David B. Blumenthal
Prof. Dr. David B. Blumenthal
Academic CV
- Since June 2021
W1 professor and head of the Biomedical Network Science Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany. - October 2019 – May 2021
Postdoctoral fellow at the Chair of Experimental Bioinformatics, Technical University of Munich, Freising, Germany. - March 2019 – September 2019
Postdoctoral fellow at the Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy. - November 2015 – February 2019
PhD candidate at the Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy. - February & November 2018
Visiting PhD student at the GREYC Research Lab in Digital Science, Caen, France. - October 2009 – June 2015
BSc & MSc Mathematics, Free University of Berlin & Technical University of Berlin, Berlin, Germany. - October 2007 – November 2013
BA & MA Philosophy, Free University of Berlin, Berlin, Germany. - September 2010 – June 2011
Erasmus exchange, University of Edinburgh, Edinburgh, United Kingdom. - June 2007
Abitur, Ottheinrich-Gymnasium Wiesloch, Wiesloch, Germany.
Publications
2022
Online in silico validation of disease and gene sets, clusterings or subnetworks with DIGEST
In: Briefings in Bioinformatics (2022)
ISSN: 1467-5463
DOI: 10.1093/bib/bbac247
URL: https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbac247/6618231?guestAccessKey=e1b9455f-ac28-4d46-af6d-c51b3b98cc8d
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Robust disease module mining via enumeration of diverse prize-collecting Steiner trees
In: Bioinformatics 38 (2022), p. 1600-1606
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/btab876
URL: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btab876/6497106?guestAccessKey=27c2a19b-11b5-4c3c-88d5-f1131e3809a9
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Enumerating dissimilar minimum cost perfect and error-correcting bipartite matchings for robust data matching
In: Information Sciences 596 (2022), p. 202-221
ISSN: 0020-0255
DOI: 10.1016/j.ins.2022.03.017
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Privacy-Preserving Artificial Intelligence Techniques in Biomedicine
In: Methods of Information in Medicine (2022)
ISSN: 0026-1270
DOI: 10.1055/s-0041-1740630
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2021
Metric Indexing for Graph Similarity Search
14th International Conference on Similarity Search and Applications (SISAP 2021) (Dortmund, 29. September 2021 - 1. October 2021)
In: Reyes N, Connor R, Kriege N, Kazempour D, Bartolini I, Schubert E, Chen J (ed.): Proceedings of the 14th International Conference on Similarity Search and Applications (SISAP 2021), Cham: 2021
DOI: 10.1007/978-3-030-89657-7_24
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Scalable generalized median graph estimation and its manifold use in bioinformatics, clustering, classification, and indexing
In: Information Systems 100 (2021), Article No.: 101766
ISSN: 0306-4379
DOI: 10.1016/j.is.2021.101766
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Upper Bounding Graph Edit Distance Based on Rings and Machine Learning
In: International Journal of Pattern Recognition and Artificial Intelligence (2021), Article No.: 2151008
ISSN: 0218-0014
DOI: 10.1142/S0218001421510083
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The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections
14th International Conference on Similarity Search and Applications (SISAP 2021) (Dortmund, 29. September 2021 - 1. October 2021)
In: Reyes N, Connor R, Kriege N, Kazempour D, Bartolini I, Schubert E, Chen J (ed.): Proceedings of the 14th International Conference on Similarity Search and Applications (SISAP 2021), Cham: 2021
DOI: 10.1007/978-3-030-89657-7_25
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Federated Principal Component Analysis for Genome-Wide Association Studies
21st IEEE International Conference on Data Mining (ICDM) (Auckland, New Zealand, 7. December 2021 - 10. December 2021)
In: 21st IEEE International Conference on Data Mining (ICDM) 2021
DOI: 10.1109/ICDM51629.2021.00127
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On the limits of active module identification
In: Briefings in Bioinformatics 22 (2021), Article No.: bbab066
ISSN: 1467-5463
DOI: 10.1093/bib/bbab066
URL: https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbab066/6189770?guestAccessKey=1be406a0-6b26-4e15-b32b-505c1ea2b279
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The AIMe registry for artificial intelligence in biomedical research
In: Nature Methods 18 (2021), p. 1128 - 1131
ISSN: 1548-7091
DOI: 10.1038/s41592-021-01241-0
URL: https://rdcu.be/cv5H7
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On the Privacy of Federated Pipelines
The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21) (Virtual Event, 11. July 2021 - 15. July 2021)
In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), New York, NY, USA: 2021
DOI: 10.1145/3404835.3462996
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Network medicine for disease module identification and drug repurposing with the NeDRex platform
