Publications

2022

Matek, C.

More than just sound: Harnessing metadata to improve neural network classifiers for medical auscultation.

Patterns 3:100426 (2022)

Schork, A.J. ; Peterson, R.E. ; Dahl, A. ; Cai, N. ; Kendler, K.S.

Author Correction: Indirect paths from genetics to education (Nature Genetics, (2022), 54, 4, (372-373), 10.1038/s41588-021-00999-5).

Nat. Genet., DOI: 10.1038/s41588-022-01092-1 (2022)

Falkai, P. ; Koutsouleris, N. ; Bertsch, K. ; Bialas, M. ; ... ; Cai, N. ; Peters, A. ; Schmitt, A. ; Theis, F.J. ; Wurst, W. ; Priller, J.

Concept of the Munich/Augsburg Consortium Precision in Mental Health for the German Center of Mental Health.

Front. Psychiatr. 13:815718 (2022)

Schork, A.J. ; Peterson, R.E. ; Dahl, A. ; Cai, N. ; Kendler, K.S.

Indirect paths from genetics to education.

Nat. Genet. 54, 372-373 (2022)

Nguyen, T.D. ; Harder, A. ; Xiong, Y. ; Kowalec, K. ; ... ; Cai, N. ; Lu, Y.

Genetic heterogeneity and subtypes of major depression.

Mol. Psychiatry 27, 1667–1675 (2022)

Sherman, E. ; Alejo, D. ; Wood-Doughty, Z. ; Sussman, M. ; ... ; Ahmidi, N. ; Whitman, G.

Leveraging machine learning to predict 30-day hospital readmission after cardiac surgery.

Ann. Thorac. Surg., DOI: 10.1016/j.athoracsur.2021.11.011 (2022)

Zou, J. ; Gopalakrishnan, S. ; Parker, C.C. ; Nicod, J. ; ... ; Cai, N. ; Palmer, A.A. ; Flint, J.

Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility.

Genes Genomes Genetics G3 12:jkab394 (2022)

2021

Jin, K.X. ; Zuo, R. ; Anastassiadis, K. ; Klungland, A. ; Marr, C. ; Filipczyk, A.A.

N6-methyladenosine (m⁶A) depletion regulates pluripotency exit by activating signaling pathways in embryonic stem cells.

Proc. Natl. Acad. Sci. U.S.A. 118:e2105192118 (2021)

Holmberg, O. ; Lenz, T. ; Koch, V. ; Alyagoob, A. ; Utsch, L. ; ... ; Marr, C. ; Joner, M. ; Nicol, P.

Histopathology-based deep-learning predicts atherosclerotic lesions in intravascular imaging.

Front. Cardiovasc. Med. 8:779807 (2021)

Moebel, E. ; Martinez-Sanchez, A. ; Lamm, L. ; Righetto, R.D. ; Wietrzynski, W. ; Albert, S. ; Larivière, D. ; ... ; Peng, T. ; Engel, B.D. ; Kervrann, C.

Author Correction: Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms (Nature Methods, (2021), 18, 11, (1386-1394), 10.1038/s41592-021-01275-4).

Nat. Methods, DOI: 10.1038/s41592-021-01349-3 (2021)

Sadafi, A. ; Makhro, A. ; Livshits, L. ; Navab, N. ; ... ; Albarqouni, S. ; Marr, C.

Sickle cell disease severity prediction from percoll gradient images using graph convolutional networks.

In: (3rd MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, 27 September-01 October 2021, Virtual, Online). 2021. 216-225 (Lect. Notes Comput. Sc. ; 12968 LNCS)

Yu, Z. ; Zhai, Y. ; Han, X. ; Peng, T. ; Zhang, X.Y.

MouseGAN: GAN-based multiple MRI modalities synthesis and segmentation for mouse brain structures.

In: (MICCAI 2021: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 27 September-01 October 2021, Virtual, Online). 2021. 442-450 (Lect. Notes Comput. Sc. ; 12901 LNCS)

Han, X. ; Zhai, Y. ; Yu, Z. ; Peng, T. ; Zhang, X.Y.

Detecting extremely small lesions in mouse brain MRI with point annotations via multi-task learning.

In: (12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, 27 September 2021, Virtual, Online). 2021. 498-506 (Lect. Notes Comput. Sc. ; 12966 LNCS)

Wagner, S.J. ; Khalili, N. ; Sharma, R. ; Boxberg, M. ; Marr, C. ; de Back, W. ; Peng, T.

Structure-preserving multi-domain stain color augmentation using style-transfer with disentangled representations.

In: (24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, 27 September-01 October 2021, Virtual, Online). 2021. 257-266 (Lect. Notes Comput. Sc. ; 12908 LNCS)

Oala, L. ; Murchison, A.G. ; Balachandran, P. ; Choudhary, S. ; ... ; Matek, C. ; Wiegand, T.

Machine learning for health: Algorithm auditing & quality control.

J. Med. Syst. 45:105 (2021)

Moebel, E. ; Martinez-Sanchez, A. ; Lamm, L. ; Righetto, R.D. ; Wietrzynski, W. ; Albert, S. ; Larivière, D. ; ... ; Peng, T. ; Engel, B.D. ; Kervrann, C.

Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms.

Nat. Methods 18, 1386-1394 (2021)

Cai, N. ; Gomez-Duran, A. ; Yonova-Doing, E. ; Kundu, K. ; Burgess, A.I. ; ... ; Howson, J.M.M. ; Stegle, O. ; Chinnery, P.F. ; Soranzo, N.

Mitochondrial DNA variants modulate N-formylmethionine, proteostasis and risk of late-onset human diseases.

Nat. Med. 27, 1564-1575 (2021)

Pachl, E. ; Zamanian, A. ; Stieler, M. ; Bahr, C. ; Ahmidi, N.

Early-, late-, and very late-term prediction of target lesion failure in coronary artery stent patients: An international multi-site study.

Appl. Sci. 11:6986 (2021)

Matek, C. ; Krappe, S. ; Münzenmayer, C. ; Haferlach, T. ; Marr, C.

Highly accurate differentiation of bone marrow cell morphologies using deep neuralnetworks on a large image dataset

Blood 138, 1917-1927 (2021)

Zhao, B. ; Ren, Y. ; Yu, Z. ; Yu, J. ; Peng, T. ; Zhang, X.Y.

AUCseg: An automatically unsupervised clustering toolbox for 3D-segmentation of high-grade gliomas in multi-parametric MR images.

Front. Oncol. 11:679952 (2021)

Lesch, S. ; Blumenberg, V. ; Stoiber, S. ; Gottschlich, A. ; ... ; Jastroch, M. ; Lamp, D. ; Thomas, M. ; Marr, C. ; Rothenfußer, S. ; Endres, S. ; Kobold, S.

T cells armed with C-X-C chemokine receptor type 6 enhance adoptive cell therapy for pancreatic tumours.

Nat. Bio. Eng., DOI: 10.1038/s41551-021-00737-6 (2021)

Glauche, I. ; Marr, C.

Mechanistic models of blood cell fate decisions in the era of single-cell data.

Curr. Opin. Syst. Biol. 28, 100355 (2021)

Cadilha, B.L. ; Benmebarek, M.R. ; Dorman, K. ; Oner, A. ; ... ; Thomas, M. ; Marr, C. ; Kobold, S.

Combined tumor-directed recruitment and protection from immune suppression enable CAR T cell efficacy in solid tumors.

Sci. Adv. 7:eabi5781 (2021)

Hecker, J.S. ; Hartmann, L. ; Riviere, J. ; Buck, M.C. ; ... ; Marr, C. ; Götze, K.S.

CHIP & HIPs: Clonal hematopoiesis is common in hip arthroplasty patients and associates with autoimmune disease.

Blood 138, 1727-1732 (2021)

von Streitberg, A. ; Jäkel, S. ; Eugenin von Bernhardi, J. ; Straube, C. ; Buggenthin, F. ; Marr, C. ; Dimou, L.

NG2-glia transiently overcome their homeostatic network and contribute to wound closure after brain injury.

Front. Cell Dev. Biol. 9:662056 (2021)

Klinger, E. ; Motta, A. ; Marr, C. ; Theis, F.J. ; Helmstaedter, M.

Cellular connectomes as arbiters of local circuit models in the cerebral cortex.

Nat. Commun. 12:2785 (2021)

Loureiro, H. ; Becker, T. ; Bauer-Mehren, A. ; Ahmidi, N. ; Weberpals, J.

Artificial intelligence for prognostic scores in oncology: A benchmarking study.

Front. Artif. Intell. 4:625573 (2021)

Schouten, J.P.E. ; Matek, C. ; Jacobs, L.F.P. ; Buck, M.C. ; Bošnački, D. ; Marr, C.

Tens of images can suffice to train neural networks for malignant leukocyte detection.

Sci. Rep. 11:7995 (2021)

Veerman, F. ; Popović, N. ; Marr, C.

Parameter inference with analytical propagators for stochastic models of autoregulated gene expression.

Int. J. Nonlinear Sci., DOI: 10.1515/ijnsns-2019-0258 (2021)

Waibel, D.J.E. ; Shetab Boushehri, S. ; Marr, C.

InstantDL: An easy-to-use deep learning pipeline for image segmentation and classification.

BMC Bioinformatics 22:103 (2021)

Bonder, M.J. ; Smail, C. ; Gloudemans, M.J. ; Frésard, L. ; Jakubosky, D. ; ... ; Cai, N. ; Montgomery, S.B. ; Stegle, O.

Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics.

Nat. Genet. 53, 313-321 (2021)

Bast, L. ; Buck, M.C. ; Hecker, J.S. ; Oostendorp, R.A.J. ; Götze, K.S. ; Marr, C.

Computational modeling of stem and progenitor cell kinetics identifies plausible hematopoietic lineage hierarchies.

iScience 24:102120 (2021)

Lupperger, V. ; Marr, C. ; Chapouton, P.

Correction: Reoccuring neural stem cell divisions in the adult zebrafish telencephalon are sufficient for the emergence of aggregated spatio-temporal patterns.

PLoS Biol. 19:e3001132 (2021)

Chatzinakos, C. ; Lee, D. ; Cai, N. ; Vladimirov, V.I. ; Webb, B.T. ; ... ; Bacanu, S.A.

