Networks allow representing interactions between entities and are highly informative. They enable the integrative analysis of different data views. We are interested in combining network-based data analysis approaches and mathematical modeling of dynamic processes with machine learning to bring in prior information. Applications stem mainly from a biomedical background, such as drug response prediction, and we focus on integrating different kinds of data with biomolecular, "multi-omics" data.

Selected projects:

• Multi-omics network-based prediction of differential drug response (DrDimont)
• Drug response prediction using graph-neural networks with uncertainty
• Proteogenomic abundance imputation
• Informing machine learning using simulations from dynamical models

Pascal Iversen

Pauline Hiort

Maximilian Kleissl

Tobias Pietz

Jonathan Wilke

Julian Zabbarov

Alumni:

Tim Garrels (MA thesis, student assistant)

Dr. Sukrit Gupta (Postdoc)

Theresa Hradilak (student assistant)

Clemens Woest (MA thesis)

Simon Witzke (MA thesis)

Axel Stebner (MA thesis)

Lilli Schuckert (BA thesis, student assistant)

• Source detection in complex networks [Project Seminar, Master]
• Mathematik III (Stochastik + Statistik) [Bachelor ITSE]
• Challenge accepted - Framework for simulation-based evaluation of machine learning models [Masterproject DE, ITSE, DH]
• Effekte kleiner Stichprobengrößen auf verschiedene Datenanalysetechniken [Projektseminar Bachelor ITSE]
• Dissecting the complex - efficient computing in large networks [Project Seminar, Master]
• Implementing Information Flow in Complex Networks [Project Seminar, Master]
• Mathematik 3 (Stochastik + Statistik) [Bachelor ITSE]

