial diversity in schizophrenia

Loes M. Olde Loohuis, Serghei Mangul, Anil P.S. Ori, Guillaume Jospin, David Koslicki, Harry Taegyun Yang, Timothy Wu, Marco P. Boks, Catherine Lomen-Hoerth, Martina Wiedau-Pazos, Rita M. Cantor, Willem M. De Vos, René S. Kahn, Eleazar Eskin, Roel A. Ophoff, 2018, Translational Psychiatry

Striped UniFrac

Daniel McDonald, Yoshiki Vázquez-Baeza, David Koslicki, Jason McClelland, Nicolai Reeve, Zhenjiang Xu, Antonio Gonzalez, Rob Knight, 2018, Nature Methods on p. 847-848

Assessing taxonomic metagenome profilers with OPAL

Fernando Meyer, Andreas Bremges, Peter Belmann, Stefan Janssen, Alice C. McHardy, David Koslicki, 2019, Genome Biology on p. 51