Publications #
Areas of work #
[ML] |
AI/ML and drug development (Novartis) |
[GEN] |
Genomics / variant benchmarking (Illumina and later collaborations) |
[SB] |
Systems biology (postdoc, University of Warwick) |
[HPC] |
Parallel algorithms (PhD and MSc, University of Warwick) |
See also: https://scholar.google.com/citations?hl=en&user=MvdVQs8AAAAJ&view_op=list_works&sortby=pubdate
2026 #
[ML] D. Zhang, T. Coroller, P. Krusche, C. Gao. synadam: Generate Synthetic ADaM Datasets. R package, CRAN, 2026. doi:10.32614/CRAN.package.synadam, github.com/Novartis/synadam.
(Novartis: package developed by David Zhang for generating synthetic ADaM clinical-trial datasets while preserving useful dataset structure - e.g. to support AI-based code development without having to expose data to agents; I helped with design & requirements)
[GEN] J. M. Holt, C. T. Saunders, E. Dolzhenko, P. Krusche, N. D. Olson, J. M. Zook, M. A. Eberle, Z. Kronenberg. Aardvark: sifting through differences in a mound of variants. Genome Biology, 2026. doi:10.1186/s13059-026-04165-0.
Preprint: bioRxiv, 2025. Supporting benchmark material: Zenodo, Code: github.com/PacificBiosciences/aardvark.
(follow-on collaboration building on my genomics work at Illumina: contributed variant-benchmarking expertise, examples and manuscript review)
2025 #
[ML] S. Bamford, W. Lemaire, M. Hodosi, S. Ahrweiler, T. Huang, C. McShea, C. Schaffer, P. Krusche, R. Goel. Reimagining Clinical Data for a Digital-First Future. Applied Clinical Trials, 19 Sep. 2025. https://www.appliedclinicaltrialsonline.com/view/clinical-data-digital-first-future.
(Novartis: contributed to this cross-industry perspective on digital-first clinical data and how better-connected data can support automation, AI and decision-making)
[ML] M. Azzarito, P. Krusche. How to Generate High-Dimensional Synthetic Medical Images with Little Data. Poster at ICAART 2025. ICAART abstract, github.com/Novartis/synthetic-mris.
(Novartis: follow-up to the synthetic medical data work; explored generation of high-dimensional synthetic brain MRI data from limited training data, with the HAGAN/WGP-HAGAN training and evaluation workflow subsequently released as open source)
2024 #
[ML] M. Monod, P. Krusche, Q. Cao, B. Sahiner, N. Petrick, D. Ohlssen, T. Coroller. TorchSurv: A Lightweight Package for Deep Survival Analysis. Journal of Open Source Software 9(104), 7341, 2024. doi:10.21105/joss.07341.
(Novartis: contributed to Python package development & publication; see also GitHub, Zenodo, and its 2025 inclusion in the FDA CDRH Regulatory Science Tools Catalog)
[ML] Y. Yang, P. Krusche, K. Pantoja, C. Shi, E. Ludmir, K. Roberts, G. Zhu. Using Large Language Models to Generate Clinical Trial Tables and Figures. arXiv:2409.12046, 18 Sep. 2024. doi:10.48550/arXiv.2409.12046.
(Novartis: this came from an internship project by Yumeng Yang, jointly supervised with Gen Zhu)
[ML] T. Coroller, B. Sahiner, A. Amatya, A. Gossmann, et al. (incl. P. Krusche). Methodology for Good Machine Learning with Multi-Omics Data. Clinical Pharmacology & Therapeutics 115(4), 745-757, 2024. doi:10.1002/cpt.3105. Preprint from 2023: doi:10.1101/2023.08.30.23294367.
(Novartis: contributed to review of the good practices from an engineering perspective)
2022 #
[ML] J. D. Ziegler, S. Subramaniam, M. Azzarito, O. Doyle, P. Krusche, T. Coroller. Multi-Modal Conditional GAN: Data Synthesis in the Medical Domain. NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research. 2022. on OpenReview
(Novartis: work on synthetic clinical data and image generation; see also the 2025 follow-up on synthetic brain MRI generation above; supervision of Novartis AI4Life Residency project)
2021 #
[ML] A.-M. Mallon et al. Advancing Data Science in Drug Development through an Innovative Computational Framework for Data Sharing and Statistical Analysis. BMC Med Res Methodol 21, 250 (2021). doi:10.1186/s12874-021-01409-4.