Increasing the resolution and precision of psychiatric genome-wide association studies by re-imputing summary statistics using a large, diverse reference panel.

Am. J. Med. Genet. B 196, 16-27 (2021)

Brunn, D. ; Turkowski, K. ; Günther, S. ; Weigert, A. ; ... ; Stathopoulos, G.T. ; Savai, R.

Interferon regulatory factor 9 promotes lung cancer progression via regulation of versican.

Cancers 13:208 (2021)

Sadafi, A. ; Moya Sans, L.M. ; Makhro, A. ; Livshits, L. ; Navab, N. ; ... ; Albarqouni, S. ; Marr, C.

Fourier transform of percol gradients boosts CNN classification ofhereditary hemolytic anemias.

In: (2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 13-16 April 2021, Nice, France). 2021. 966-970

Yu, Z. ; Han, X. ; Zhao, B. ; Zhuo, Y. ; Ren, Y. ; ... ; Lamm, L. ; Marr, C. ; Shan, F. ; Peng, T. ; Zhang, X.-Y.

DABC-Net for robust pneumonia segmentation and prediction of COVID-19 progression on chest CT scans.

Research Square, in press (2021)

2020

Sadafi, A. ; Makhro, A. ; Bogdanova, A. ; Navab, N. ; Peng, T. ; Albarqouni, S. ; Marr, C.

Attention based multiple instance learning for classification of blood cell disorders.

In:. 2020. 246-256 (Lect. Notes Comput. Sc. ; 12265 LNCS)

Peng, T. ; Lamm, L. ; Loeffler, D. ; Ahmed, N. ; Navab, N. ; ... ; Marr, C.

Background and illumination correction for time-lapse microscopy data with correlated foreground.

In:. 2020. 174-183 (Lect. Notes Comput. Sc. ; 12265 LNCS)

Schuh, L. ; Loos, C. ; Pokrovsky, D. ; Imhof, A. ; Rupp, R.A.W. ; Marr, C.

H4K20 methylation is differently regulated by dilution and demethylation in proliferating and cell-cycle-arrested xenopus embryos.

Cell Syst. 11, 653-662.e8 (2020)

Matek, C. ; Spiekermann, K. ; Marr, C.

Zytomorphologische Diagnostik mithilfe von künstlicher Intelligenz (KI).

Tumordiagnos. Ther. 41, 666-668 (2020)

Lupperger, V. ; Marr, C. ; Chapouton, P.

Reoccurring neural stem cell divisions in the adult zebrafish telencephalon are sufficient for the emergence of aggregated spatiotemporal patterns.

PLoS Biol. 18:e3000708 (2020)

Chlis, N.-K. ; Karlas, A. ; Fasoula, N.-A. ; Kallmayer, M. ; Eckstein, H.H. ; Theis, F.J. ; Ntziachristos, V. ; Marr, C.

A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography.

Photoacoustics 20:100203 (2020)

Fischer, C.A, ; Besora-Casals, L. ; Rolland, S.G. ; Haeussler, S. ; ... ; Marr, C.

MitoSegNet: Easy-to-use deep learning segmentation for analyzing mitochondrial morphology.

iScience 23:101601 (2020)

Jiang, D. ; Christ, S. ; Correa-Gallegos, D. ; Ramesh, P. ; Kalgudde Gopal, S. ; Wannemacher, J. ; Mayr, C. ; Lupperger, V. ; Yu, Q. ; Ye, H. ; Mück-Häusl, M. ; Rajendran, V. ; Wan, L. ; Liu, J. ; Mirastschijski, U. ; Volz, T. ; Marr, C. ; Schiller, H. B. ; Rinkevich, Y.

Injury triggers fascia fibroblast collective cell migration to drive scar formation through N-cadherin.

Nat. Commun. 11:5653 (2020)

Chatzinakos, C. ; Georgiadis, F. ; Lee, D. ; Cai, N. ; Vladimirov, V.I. ; ... ; Bacanu, S.A.

TWAS pathway method greatly enhances the number of leads for uncovering the molecular underpinnings of psychiatric disorders.

Am. J. Med. Genet. B 183, 454-463 (2020)

Cai, N. ; Choi, K.W. ; Fried, E.I.

Reviewing the genetics of heterogeneity in depression: Operationalizations, manifestations, and etiologies.

Hum. Mol. Genet. 29, R10-R18 (2020)

Bheda, P. ; Aguilar-Gomez, D. ; Becker, N.B. ; Becker, J. ; Stavrou, E. ; Kukhtevich, I. ; ... ; Marr, C. ; Schneider, R.

Single-cell tracing dissects regulation of maintenance and inheritance of transcriptional reinduction memory.

Mol. Cell 78, 915-925 (2020)

Matek, C. ; Schwarz, S. ; Spiekermann, K. ; Marr, C.

Abstract: Recognition of AML blast cells in a curated single-cell dataset of leukocyte morphologies using deep convolutional neural networks.

