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

W205C Westgate

dmk333@psu.edu

814-865-1611

Research Areas:

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

 
 

 

Education

  • BS, Mathematics, Washington State University, 2006
  • Ph D, Mathematics, Pennsylvania State University, 2012

Publications

Books

  • David Koslicki, 2018, Introduction to Mathematical Software, Zenodo, pp. 207

Journal Articles

  • David Koslicki, Stephen White, Chunyu Ma and Alexei Novikov, 2024, "YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample", Oxford Journal of Bioinformatics, (btae047)
  • Chunyu Ma, Zhihan Zhou, Han Liu and David Koslicki, 2023, "KGML-xDTD: A Knowledge Graph-based Machine Learning Framework for Drug Treatment Prediction and Mechanism Description", GigaScience
  • Mahmudur Rahman Hera, N. Tessa Pierce-Ward and David Koslicki, 2023, "Deriving Confidence Intervals for Mutation Rates Across a Wide Range of Evolutionary Distances Using FracMinHash", Genome Research, (gr.277651.123)
  • Chunyu Ma, Shaopeng Liu and David Koslicki, 2023, "ARAX: a modular graph-based reasoning tool for biomedical questions", Bioinformatics, 39, (3)
  • Melanie Mumau, Abiola Irvine, Chunyu Ma, Sheila K Pierson, Brent Shaw, Michael V Gonzalez, Daniel Korn, Tracey Sikora, Grant Mitchell, David Koslicki and others, 2023, "A translational approach to identifying and targeting TNF signaling in idiopathic multicentric Castleman disease", Blood, 142, pp. 3921
  • Karamarie Fecho, Chris Bizon, Tursynay Issabekova, Sierra Moxon, Anne E Thessen, Shervin Abdollahi, Sergio E Baranzini, Basazin Belhu, William E Byrd, Lawrence Chung, David Koslicki and others, 2023, "An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges", Journal of Clinical and Translational Science, 7, (1), pp. e214
  • E. C. Wood, Amy K. Glenn, Finn Womack, Liliana Acevedo, Timothy S Yoon, Chunyu Ma, Veronica Flores, Meghamala Sinha, Yodsawalai Chodpathumwan, Arash Termehchy, Jared C. Roach, Luis Mendoza, Andrew S. Hoffman, Eric W. Deutsch, David Koslicki and Stephen A. Ramsey, 2022, "RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine", BMC Bioinformatics, 23, (400)
  • Shaopeng Liu and David Koslicki, 2022, "CMash: fast, multi-resolution estimation of k-mer-based Jaccard and containment indices", Bioinformatics, 38
  • Mahdi Belbasi, Antonio Blanca, Robert S Harris, David Koslicki and Paul Medvedev, 2022, "The minimizer Jaccard estimator is biased and inconsistent", Bioinformatics, 38
  • Karamarie Fecho, David Koslicki and The Biomedical Data Translator Consortium, 2022, "Progress toward a universal biomedical data translator", Clinical and Translational Science, 15, (8)
  • Deepak R Unni, David Koslicki and The Biomedical Data Translator Consortium, 2022, "Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science", Clinical and Translational Science, 15, (8)
  • Varuni Sarwal, Jaqueline Brito, Serghei Mangul and David Koslicki, 2022, "TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles", HiCOMB 2022
  • Fernando Meyer, Adrian Fritz, Z.L. Deng and David Koslicki, 2022, "Critical Assessment of Metagenome Interpretation - the second round of challenges", Nature Methods, 19, pp. 429-440
  • Antonio Blanca Pimentel, Robert Scott Harris, David Koslicki and Paul Medvedev, 2022, "The statistics of k-mers from a sequence undergoing a simple mutation process without spurious matches", Journal of Computational Biology, 29, (2), pp. 155-168
  • David Koslicki, Dana Gibbon and Mark Novak, 2022, "PressPurt: network sensitivity to press perturbations under interaction uncertainty", F1000Research
  • Mohammed Alser, Jeremy Rotman, Dhrithi Deshpande, Kodi Taraszka, Huwenbo Shi, Pelin Baykal, Harry Yang, Victor Xue, Sergey Knyazev, Benjamin Singer, Brunilda Balliu, David Koslicki, Pavel Skums, Alex Zelikovsky, Can Alkan, Onur Mutlu and Serghei Mangul, 2021, "Technology dictates algorithms: recent developments in read alignment", Genome Biology, 22, (249)
  • Karamarie Fecho, James Balhoff, Chris Bizon, William Byrd, Sui Hang, David Koslicki, Stefano Rensi, Patrick Schmitt, Mathias Wawer, Mark Williams and Stanley Ahalt, 2021, "Application of MCAT Questions as a Testing Tool and Evaluation Metric for Knowledge Graph-based Reasoning Systems", Clinical and Translational Science, 14, (5), pp. 5
  • Fernando Meyer, Till-Robin Lesker, David Koslicki, Adrian Fritz, Alexey Gurevich, Aaron Darling, Alexander Sczyrba, Bremges and Alic C. McHardy, 2021, "Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit", Nature Protocols, 16, (4), pp. 1785-1801
  • Nathan LaPierre, Mahammed Alser, Eleazar Eskin, David Koslicki and Serghei Mangul, 2020, "Metalign: efficient alignment-based metagenomic profiling via containment min hash", Genome Biology, 21, (242), pp. 15
  • Caitlin Loeffler, Aaron Karlsberg, Lana S Martin, Eleazar Eskin, David Koslicki and Serghei Mangul, 2020, "Improving the usability and comprehensiveness of microbial databases", BMC Biology, 18, (37)
  • David Koslicki and The Biomedical Data Translator Consoritum, 2019, "Clinical Data: Sources and Types, Regulatory Constraints, Applications", Clinical and Translational Science, 12, pp. 329-333
  • 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 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
  • Shuchang Tian, Min Soo Kim, Jingcheng Zhao, Kerim Heber, Fuhua Hao, David Koslicki, Andrew David Patterson and Jordan Bisanz, , "A Synthetic Microbiota Designed Through Meta-Analysis Provides Insight to Community Function in Clostridioides Difficile Resistance", Cell Press