In: Nature Communications 12 (2021), Article No.: 6848
ISSN: 2041-1723
DOI: 10.1038/s41467-021-27138-2
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Flimma: a federated and privacy-aware tool for differential gene expression analysis
In: Genome Biology 22 (2021), Article No.: 338
ISSN: 1474-760X
DOI: 10.1186/s13059-021-02553-2
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2020
A framework for modeling epistatic interaction
In: Bioinformatics 37 (2020), p. 1708 - 1716
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/btaa990
URL: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa990/6012351?guestAccessKey=4683fb7f-7afc-4b9c-b0d5-3d0085904eb4
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Comparing heuristics for graph edit distance computation
In: Vldb Journal 29 (2020), p. 419-458
ISSN: 1066-8888
DOI: 10.1007/s00778-019-00544-1
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On the exact computation of the graph edit distance
In: Pattern Recognition Letters 134 (2020), p. 46-57
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2018.05.002
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EpiGEN: An epistasis simulation pipeline
In: Bioinformatics 36 (2020), p. 4957-4959
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/btaa245
URL: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa245/5820008?guestAccessKey=2385c5f1-6587-4065-b2f2-1039765fa5b6
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Improved local search for graph edit distance
In: Pattern Recognition Letters 129 (2020), p. 19-25
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2019.10.028
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Fast linear sum assignment with error-correction and no cost constraints
In: Pattern Recognition Letters 134 (2020), p. 37-45
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2018.03.032
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Finding k-shortest paths with limited overlap
In: Vldb Journal (2020)
ISSN: 1066-8888
DOI: 10.1007/s00778-020-00604-x
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What is meaningful research and how should we measure it?
In: Scientometrics 125 (2020), p. 153-169
ISSN: 0138-9130
DOI: 10.1007/s11192-020-03649-5
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BiCoN: Network-constrained biclustering of patients and omics data
In: Bioinformatics 37 (2020), p. 2398 - 2404
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/btaa1076
URL: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa1076/6050718?guestAccessKey=e2e9cb2b-ac3d-44a6-abc7-2b92ae15d34c
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Individuating Possibly Repurposable Drugs and Drug Targets for COVID-19 Treatment through Hypothesis-Driven Systems Medicine Using CoVex
In: Assay and Drug Development Technologies 18 (2020), p. 348-355
ISSN: 1540-658X
DOI: 10.1089/adt.2020.1010
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Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing
In: Nature Communications 11 (2020), Article No.: 3518
ISSN: 2041-1723
DOI: 10.1038/s41467-020-17189-2
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2019
GEDLIB: A C++ Library for Graph Edit Distance Computation
12th IAPR-TC15 Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2019 (Tours, 19. June 2019 - 21. June 2019)
In: Donatello Conte, Jean-Yves Ramel, Pasquale Foggia (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2019
DOI: 10.1007/978-3-030-20081-7_2
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2018
Ring based approximation of graph edit distance
Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2018 and Statistical Techniques in Pattern Recognition, SPR 2018 (Beijing, 17. August 2018 - 19. August 2018)
In: Edwin R. Hancock, Tin Kam Ho, Battista Biggio, Richard C. Wilson, Antonio Robles-Kelly, Xiao Bai (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2018
DOI: 10.1007/978-3-319-97785-0_28
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Quasimetric Graph Edit Distance as a Compact Quadratic Assignment Problem
24th International Conference on Pattern Recognition, ICPR 2018 (Beijing, 20. August 2018 - 24. August 2018)
In: Proceedings - International Conference on Pattern Recognition 2018
DOI: 10.1109/ICPR.2018.8546055
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Improved lower bounds for graph edit distance
In: IEEE Transactions on Knowledge and Data Engineering 30 (2018), p. 503-516
ISSN: 1041-4347
DOI: 10.1109/TKDE.2017.2772243
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Finding k-dissimilar paths with minimum collective length
26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018 (Seattle, WA, 6. November 2018 - 9. November 2018)
In: Li Xiong, Roberto Tamassia, Kashani Farnoush Banaei, Ralf Hartmut Guting, Erik Hoel (ed.): GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems 2018
DOI: 10.1145/3274895.3274903
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2017
Correcting and speeding-up bounds for non-uniform graph edit distance
33rd IEEE International Conference on Data Engineering, ICDE 2017 (San Diego, CA, 19. April 2017 - 22. April 2017)
