List of publications

Gralinska, E.; Vingron, M.: Association Plots: visualizing cluster-specific associations in high-dimensional correspondence analysis biplots. Journal of the Royal Statistical Society - Series C: Applied Statistics 72 (4), pp. 1023 - 1040 (2023)

Jatzlau, J.; Mendez, P.-L.; Altay, A.; Raaz, L.; Zhang, Y.; Mähr, S.; Sesver, A.; Reichenbach, M.; Mundlos, S.; Vingron, M. et al.; Knaus, P.: Fluid shear stress-modulated chromatin accessibility reveals the mechano-dependency of endothelial SMAD1/5-mediated gene transcription. iScience 26 (9), 107405 (2023)

Lienhard, M.; van den Beucken , T.; Timmermann, B.; Hochradel, M.; Boerno, S.; Caiment , F.; Vingron, M.; Herwig, R.: IsoTools: a flexible workflow for long-read transcriptome sequencing analysis. Bioinformatics, btad364 (2023)

Mehringer, S.; Seiler, E.; Droop, F.; Mitra, D.; Rahn, R.; Vingron, M.; Reinert, K.: Hierarchical Interleaved Bloom Filter: enabling ultrafast, approximate sequence queries. Genome Biology: Biology for the Post-Genomic Era 24 (1), 131 (2023)

De Maio, N.; Kalaghatgi, P.; Turakhia, Y.; Corbett-Detig, R.; Quang Minh, B.; Goldman, N.: Maximum likelihood pandemic-scale phylogenetics. Nature Genetics 55, pp. 746 - 752 (2023)

Melo, U. S.; Jatzlau, J.; Prada-Medina, C. A.; Flex, E.; Hartmann, S.; Ali, S.; Schöpflin, R.; Bernardini, L.; Ciolfi, A.; Moeinzadeh, H. et al.; Klever, M.-K.; Altay, A.; Vallecillo-García, P.; Carpentieri, G.; Delledonne, M.; Ort, M.-J.; Schwestka, M.; Battista Ferrero, G.; Tartaglia, M.; Brusco, A.; Gossen, M.; Strunk, D.; Geißler, S.; Mundlos, S.; Stricker, S.; Knaus, P.; Giorgio, E.; Spielmann, M.: Enhancer hijacking at the ARHGAP36 locus is associated with connective tissue to bone transformation. Nature Communications 14, 2034 (2023)

Kibar, G.; Vingron, M.: Prediction of protein–protein interactions using sequences ofintrinsically disordered regions. Proteins: Structure, Function, and Bioinformatics, prot.26486 (2023)

Klimm, F.; Jones, N. S.; Schaub, M. T.: Modularity Maximization for Graphons. SIAM Journal on Applied Mathematics 82 (6) (2022)

Klimm, F.: Quantifying the 'end of history' through a Bayesian Markov-chain approach. Royal Society Open Science 9 (11), 221131 (2022)

Schöpflin, R.; Melo, U. S.; Moeinzadeh, M. H.; Heller, D.; Laupert, V.; Hertzberg, J.; Holtgrewe, M.; Alavi, N.; Klever, M.-K.; Jungnitsch, J. et al.; Comak, E.; Türkmen, S.; Horn, D.; Duffourd, Y.; Faivre, L.; Callier, P.; Sanlaville, D.; Zuffardi, O.; Tenconi, R.; Kurtas, N. E.; Giglio, S.; Prager, B.; Latos-Bielenska, A.; Vogel, I.; Bugge, M.; Tommerup, N.; Spielmann, M.; Vitobello, A.; Kalscheuer, V. M.; Vingron, M.; Mundlos, S.: Integration of Hi-C with short and long-read genome sequencing reveals the structure of germline rearranged genomes. Nature Communications 13, 6470 (2022)

Schindler, M.; Osterwalder, M.; Harabula, I.; Wittler, L.; Tzika, A. C.; Dechmann, D.; Vingron, M.; Visel, A.; Haas, S.; Real, F. M.: Co-option of the transcription factor SALL1 in mole ovotestis formation. bioRxiv, 514220 (2022)