Conference Proceedings

  • Wei Wei, Andrew Millward and David Koslicki, 2023, "L2-UniFrac: taking averages with respect to a phylogenetically informed metric", ISMB 2023
  • Mahmudur Rahman Hera, N. Tessa Pierce-Ward and David Koslicki, 2023, "Deriving Confidence Intervals for Mutation Rates Across a Wide Range of Evolutionary Distances Using FracMinHash", RECOMB 2023, 13976
  • Wei Wei and David Koslicki, 2022, "Using the UniFrac metric on Whole Genome Shotgun data", WABI 2022
  • Shaopeng Liu and David Koslicki, 2022, "CMash: fast, multi-resolution estimation of k-mer-based Jaccard and containment indices", ISMB 2022, 38
  • Mahdi Belbasi, Antonio Blanca Pimentel, Robert Scott Harris, David Koslicki and Paul Medvedev, 2022, "The minimizer Jaccard estimator is biased and inconsistent", ISMB 2022
  • Antonio Blanca Pimentel, Robert Scott Harris, David Koslicki and Paul Medvedev, 2021, "The statistics of k-mers from a sequence undergoing a simple mutation process without spurious matches", RECOMB 2021, 29
  • Simon Foucart and David Koslicki, 2020, "Finer Metagenomic Reconstruction via Biodiversity Optimization", Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 33, pp. 14
  • 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

  • Finn Womack, Jason McClelland and David Koslicki, 2019, "Leveraging Distributed Biomedical Knowledge Sources to Discover Novel Uses for Known Drugs", bioRxiv preprint
  • David Koslicki, 2012, "SUBSTITUTION MARKOV CHAINS WITH APPLICATIONS TO MOLECULAR EVOLUTION"

Research Projects

  • June 2020 - May 2022, "QuBBD: Fast, Efficient Mathematical Approach to the Analysis of the Human Microbiome through Biodiversity Optimization," (Sponsor: National Science Foundation).

Honors and Awards

  • College of Science Impact Award, Oregon State University, October 2018

Service

Service to Penn State:

  • Committee Work, Committee Member, CSE Strategic Committee, CSE Strategic Committee, 2023
  • Committee Work, Committee Member, Undergraduate Committee, CS+X/Minor, Undergraduate Committee, CS+X/Minor, 2023
  • Committee Work, Committee Member, Online Learning Committee, Online Learning Committee, 2023
  • Committee Work, Committee Member, Bioinformatics and Genomics qualification exam committee, The Huck Institutes of the Life Sciences, Qualification exam committee, April 2020
  • Academic Leadership and Support Work, Committee Member, Executive Committee Member, The Huck Institutes of the Life Sciences Microbiome center, Executive Committee of the Penn State Microbiome Center, July 2020
  • Committee Work, Committee Member, Safety Committee, May 2020
  • Committee Work, Member, Committee Member, Graduate Committee, August 2019 - August 2021

Service to External Organizations:

  • Organizing Conferences and Service on Conference Committees, Moderator, Microbiome community of special interest moderator, ISMB, July 2023 - July 2023
  • Organizing Conferences and Service on Conference Committees, Committee Member, Proceedings Program Committee member, IEEE BIBM, June 2022 - July 2022
  • Organizing Conferences and Service on Conference Committees, Committee Member, Proceedings Program Committee member, ISMB, December 2022 - January 2023
  • Organizing Conferences and Service on Conference Committees, Committee Member, Proceedings Program Committee member, ISMB, December 2021 - January 2022
  • Organizing Conferences and Service on Conference Committees, Committee Member, Program committee member for the ACM conference on bioinformatics, computational biology, and health informatics (BCB), ACM BCB, February 2019 - February 2019
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Computational Genomics Summer Institute (CGSI) Co-organizer, Computational Genomics Summer Institute (CGSI), December 2018 - August 2019
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Computational Genomics Summer Institute (CGSI) Co-organizer, Computational Genomics Summer Institute (CGSI), December 2017 - August 2018
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Computational Genomics Summer Institute (CGSI) Co-organizer, December 2016 - July 2017
  • Service to Public and Private Organizations, Board Member, Critical Assessment of Metagenomic Interpretation (CAMI) advisory board member, CAMI, January 2015
 


 

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 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.

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