In: Proceedings - International Conference on Data Engineering 2017
DOI: 10.1109/ICDE.2017.57
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Exact computation of graph edit distance for uniform and non-uniform metric edit costs
11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2017 (Anacapri, ITA, 16. May 2017 - 18. May 2017)
In: Pasquale Foggia, Mario Vento, Cheng-Lin Liu (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2017
DOI: 10.1007/978-3-319-58961-9_19
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Activities
Experts for reviewing scientific journals
- Computational and Structural Biotechnology Journal
since 22. June 2022 - Bioinformatics (Oxford, England)
since 5. November 2021 - Frontiers in Medicine
since 3. September 2021 - Assay and Drug Development Technologies
since 1. January 2021 - Heliyon
since 1. January 2021 - Nature Communications
since 1. January 2021 - BioData Mining
since 1. January 2020 - Pattern Analysis and Applications
since 1. January 2020 - Information Sciences
since 1. January 2020 - European Journal of Operational Research
since 1. January 2020 - Information Systems Frontiers
since 1. January 2019 - Pattern Recognition Letters
since 1. January 2019
Experts for funding organisations
- Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen
since 1. October 2021 - TUM Global Postdoc Fellowship
since 1. January 2021 - The Research Council of Norway
since 1. January 2021
Other activities (FAU-external)
Awards
- 2021: Best PhD Student Award (Faculty of Computer Science, Free University of Bozen-Bolzano)
- 2021: Best Talk Award (29th Conference on Intelligent Systems for Molecular Biology, Network Biology Community of Special Interest)
- 2017: Best Paper Award (11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition)
- 2015: PhD Grant (Faculty of Computer Science, Free University of Bozen-Bolzano)
- 2015: MSc Award (Institute of Mathematics, Technical University of Berlin)
- 2007: Student Scholarship (German Academic Scholarship Foundation)
Funding
2022
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Unsupervised Network Medicine for Longitudinal Omics Data
(FAU Funds)
Term: since 15. January 2022Over the last years, large amounts of molecular profiling data (also called “omics data”) have become available. This has raised hopes to identify so-called disease modules, i.e., sets of functionally related molecules constituting candidate disease mechanisms. However, omics data tend to be overdetermined and noisy; and modules identified via purely statistical means are hence often unstable and functionally uninformative. Hence, network-based disease module mining methods (DMMMs) project omics data onto biological networks such as protein-protein interaction (PPI) networks, gene regulatory networks (GRNs), or microbial interaction networks (MINs). Subsequently, network algorithms are used to identify disease modules consisting of small subnetworks. This dramatically decreases the size of the search space and prioritizes disease modules consisting of functionally related molecules, positively affecting both stability and functional relevance of the discovered modules.
However, to the best of our knowledge, all existing DMMMs are subject to at least one of the following two limitations: Firstly, existing DMMMs are typically supervised, in the sense that they try to find subnetworks explaining differences in the omics data between predefined case and control patients or pre-defined disease subtypes. This is potentially problematic, because it implies that existing DMMMs are biased by our current disease ontologies, which are mostly symptom- or organ-based and therefore often too coarse-grained. For instance, around 95 % of all patients with hypertension are diagnosed with so-called “essential hypertension” (code BA00.Z in the ICD-11 disease ontology), meaning that the cause of the hypertension is unknown. In fact, there are probably several disjoint molecular mechanisms causing “essential hypertension”, and the same holds true for many other complex diseases such as Alzheimer’s disease, multiple sclerosis, and Crohn’s disease. Supervised DMMMs which take existing disease definitions for granted hence risk overlooking the molecular mechanisms causing mechanistically distinct subtypes.
Secondly, most existing DMMMs are designed for static omics data and do not support longitudinal data where the patients’ molecular profiles are observed over time. Existing analysis frameworks for longitudinal omics data largely use purely statistical means. Consequently, network medicine approaches for time series data are needed.
To the best of our knowledge, there are only three DMMMs which, in part, overcome these limitations: BiCoN and GrandForest allow unsupervised disease module mining but do not support longitudinal omics data. TiCoNE supports longitudinal data but requires predefined case vs. control or subtype annotations as input. There is hence an unmet need for unsupervised DMMMs for longitudinal omics data. Developing such methods is the main objective of the proposed project.