Ringel, A.; Szabo, Q.; Chiariello, A. M.; Chudzik, K.; Schöpflin, R.; Rothe, P.; Mattei, A. L.; Zehnder, T.; Harnett, D.; Laupert, V. et al.; Bianco, S.; Hetzel, S.; Glaser, J.; Phan, M. H. Q.; Schindler, M.; Ibrahim, D. M.; Paliou, C.; Esposito, A.; Prada-Medina, C. A.; Haas, S. A.; Giere, P.; Vingron, M.; Wittler, L.; Meissner, A.; Nicodemi, M.; Cavalli, G.; Bantignies, F.; Mundlos, S.; Robson, M. I.: Repression and 3D-restructuring resolves regulatory conflicts in evolutionarily rearranged genomes. Cell 185 (20), e21, pp. 3689 - 3704 (2022)

Klimm, F.: Topological data analysis of truncated contagion maps. Chaos 32, 073108 (2022)

Baranasic, D.; Hörtenhuber, M.; Balwierz, P.; Zehnder, T.; Mukarram, A. K.; Nepal, C.; Varnai, C.; Hadzhiev, Y.; Jimenez- Gonzalez, A.; Li, N. et al.; Wragg, J.; D’Orazio, F.; Díaz, N.; Hernández- Rodríguez, B.; Chen, Z.; Stoiber, M.; Dong, M.; Stevens, I.; Ross, S. E.; Eagle, A.; Martin, R.; Obasaju, P.; Rastegar, S.; McGarvey, A. C.; Kopp, W.; Chambers, E.; Wang, D.; Kim, H. R.; Acemel, R. D.; Naranjo, S.; Lapinski, M.; Chong, V.; Mathavan, S.; Peers, B.; Sauka-Spengler, T.; Vingron, M.; Carninci, P.; Ohler, U.; Lacadie, S. A.; Burgess, S.; Winata, C.; van Eeden, F.; Vaquerizas, J. M.; Gómez-Skarmeta, J. L.; Onichtchouk, D.; Brown, B. J.; Bogdanovic, O.; Westerfield, M.; Wardle, F. C.; Daub, C. O.; Lenhard, B.; Müller, F.: Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis-regulatory elements. Nature Genetics 54 (7), pp. 1037 - 1050 (2022)

Rosebrock, D.; Arora, S.; Mutukula, N.; Volkman, R.; Gralinska, E.; Balaskas, A.; Aragonés Hernández, A.; Buschow, R.; Brändl, B.; Müller, F.-J. et al.; Arndt, P. F.; Vingron, M.; Elkabetz, Y.: Enhanced cortical neural stem cell identity through short SMAD and WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells. Nature Cell Biology 24, pp. 981 - 995 (2022)

Li, Y.; Chen, S.; Rapakoulia, T.; Kuwahara, H.; Yip, K. Y.; Gao, X.: Deep learning identifies and quantifies recombination hotspot determinants. Bioinformatics 38 (10), pp. 2683 - 2691 (2022)

Gralinska, E.; Kohl, C.; Fadakar, S.; Vingron, M.: Visualizing Cluster-specific Genes from Single-cell Transcriptomics Data Using Association Plots. Journal of Molecular Biology 434 (11), 167525 (2022)

Hertzberg, J.; Mundlos, S.; Vingron, M.; Gallone, G.: TADA – a Machine Learning Tool for Functional Annotation based Prioritisation of Putative Pathogenic CNVs. Genome Biology 23, 67 (2022)

Ly, L.-H.; Vingron, M.: Effect of imputation on gene network reconstruction from single-cell RNA-seq data. Patterns 3, 100414 (2022)

Glaser, L. V.; Steiger, M.; Fuchs, A.; van Bömmel, A.; Einfeldt, E.; Chung, H.-R.; Vingron, M.; Meijsing, S. H.: Assessing genome-wide dynamic changes in enhancer activity during early mESC differentiation by FAIRE-STARR-seq. Nucleic Acids Research (London) 49 (21), gkab1100, pp. 12178 - 12195 (2021)