• Witzke S, Danz N, Baum K, Renard BY. Mobility data improve forecasting of COVID-19 incidence trends using Graph Neural Networks epiDAMIK 6.0: The 6th International workshop on Epidemiology meets Data Mining and Knowledge Discovery at KDD 2023 [link]
• Kleissl M, Drews L, Heyder BB, Zabbrov J, Iversen P, Witzke S, Renard BY, Baum K*: SimbaML: Connecting mechanistic models and machine learning with augmented data. ICLR 2023 Tiny Paper *corresponding author [link]
• Garrels T, Khodabakhsh A, Renard BY, Baum K*: LazyFox: Fast and parallelized overlapping community detection in large graphs, PeerJ Computer Science 9:e1291. *corresponding author [link]
• Hiort P, Hugo J, Zeinert J, Müller N, Kashyap S, Rajapakse JC, Azuaje F, Renard BY, Baum K*: DrDimont: explainable drug response prediction from differential analysis of multi-omics networks. Bioinformatics 2022; Sep 16;38(Supplement_2):ii113-ii119. *corresponding author [link]
• Langenhan J, Jaeger C, Baum K, Simon M, Lisec J. A Flexible Tool to Correct Superimposed Mass Isotopologue Distributions in GC-APCI-MS Flux Experiments. Metabolites 2022;12(5). doi: 10.3390/metabo12050408 [link]
• Lahmann I, Zhang Y, Baum K, Wolf J, Birchmeier C:An oscillatory network controlling self-renewal of skeletal muscle stem cells. Exp Cell Res 2021;409(2):112933. [link]
• Zhang Y, Lahmann I, Baum K, Shimojo H, Mourikis P, Wolf J, Kageyama R, Birchmeier C: Oscillations of Delta-like1 regulate the balance between differentiation and maintenance of muscle stem cells. Nature Communications 2021;12(1):1318. [link]
• Lisec J, Kobelt D, Walther W, Mokrizkij M, Grötzinger C, Jaeger C, Baum K, Simon M, Wolf J, Beindorff N, Brenner W, Stein U: Systematic Identification of MACC1-Driven Metabolic Networks in Colorectal Cancer. Cancers 2021, 13(5). [link]
• Arlt B, Zasada C, Baum K, Wuenschel J, Mastrobuoni G, Lodrini M, Astrahantseff K, Winkler A, Schulte JH, Finkler S, Forbes M, Hundsdoerfer P, et al.: Inhibiting phosphoglycerate dehydrogenase counteracts chemotherapeutic efficacy against MYCN‐amplified neuroblastoma. International J Cancer 2021; Mar 1;148(5):1219-1232. Epub 2020 Dec 17. [link]
• Tjaden B*, Baum K*, Marquardt V, Simon M, Trajkovic-Arsic M, Kouril T, Siebers B, Lisec J, Siveke JT, Schulte J, Benary U, Remke M, Wolf J, Schramm A: N-Myc-induced metabolic rewiring creates novel therapeutic vulnerabilities in neuroblastoma. Scientific Reports 2020; 10(7157). *co-first authors [link]
• Baum K*, Schuchhardt J, Wolf J, Busse D: Of gene expression and cell division time: A mathematical framework for advanced differential gene expression and data analysis. Cell Systems 2019; 9(6):569-79.e7. *corresponding author [link]
• Baum K, Rajapakse JC, Azuaje F: Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models [version 2; peer review: 1 approved, 2 approved with reservations]. F1000Res 2019; 8(465). [link]
• Dittmar G, Perez Hernandez D, Kowenz-Leutz E, Kirchner M, Kahlert G, Wesolowski R, Baum K, Knoblich M, Hofstätter M, Muller A, Wolf J, Reimer U, Leutz A: PRISMA: Protein Interaction Screen on Peptide Matrix reveals interaction footprints and modifications-dependent interactome of intrinsically disordered C/EBPβ. iScience 2019; 13: 351–370. [link]
• Schroeder MP, Bastian L, Eckert C, Gökbuget N, James AR, Ortiz Tanchez J, Schlee C, Isaakidis K, Häupl B, Baum K, Migueles Lozano OA, et al.: Integrated analysis of relapsed B-cell precursor Acute Lymphoblastic Leukemia identifies subtype-specific cytokine and metabolic signatures. Scientific Reports 2019; 9(1):4188. [link]
• Wagner AS, Politi AZ, Ast A, Bravo-Rodriguez K, Baum K, Buntru A, Strempel NU, Brusendorf L, Hänig C, Boeddrich A, Plassmann S, Klockmeier K, et al.: Self-assembly of Mutant Huntingtin Exon-1 Fragments into Large Complex Fibrillar Structures Involves Nucleated Branching. J Molecular Biology 2018; 430(12):1725-1744. On the title page. [link]
• Baum K, Politi AZ, Kofahl B, Steuer R, Wolf J: Feedback, mass conservation and reaction kinetics affect the robustness of cellular oscillations. PLOS Computational Biology 2016 Dec 27; 12(12):e1005298. [link]
• Yilmaz ZB, Kofahl B, Beaudette P, Baum K, Ipenberg I, Weih F, Wolf J, Dittmar G, Scheidereit C: Quantitative dissection and modeling of the NF-κB p100-p105 module reveals interdependent precursor proteolysis. Cell Reports 2014; 9(5):1756-69. [link]
• Schmidt V, Baum K, Lao A, Rateitschak K, Schmitz Y, Teichmann A, Wiesner B, Petersen CM, Nykjaer A, Wolf J, Wolkenhauer O, Willnow TE: Quantitative modelling of amyloidogenic processing and its influence by SORLA in Alzheimer’s disease. EMBO J 2012; 31(1):187-200. [link]

• Baum K, Wolf J: LoopDetect: Comprehensive Feedback Loop Detection in Ordinary Differential Equation Models. bioRxiv, 17 Nov 2020. [link]
• Baum K*, Rajapakse JC, Azuaje F: Crop Circles of Cancer. In: Matthäus F et al. (eds.), The Art of Theoretical Biology, Springer Nature Switzerland, 2020; 72-73. *corresponding author [link]

2021/05: Group Leader (Senior Researcher) at HPI

2020: PostDoc at HPI

2017-2019: PostDoc at Luxembourg Institute of Health, joint project with Nanyang Technological University Singapore

2014-2020: PostDoc at Max Delbrück Center for Molecular Medicine in the Helmholtz Association

2009-2014: PhD in Theoretical Biophysics at Humboldt University Berlin and Max Delbrück Center for Molecular Medicine in the Helmholtz Association

2003-2009: studies of Mathematics (diploma), Humboldt University Berlin and École Polytechnique, France

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