In: Bildverarbeitung für die Medizin 2020. 2020. 53-54 (Inf. aktuell)

Schuh, L. ; Saint-Antoine, M. ; Sanford, E.M. ; Emert, B.L. ; ... ; Marr, C. ; Goyal, Y.

Gene networks with transcriptional bursting recapitulate rare transient coordinated high expression states in cancer.

Cell Syst. 10, 363-378.e12 (2020)

Jiang, D. ; Ramesh, P. ; Christ, S. ; Correa-Gallegos, D. ; Gopal, S.K. ; Yu, Q. ; Lupperger, V. ; Marr, C. ; Rinkevich, Y.

Scar formation is driven by N-cadherin dependent collective fibroblast migration.

Wound Repair Regen. 28, A16-A16 (2020)

Cai, N. ; Revez, J.A. ; Adams, M.J. ; Andlauer, T.F.M. ; ... ; Flint, J.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Nat. Genet. 52, 437-447 (2020)

Angerer, P. ; Fischer, D.S. ; Theis, F.J. ; Scialdone, A. ; Marr, C.

Automatic identification of relevant genes from low-dimensional embeddings of single-cell RNA-seq data.

Bioinformatics 36, 4291-4295 (2020)

Alabert, C. ; Loos, C. ; Voelker-Albert, M. ; Graziano, S. ; Forné, I. ; Reveron-Gomez, N. ; Schuh, L. ; Hasenauer, J. ; Marr, C. ; Imhof, A. ; Groth, A.

Domain model explains propagation dynamics and stability of histone H3K27 and H3K36 methylation landscapes.

Cell Rep. 30, 1223-1234 (2020)

2019

Lee, J. ; Ahmidi, N. ; Srinivasan, R. ; Alejo, D. ; Dinatale, J. ; ... ; Shpitser, I.

Finding predictors and causes of cardiac surgery ICU readmission using machine learning and causal inference.

Eur. Heart J. 40, 3575-3575 (2019)

Dahl, A. ; Cai, N. ; Ko, A. ; Laakso, M. ; Pajukanta, P. ; ... ; Zaitlen, N.

Reverse GWAS: Using genetics to identify and model phenotypic subtypes.

PLoS Genet. 15:e1008009 (2019)

Peng, T. ; Boxberg, M. ; Weichert, W. ; Navab, N. ; Marr, C.

Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval.

Lect. Notes Comput. Sc. 11764 LNCS, 676-684 (2019)

Sadafi, A. ; Koehler, N. ; Makhro, A. ; Bogdanova, A. ; Navab, N. ; Marr, C. ; Peng, T.

Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy.

Lect. Notes Comput. Sc. 11764 LNCS, 685-693 (2019)

Matek, C. ; Schwarz, S. ; Spiekermann, K. ; Marr, C.

Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks.

Nat. Mach. Intell. 1, 538-544 (2019)

Waibel, D.J.E. ; Tiemann, U. ; Lupperger, V. ; Semb, H. ; Marr, C.

In-silico staining from bright-field and fluorescent images using deep learning.

In:. 2019. 184-186 (Lect. Notes Comput. Sc. ; 11729 LNCS)

Schneider, M. ; Wang, L. ; Marr, C.

Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets.

Lect. Notes Comput. Sc. 11728 LNCS, 673-686 (2019)

Mishra, M. ; Schmitt, S. ; Zischka, H. ; Strasser, M. ; Navab, N. ; Marr, C. ; Peng, T.

Quantifying structural heterogeneity of healthy and cancerous mitochondria using a combined segmentation and classification USK-net.

Lect. Notes Comput. Sc. 11731 LNCS, 289-298 (2019)

Jiang, D. ; Christ, S. ; Gallegos, D.C. ; Ramesh, P. ; Gopal, S.K. ; Yu, Q. ; Mayr, C. ; Lupperger, V. ; Liu, J. ; Marr, C. ; Schiller, H. B. ; Rinkevich, Y.

Visualizing scar development in living tissues reveals the collective migration of fibroblasts mediated by N-cadherin.

Exp. Dermatol. 28, E13-E13 (2019)

Tischler, J. ; Gruhn, W.H. ; Reid, J. ; Allgeyer, E. ; Buettner, F. ; Marr, C. ; Theis, F.J. ; ... ; Surani, M.A.

Metabolic regulation of pluripotency and germ cell fate through alpha-ketoglutarate.

EMBO J. 38:e99518 (2019)

2018

Cai, N. ; Revez, J.A. ; Adams, M.J. ; Andlauer, T.F.M. ; ... ; Weissman, M.M.

Minimal phenotyping yields GWAS hits of low specificity for major depression.

bioRxiv, accepted (2018)

Peterson, R.E. ; Cai, N. ; Dahl, A.W. ; Bigdeli, T.B. ; Edwards, A.C. ; ... ; Kendler, K.S.

Molecular genetic analysis subdivided by adversity exposure suggests etiologic heterogeneity in major depression.

Am. J. Psychiatry 175, 545-554 (2018)

Backofen, R. ; Costa, F. ; Theis, F.J. ; Marr, C. ; Preusse, M. ; Becker, C. ; Saunders, S. ; ... ; Dovzhenko, O.

MicroRNA as an integral part of cell communication: Regularized target prediction and network prediction.

