Alexander Schönhuth
- Full Name
- Prof.dr. A. Schönhuth
- Function(s)
- Researcher - Unknown
- A.Schoenhuth@cwi.nl
- Telephone
- +31 20 592 4113
- Room
- M242
- Department(s)
- Life Sciences and Health
- Homepage
- http://homepages.cwi.nl/~as
Biography
I am a Genome Data Scientist who works at the interfaces of statistics, discrete mathematics and pattern recognition on the one hand and molecular biology and biomedicine on the other hand. I joined CWI in 2010, coming from UC Berkeley where I was a postdoctoral fellow in the Laboratory for Mathematical and Computational Biology in the Department of Mathematics, and I got tenure at CWI in 2014. Prior to UC Berkeley I also was a postdoctoral fellow in the Data Mining and Computational Laboratories of the School of Computing Science at Simon Fraser University in Vancouver. I received my PhD in 2006 from University of Cologne, Germany. On the theoretical end, I am particularly interested in data mining, sequence analysis and machine learning, with a special focus on Markovian and latent variable models. Biomedical questions I address relate to issues in computational genomics, in particular in the areas of pathogen, cancer and single cell biology. Genotyping and phasing variants from next- and third-generation sequencing data is a special focus. I am also concerned with computational pan-genomics, that is, to try to make sense out of -- soon -- millions of sequenced genomes, and with translating genome sequencing data into information that one can make use of in clinical practice, using machine learning methods.
Publications
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Lopez Rincon, A, Mendoza-Maldonado, L, Martinez-Archundia, M, Schönhuth, A, Kraneveld, A.D, Garssen, J, & Tonda, A. (2020). Machine learning-based ensemble recursive feature selection of circulating miRNAs for cancer tumor classification. Cancers, 12(7), 1–27. doi:10.3390/cancers12071785
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Köster, J, Dijkstra, L.J, Marschall, T, & Schönhuth, A. (2020). Varlociraptor: Enhancing sensitivity and controlling false discovery rate in somatic indel discovery. Genome Biology, 21(1). doi:10.1186/s13059-020-01993-6
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Lähnemann, D, Köster, J, Szczurek, E, McCarthy, D.J, Hicks, S.C, Robinson, M.D, … Schönhuth, A. (2020). Eleven grand challenges in single-cell data science. Genome Biology, 21. doi:10.1186/s13059-020-1926-6
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Baaijens, J.A, Stougie, L, & Schönhuth, A. (2020). Strain-aware assembly of genomes from mixed samples using flow variation graphs. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence. doi:10.1007/978-3-030-45257-5_14
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Baaijens, J.A, van der Roest, B, Köster, J, Stougie, L, & Schönhuth, A. (2019). Full-length de novo viral quasispecies assembly through variation graph construction. Bioinformatics, 35(24), 5086–5094. doi:10.1093/bioinformatics/btz443
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Nersisyan, L, Nikoghosyan, M, Arakelyan, A, Francioli, L.C, Menelaou, A. (Androniki), Pulit, S.L. (Sara L.), … The Genome of the Netherlands Consortium, . (2019). WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene. Nature Scientific Reports, 9(1). doi:10.1038/s41598-019-55109-7
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Lopez Rincon, A, Martinez-Archundia, M, Martinez-Ruiz, G.U, Schönhuth, A, & Tonda, A. (2019). Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection. BMC Bioinformatics, 20(1). doi:10.1186/s12859-019-3050-8
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Denti, L, Previtali, M, Bernardini, G, Schönhuth, A, & Bonizzoni, P. (2019). MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants. iScience, 18, 20–27. doi:10.1016/j.isci.2019.07.011
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Yin, B, Balvert, M, van der Spek, R.A.A, Dutilh, B.E, Bohte, S.M, Veldink, J, & Schönhuth, A. (2019). Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype. Bioinformatics, 35(14), i538–i547. doi:10.1093/bioinformatics/btz369
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Baaijens, J.A, & Schönhuth, A. (2019). Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics, 35(21), 4281–4289. doi:10.1093/bioinformatics/btz255
Current projects with external funding
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Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
Professional activities
- Committee member: Member Program Committee - ACM Conference on Bioinformatics,ﾠﾠComputational Biology and Biomedicine [ACM-BCB], 2012, 2017
- Committee member: Founding Member - Consortium, "Computational Pangenomics"
- Committee member: Member Consortium - "The Genome of the Netherlands"
Grants
- - Summer Semester Stipends, IPAM, UCLA, 2016, 2017 (2016)
- Vidi Innovational Research Grant NWO (2013)
- - Fall Semester Stipend, IPAM, University of California at Los (2011)
Awards
- Faculty of the 1000 paper award (voor "CLEVER: Clique-Enumerating Variant Finder") (2013)