(Novartis: helped with technical input and review of engineering practices)
2019 #
[GEN] S. Chen, P. Krusche, E. Dolzhenko, R.M. Sherman, R. Petrovski, F. Schlesinger, M. Kirsche, D.R. Bentley, M.C. Schatz, F. J. Sedlazeck, M.A. Eberle. Paragraph: A graph-based structural variant genotyper for short-read sequence data. Genome Biology 20:291 (2019), doi:10.1186/s13059-019-1909-7; pre-print on bioRxiv doi:10.1101/635011, github.com/illumina/paragraph, 2019.
(Illumina: method development and implementation behind paragraph)
[GEN] E. Dolzhenko, V. Deshpande, F. Schlesinger, P. Krusche, R. Petrovski, S. Chen, D. Emig-Agius, A. Gross, G. Narzisi, B. Bowman, K. Scheffler, J. J.F.A. van Vugt, C. French, A. Sanchis-Juan, K. Ibáñez, A. Tucci, B. Lajoie, J. H. Veldink, L. Raymond, R. J. Taft, D. R. Bentley, M. A. Eberle. ExpansionHunter: a sequence-graph-based tool to analyze variation in short tandem repeat regions. Bioinformatics, btz431, doi:10.1093/bioinformatics/btz431, 2019. github.com/illumina/expansionhunter
(Illumina: contributed to manuscript review)
2018/2019 #
[GEN] P. Krusche, L. Trigg, P. C. Boutros, C. E. Mason, F. M. De La Vega, B. L. Moore, M. Gonzalez-Porta, M. A. Eberle, Z. Tezak, S. Lababidi, R. Truty, G. Asimenos, B. Funke, M. Fleharty, B.A. Chapman, M. Salit, J. M. Zook, The Global Alliance for Genomics and Health Benchmarking Team. Best Practices for Benchmarking Germline Small Variant Calls in Human Genomes, Nature Biotechnology 37, 555–560 (2019), pre-print on bioRxiv doi:10.1101/270157, github.com/ga4gh/benchmarking-tools / github.com/illumina/hap.py.
(Illumina: Part of the GA4GH benchmarking effort, developed the benchmarking method that was also used later in the precisionFDA truth challenge V2 and collaborated on the manuscript)
2017 #
[GEN] P. Krusche, E. Dolzhenko, N. Johnson, M.A. Bekritsky, A. Gross, B.R. Lajoie, V. Rajan, Z. Kingsbury, S.J. Humphray, S.S. Ajay, R.J. Taft, D.R. Bentley, M.A. Eberle. A graph method for population genotyping of structural variants. Poster at ASHG 2017, github.com/illumina/paragraph.
(Illumina: method development and implementation behind paragraph)
[GEN] M.A. Bekritsky, P. Krusche, N. Johnson, E. Dolzhenko, A. Gross, B.R. Lajoie, V. Rajan, N. Gonzaludo, Z. Kingsbury, S.J. Humphray, S.S. Ajay, R.J. Taft, D.R. Bentley, M.A. Eberle. Polaris: A collection of 220 publicly available whole genomes for sharing validated structural variants. Poster at ASHG 2017, github.com/illumina/polaris.
(Illumina: teamwork)
[GEN] S. Kim, K. Scheffler, A. L. Halpern, M. A. Bekritsky, E. Noh, M. Källberg, X. Chen, D. Beyter, P. Krusche, C. T. Saunders. Strelka2: fast and accurate calling of germline and somatic variants. Nature Methods 15, 591–594 (2018). Paper: doi:10.1038/s41592-018-0051-x; preprint: doi:10.1101/192872, Poster at WABI 2017, github.com/illumina/strelka.
(Illumina: contributed to development & accuracy assessment of the Strelka variant caller)
[GEN] M.A. Eberle, E. Fritzilas, P. Krusche, M. Källberg, B. Moore, M.A. Bekritsky, Z. Iqbal, H. Chuang, S.J. Humphray, A. Halpern, S. Kruglyak, E.H. Margulies, G. McVean and D.R. Bentley. A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree. Genome Research, 27:157-164. doi:10.1101/gr.210500.116, 2017.
(Illumina: method and data pipeline development)
2015 #
[SB] N. J. Davies, P. Krusche, E. Tauber and S. Ott. Analysis of 5’ gene regions reveals extraordinary conservation of novel non-coding sequences in a wide range of animals. BMC Evolutionary Biology, 15, 227 doi:10.1186/s12862-015-0499-6, 2015.