In: Lecture Notes in Bioengineerin. 2018. 85-100

Kyncl, M. ; Bast, L. ; Henkel, L. ; Theis, F.J. ; Oostendorp, R.A.J. ; Marr, C. ; Goetze, K.S.

Data driven computational modeling of hematopoiesis in myelodysplastic syndromes unveils differences in hematopoietic stem cell kinetics compared to age-matched healthy controls.

Blood 132 (2018)

Chatzopoulou, E.I. ; Raharja-Liu, P. ; Murschhauser, A. ; Sekhavati, F. ; Buggenthin, F. ; Vollmar, A.M. ; Marr, C. ; Rädler, J.O.

A single-cell micro-trench platform for automatic monitoring of cell division and apoptosis after chemotherapeutic drug administration.

Sci. Rep. 8:18042 (2018)

Bast, L. ; Calzolari, F. ; Strasser, M. ; Hasenauer, J. ; Theis, F.J. ; Ninkovic, J. ; Marr, C.

Increasing neural stem cell division asymmetry and quiescence are predicted to contribute to the age-related decline in neurogenesis.

Cell Rep. 25, 3231-3240.e8 (2018)

Feigelman, J ; Weindl, D. ; Theis, F.J. ; Marr, C. ; Hasenauer, J.

LNA++: Linear noise approximation with first and second order sensitivities.

In: Lecture Notes in Computer Science (16th International Conference on Computational Methods in Systems Biology, 12-14 September 2018, Brno; Czech Republic). 2018. 300-306 ( ; 11095 LNBI)

Damialis, A. ; Oteros, J. ; Troll, S. ; Lauer, S. ; Leier, V. ; Häring, H.-U. ; Kehmer, M. ; Thomas, M. ; ... ; Buters, J.T.M. ; Traidl-Hoffmann, C.

From pollen to fungal spore allergy: Alternaria spores under differing environmental regimes and the need for an electronic Spore Information Network (eSPIN) in Bavaria, Germany.

Allergy 73, 103-104 (2018)

Kriegel, F. ; Matek, C. ; Dršata, T. ; Kulenkampff, K. ; Tschirpke, S. ; ... ; Lipfert, J.

The temperature dependence of the helical twist of DNA.

Nucleic Acids Res. 46, 7998-8009 (2018)

Strasser, M. ; Hoppe, P.S. ; Loeffler, D. ; Kokkaliaris, K.D. ; ... ; Theis, F.J. ; Marr, C.

Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm.

Nat. Commun. 9:2697 (2018)

Viader Llargues, O. ; Lupperger, V. ; Pola-Morell, L. ; Marr, C. ; López-Schier, H.

Live cell-lineage tracing and machine learning reveal patterns of organ regeneration.

eLife 7:e30823 (2018)

Matek, C. ; Marr, C. ; Spiekermann, K.

Digital cytomorphology: Deep learning on an image data set of cell morphologies in acute myeloid leukemia.

In: (Workshop on Bildverarbeitung fur die Medizin, 11-13 March 2018, Erlangen). 2018. 10-10

Matek, C. ; Marr, C. ; Spiekermann, K.

Computer-aided morphological classification of blood cells relevant in Acute Myeloid Leukemia.

Oncol. Res. Treat. 41, 197-197 (2018)

2017

Speed, D. ; Cai, N. ; Johnson, M.R. ; Nejentsev, S. ; Balding, D.J.

Reevaluation of SNP heritability in complex human traits.

Nat. Genet. 49, 986-992 (2017)

Veerman, F. ; Marr, C. ; Popović, N.

Time-dependent propagators for stochastic models of gene expression: An analytical method.

J. Math. Biol., 1-52 (2017)

Lupperger, V. ; Buggenthin, F. ; Chapouton, P. ; Marr, C.

Image analysis of neural stem cell division patterns in the zebrafish brain.

Cytometry A 93A, 314-322 (2017)

Keskin, A.D. ; Kekuš, M. ; Adelsberger, H. ; Neumann, U. ; ... ; Peng, T. ; Sakmann, B. ; Busche, M.A.

BACE inhibition-dependent repair of Alzheimer's pathophysiology.

Proc. Natl. Acad. Sci. U.S.A. 114, 8631-8636 (2017)

Peng, T. ; Thorn, K. ; Schroeder, T. ; Wang, L. ; Theis, F.J. ; Marr, C. ; Navab, N.

A BaSiC tool for background and shading correction of optical microscopy images.

Nat. Commun. 8:14836 (2017)

Gokkaya, M. ; Bezold, S. ; Rauer, D. ; Häring, F. ; Beck, I. ; Chaker, A. ; Thomas, M. ; Hammel, G. ; Neumann, A.U. ; Damialis, A. ; Gilles-Stein, S. ; Traidl-Hoffmann, C.

From exposure to reaction: Panel study on the relationship between pollen exposure and the local and systemic expression of inflammatory parameters.

Exp. Dermatol. 26, E5-E5 (2017)

Blasi, T. ; Buettner, F. ; Strasser, M. ; Marr, C. ; Theis, F.J.

CgCorrect: A method to correct for confounding cell-cell variation due to cell growth in single-cell transcriptomics.

Phys. Biol. 14:036001 (2017)

Hilsenbeck, O. ; Schwarzfischer, M. ; Loeffler, D. ; Dimopoulos, S. ; Hastreiter, S. ; Marr, C. ; Theis, F.J. ; Schroeder, T.

fastER: A user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy.

Bioinformatics 33, 2020-2028 (2017)

Buggenthin, F. ; Buettner, F. ; Hoppe, P.S. ; Endele, M. ; Kroiss, M. ; Strasser, M. ; Schwarzfischer, M. ; Loeffler, D. ; Kokkaliaris, K.D. ; Hilsenbeck, O. ; Schroeder, T. ; Theis, F.J. ; Marr, C.

Prospective identification of hematopoietic lineage choice by deep learning.

Nat. Methods, DOI: 10.1038/nmeth.4182 (2017)

2016

Feigelman, J. ; Ganscha, S. ; Hastreiter, S. ; Schwarzfischer, M. ; Filipczyk, A. ; Schröder, T. ; Theis, F.J. ; Marr, C. ; Claassen, M.

Analysis of cell lineage trees by exact bayesian inference identifies negative autoregulation of nanog in mouse embryonic stem cells.

Cell Syst. 3, 480-490 (2016)

Bortsova, G. ; Sterr, M. ; Wang, L. ; Milletari, F. ; Navab, N. ; Böttcher, A. ; Lickert, H. ; Theis, F.J. ; Peng, T.

Mitosis detection in intestinal crypt images with hough forest and conditional random fields.

Lect. Notes Comput. Sc. 10019, 287-295 (2016)

Mishra, M. ; Schmitt, S. ; Wang, L. ; Strasser, M. ; Marr, C. ; Navab, N. ; Zischka, H. ; Peng, T.

Structure-based assessment of cancerous mitochondria using deep networks.

In: Proceedings (Proceedings / IEEE 13th International Symposium on Biomedical Imaging (ISBI), 13-16 April 2016, Prague, Czech Republic). IEEE, 2016.

Hilsenbeck, O. ; Schwarzfischer, M. ; Skylaki, S. ; Schauberger, B. ; Hoppe, P.S. ; Loeffler, D. ; Kokkaliaris, K.D. ; ... ; Filipczyk, A. ; Strasser, M. ; Buggenthin, F. ; Feigelman, J. ; Krumsiek, J. ; van den Berg, A.J. ; Endele, M. ; Marr, C. ; Theis, F.J. ; Schroeder, T.

Software tools for single-cell tracking and quantification of cellular and molecular properties.

Nat. Biotechnol. 34, 703-706 (2016)

Hoppe, P.S. ; Schwarzfischer, M. ; Loeffler, D. ; Kokkaliaris, K.D. ; Hilsenbeck, O. ; Moritz, N. ; Endele, M. ; Filipczyk, A. ; Gambardella, A. ; Ahmed, N. ; Etzrodt, M. ; ... ; Rieger, M.A. ; Marr, C. ; Strasser, M. ; Schauberger, B. ; Burtscher, I. ; Bürger, A. ; Lickert, H. ; Theis, F.J. ; Schroeder, T.

Early myeloid lineage choice is not initiated by random PU.1 to GATA1 protein ratios.

Nature 535, 299-302 (2016)

Tuschl, K. ; Meyer, E. ; Valdivia, L.E. ; Zhao, N. ; ... ; Cuno, S.M. ; Prokisch, H. ; Mills, P.B. ; Kurian, M.A. ; Wilson, S.W.

Mutations in SLC39A14 disrupt manganese homeostasis and cause childhood-onset parkinsonism-dystonia.

Nat. Commun. 7:11601 (2016)

Dragoi, D. ; Krattenmacher, A. ; Mishra, V.K. ; Schmidt, J. ; Kloos, U. ; Meixner, L.K. ; Hauck, S.M. ; Buggenthin, F. ; Schwartz, D. ; Marr, C. ; Johnsen, S.A. ; Scheel, C.

Twist1 induces distinct cell states depending on TGFBR1-activation.

Oncotarget 7, 30396-30407 (2016)

Marr, C. ; Zhou, J.X. ; Huang, S.

Single-cell gene expression profiling and cell state dynamics: Collecting data, correlating data points and connecting the dots.

Curr. Opin. Biotechnol. 39, 207-214 (2016)

Blasi, T. ; Feller, C. ; Feigelman, J. ; Hasenauer, J. ; Imhof, A. ; Theis, F.J. ; Becker, P.B. ; Marr, C.

Combinatorial histone acetylation patterns are generated by motif-specific reactions.

Cell Syst. 2, 49-58 (2016)

Angerer, P. ; Haghverdi, L. ; Büttner, M. ; Theis, F.J. ; Marr, C. ; Buettner, F.

Destiny: Diffusion maps for large-scale single-cell data in R.

Bioinformatics 32, 1241-1243 (2016)

2015

Cai, N. ; Chang, S. ; Li, Y. ; Li, Q. ; ... ; Flint, J.

Molecular signatures of major depression.

Curr. Biol. 25, 1146-1156 (2015)

CONVERGE consortium (Cai, N.)