(postdoc at Warwick: some of the analysis in this paper is based on the APPLES promoter sequence analysis software package)
2014 #
[SB] C. Feillet, P. Krusche, F. Tamanini, R. C. Janssens, M. J. Downey, P. Martin, M. Teboul, S. Saito, F. A. Levi, T. Bretschneider, G. T. J. van der Horst, F. Delaunay, D. A. Rand, Phase locking and multiple oscillating attractors for the coupled mammalian clock and cell cycle. PNAS 111 (27) 9828-9833, 2014. doi:10.1073/pnas.1320474111
(postdoc at Warwick: data analysis and visualisation, mathematical modelling)
2013 #
[SB] R. Laranjeiro, T. K. Tamai, E. Peyric, P. Krusche, S. Ott, D. Whitmore. Cyclin-dependent kinase inhibitor p20 controls circadian cell-cycle timing. PNAS 110 (17) 6835-6840; doi:10.1073/pnas.1217912110, 2013.
(postdoc at Warwick: bioinformatic sequence analysis and phylogenetic tree construction)
2012 #
[SB] L. Baxter, A. Jironkin, R. Hickman, J. Moore, C. Barrington, P. Krusche, N. P. Dyer, V. Buchanan-Wollaston, A. Tiskin, J. Beynon, K. Denby, S. Ott. Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants. The Plant Cell, 24(10), pp.3949–3965. Available at: doi:10.1105/tpc.112.103010, 2012.
(postdoc at Warwick: code and documentation for the APPLES promoter sequence analysis software package)
2010 #
[SB] E. Picot, P. Krusche, A. Tiskin, I. Carré, S. Ott. Evolutionary analysis of regulatory sequences (EARS) in plants. The Plant journal for cell and molecular biology, 64(1), pp.165–176; doi:10.1111/j.1365-313X.2010.04314.x, 2010.
(postdoc at Warwick: fast alignment-plot code in C++/Assembler for the EARS Web Tool; code available at github.com/pkrusche/seaweeds)
[HPC] P. Krusche, A. Tiskin. New algorithms for efficient parallel string comparison. SPAA '10: Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures, pp. 209–216; doi:10.1145/1810479.1810521, 2010.
(PhD at Warwick: algorithm design, implementation and experiments)
[HPC] P. Krusche, A. Tiskin. Computing alignment plots efficiently. Parallel Computing: From Multicores and GPU's to Petascale, pp. 158-165, doi:10.3233/978-1-60750-530-3-158, 2010.
(PhD at Warwick: algorithm design, implementation and experiments)
Slides for the talk at LSD/LAW 2010 at King's College London.
[HPC] P. Krusche, A. Tiskin. Parallel longest increasing subsequences in scalable time and memory. Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science vol. 6067 pp. 176-185; doi:10.1007/978-3-642-14390-8_19, 2010.
(PhD at Warwick: algorithm design, implementation and experiments)
Slides for the talk at the T&MC Workshop 2009.
2009 #
[HPC] P. Krusche, A. Tiskin. String comparison by transposition networks. Texts in Algorithmics, vol. 11 of London Algorithmics 2008: Theory and Practice, collegepublications.co.uk and arxiv.org/abs/0903.3579, 2009.
(PhD at Warwick: algorithm design and write-up)
Slides for the talk at WPCCS'08.
2007 #
[HPC] P. Krusche, A. Tiskin. Efficient parallel string comparison. Proceedings of ParCo 2007, vol. 38 of NIC Series, pp. 193-200, John von Neumann Institute for Computing, ISBN: 978-3-9810843-4-4; Full proceedings volume: https://juser.fz-juelich.de/record/60553/files/NIC225296.pdf, 2007.
(PhD at Warwick: algorithm design, implementation and experiments)
Slides for the talk at ParCo 2007 in Jülich, Germany, 4th of September 2007
Slides for the talk at the AFM seminar at Warwick, 23rd of April 2007
2006 #
[HPC] P. Krusche, A. Tiskin. Efficient Longest Common Subsequence Computation Using Bulk-Synchronous Parallelism. Proceedings of ICCSA 2006, Lecture Notes in Computer Science vol. 3984, pp. 165-174; doi:10.1007/11751649_18, 2006.
(PhD at Warwick: algorithm design, implementation and experiments)
Slides for the talk given at the PDC'06 workshop at ICCSA 2006 in Glasgow
2005 #
[HPC] P. Krusche. Experimental Evaluation of BSP Programming Libraries. Parallel Processing Letters vol. 18:1 pp. 7-21 doi:10.1142/S0129626408003193
(MSc work at Warwick: benchmarking study of BSP libraries - done in 2005, final publication in PPL 2008)