Sparse whole-genome sequencing identifies two loci for major depressive disorder.

Nature 523, 588-591 (2015)

Cai, N. ; Li, Y. ; Chang, S. ; Liang, J. ; ... ; Flint, J.

Genetic control over mtDNA and its relationship to major depressive disorder.

Curr. Biol. 25, 3170-3177 (2015)

Wang, L. ; Belagiannis, V. ; Marr, C. ; Theis, F.J. ; Yang, G.Z. ; Navab, N.

Anatomic-landmark detection using graphical context modelling.

In: Proceedings (12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, 16-19 April 2015, Brooklyn, United States). 2015. 1304-1307

Loos, C. ; Marr, C. ; Theis, F.J. ; Hasenauer, J.

Approximate bayesian computation for stochastic single-cell time-lapse data using multivariate test statistics.

Lect. Notes Comput. Sc. 9308, 52-63 (2015)

Marr, C. ; Hasenauer, J. ; Theis, F.J.

Models and methods for systems biology and systems medicine: The Institute of Computational Biology at the Helmholtz Zentrum München.

Systembiologie.de 9, 40-43 (2015)

Feigelman, J. ; Popovic, N. ; Marr, C.

A case study on the use of scale separation-based analytical propagators for parameter inference in models of stochastic gene regulation.

J. Coupled Syst. Multiscale Dyn. 3, 164-173 (2015)

Preusse, M. ; Marr, C. ; Saunders, S. ; Maticzka, D. ; Lickert, H. ; Backofen, R. ; Theis, F.J.

SimiRa: A tool to identify coregulation between microRNAs and RNA-binding proteins.

RNA Biol. 12, 998-1009 (2015)

Filipczyk, A. ; Marr, C. ; Hastreiter, S. ; Feigelman, J. ; Schwarzfischer, M. ; Hoppe, P.S. ; Loeffler, D. ; Kokkaliaris, K.D. ; Endele, M. ; Schauberger, B. ; Hilsenbeck, O. ; Skylaki, S. ; Hasenauer, J. ; Anastassiadis, K. ; Theis, F.J. ; Schroeder, T.

Network plasticity of pluripotency transcription factors in embryonic stem cells.

Nat. Cell Biol. 17, 1235-1246 (2015)

Strasser, M. ; Feigelman, J. ; Theis, F.J. ; Marr, C.

Inference of spatiotemporal effects on cellular state transitions from time-lapse microscopy.

BMC Syst. Biol. 9:61 (2015)

Lupperger, V.

Bioimage informatic analysis of the spatial impact on cell state transitions.

München, Ludwig-Maximilians-Universität & Technische Universität, Bioinformatik, Master-Thesis, 2015, 57 S.

Theis, F.J. ; Ugelvig, L.V. ; Marr, C. ; Cremer, S.

Opposing effects of allogrooming on disease transmission in ant societies.

Philos. Trans. R. Soc. B - Biol. Sci. 370, DOI: 10.1098/rstb.2014.0108 (2015)

Popovic, N. ; Marr, C. ; Swain, P.S.

A geometric analysis of fast-slow models for stochastic gene expression.

J. Math. Biol. 72, 87-122 (2015)

Hug, S. ; Schwarzfischer, M. ; Hasenauer, J. ; Marr, C. ; Theis, F.J.

An adaptive scheduling scheme for calculating Bayes factors with thermodynamic integration using Simpson’s rule.

Stat. Comp. 26, 663-677 (2015)

Buettner, F. ; Natarajan, K.N. ; Casale, F.P. ; Proserpio, V. ; Scialdone, A. ; Theis, F.J. ; ... ; Marioni, J.C. ; Stegle, O.

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

Nat. Biotechnol. 33, 155-160 (2015)

2014

Reversat, A. ; Buggenthin, F. ; Merrin, J. ; Leithner, A. ; de Vries, I. ; Theis, F.J. ; Marr, C. ; Sixt, M.

Morphodynamic analysis of T lymphocyte migration in confined microenvironments.

Mol. Biol. Cell 25:P537 (2014)

Peng, T. ; Wang, L. ; Bayer, C. ; Conjeti, S. ; Baust, M. ; Navab, N.A.

Shading correction for whole slide image using low rank and sparse decomposition.

Lect. Notes Comput. Sc. 8673, 33-40 (2014)

Khakhutskyy, V. ; Schwarzfischer, M. ; Hubig, N. ; Plant, C. ; Marr, C. ; Rieger, M.A. ; Schröder, T. ; Theis, F.J.

Centroid clustering of cellular lineage trees.

Lect. Notes Comput. Sc. 8649, 15-29 (2014)

Feigelman, J. ; Theis, F.J. ; Marr, C.

MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data.

BMC Bioinformatics 15:240 (2014)

2013

Buggenthin, F. ; Marr, C. ; Schwarzfischer, M. ; Hoppe, P.S. ; Hilsenbeck, O. ; Schroeder, T. ; Theis, F.J.

An automatic method for robust and fast cell detection in bright field images from high-throughput microscopy.

BMC Bioinformatics 14:297 (2013)

2012

Sonnenschein, N. ; Marr, C. ; Hütt, M.-T.

A topological characterization of medium-dependent essential metabolic reactions.

Metabolites 2, 632-647 (2012)

Marr, C. ; Strasser, M. ; Schwarzfischer, M. ; Schroeder, T. ; Theis, F.J.

Multi-scale modeling of GMP differentiation based on single-cell genealogies.

FEBS J. 279, 3488-3500 (2012)

Konrad, M. ; Vyleta, M.L. ; Theis, F.J. ; Stock, M. ; Tragust, S. ; ... ; Marr, C. ; Cremer, S.

Social transfer of pathogenic fungus promotes active immunisation in ant colonies.

PLoS Biol. 10:e1001300 (2012)

Strasser, M. ; Theis, F.J. ; Marr, C.

Stability and multiattractor dynamics of a toggle switch based on a two-stage model of stochastic gene expression.

Biophys. J. 102, 19-29 (2012)

Marr, C. ; Hütt, M.-T.

Cellular automata on graphs: Topological properties of ER graphs evolved towards low-entropy dynamics.

Entropy 14, 993-1010 (2012)

2011

Schwarzfischer, M. ; Marr, C. ; Krumsiek, J. ; Hoppe, P.S. ; Schroeder, T. ; Theis, F.J.

Efficient fluorescence image normalization for time lapse movies.

In: Proceedings (Microscopic Image Analysis with Applications in Biology, 2nd September 2011, Heidelberg, Germany). Heidelberg: MIAAB, 2011. http://www.miaab.org/miaab-2011-

Kowarsch, A. ; Preusse, M. ; Marr, C. ; Theis, F.J.

miTALOS: Analyzing the tissue-specific regulation of signaling pathways by human and mouse microRNAs.

RNA 17, 809-819 (2011)

Krumsiek, J. ; Marr, C. ; Schroeder, T. ; Theis, F.J.

Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.

PLoS ONE 6:e22649 (2011)

Goeckenjan, G. ; Sitter, H. ; Thomas, M. ; Branscheid, D. ; ... ; Brüske, I. ; Wichmann, H.-E. ; Worth, H.

Prävention, Diagnostik, Therapie und Nachsorge des Lungenkarzinoms. Interdisziplinäre S3-Leitlinie der Deutschen Gesellschaft für Pneumologie und Beatmungsmedizin und der Deutschen Krebsgesellschaft - Kurzfassung.

Pneumologie 65, 51-75 (2011)

Goeckenjan, G. ; Sitter, H. ; Thomas, M. ; Branscheid, D. ; ... ; Brüske, I. ; Wichmann, H.-E. ; German Cancer Society ()

Prevention, diagnosis, therapy, and follow-up of lung cancer: Interdisciplinary guideline of the German Respiratory Society and the German Cancer Society.

Pneumologie 65, 39-59 (2011)

2010

Wittmann, D.M. ; Marr, C. ; Theis, F.J.

Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks.

J. Theor. Biol. 266, 436-448 (2010)

Kowarsch, A. ; Marr, C. ; Schmidl, D. ; Ruepp, A. ; Theis, F.J.

Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways.

PLoS ONE 5:e11154 (2010)

Liebovitch, L.S. ; Shehadeh, L.A. ; Jirsa, V.K. ; Hütt, M.-T. ; Marr, C.

Determining the properties of gene regulatory networks from expression data.

In: Das, S.* ; Caragea, D.* ; Welch, S.* ; Hsu, W.H.* [Eds.]: Handbook of Research on Computational Methodologies in Gene Regulatory Networks. IGI Global, 2010. 405-428

Lutter, D. ; Marr, C. ; Krumsiek, J. ; Lang, E.W. ; Theis, F.J.

Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects.

BMC Genomics 11:224 (2010)

Marr, C. ; Theis, F.J. ; Liebovitch, L.S. ; Hütt, M.-T.

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli.

PLoS Comput. Biol. 6, 31:e1000836 (2010)

Goeckenjan, G. ; Sitter, H. ; Thomas, M. ; Branscheid, D. ; ... ; Brüske, I. ; Wichmann, H.-E. ; Worth, H.

Pneumologie 64, Suppl.2, e1-e164 (2010)

2009

Marr, C. ; Hütt, M.-T.

Outer-totalistic cellular automata on graphs.

Phys. Lett. A 373, 546-549 (2009)

Webb, K.J. ; Norton, W.H.J. ; Trümbach, D. ; Meijer, A.H. ; Ninkovic, J. ; Topp, S. ; Heck, D. ; Marr, C. ; Wurst, W. ; Theis, F.J. ; Spaink, H.P. ; Bally-Cuif, L.

Zebrafish reward mutants reveal novel transcripts mediating the behavioral effects of amphetamine.

Genome Biol. 10:R81 (2009)

2008

Marr, C. ; Geertz, M. ; Hütt, M.-T. ; Muskhelisvili, G.

Dissecting the logical types of network control in gene expression profiles.

BMC Syst. Biol. 2:18 (2008)

2007

Marr, C. ; Müller-Linow, M. ; Hütt, M.-T.

Regularizing capacity of metabolic networks.

Phys. Rev. E 75:041917 (2007)

2006

Marr, C. ; Hütt, M.-T.