List of publications

Rapakoulia, T.; Lopez Ruiz de Vargas, S.; Akbari-Omgba, P.; Laupert, V.; Ulitsky, I.; Vingron, M.: CENTRE: a gradient boosting algorithm for Cell-type-specific ENhancer-Target pREdiction. Bioinformatics 39 (11), btad687 (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)

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)

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 39 (6), 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 (1), 2034 (2023)

Kibar, G.; Vingron, M.: Prediction of protein–protein interactions using sequences ofintrinsically disordered regions. Proteins: Structure, Function, and Bioinformatics 91 (7), pp. 980 - 990 (2023)

Raschka , T.; Sood , M.; Schultz, B.; Altay, A.; Ebeling, C.; Fröhlich, H.: AI reveals insights into link between CD33 and cognitive impairment in Alzheimer’s Disease. PLOS Computational Biology 19 (2), e1009894 (2023)

Schindler, M.; Osterwalder, M.; Harabula, I.; Wittler, L.; Tzika, A. C.; Dechmann, D. K. N.; Vingron, M.; Visel, A.; Haas, S.; Real, F. M.: Induction of kidney-related gene programs through co-option of SALL1 in mole ovotestes. Development 150 (17), dev201562 (2023)

Kibar, G.: Exploring feature identification and machine learning in predicting protein-protein interactions of disordered proteins. Dissertation (2023)

Rosebrock, D.: Dissecting regional heterogeneity and modeling transcriptional cascades in brain organoids. Dissertation, vii, 129 pp. (2023)

Bressin, A. S.: A Multi-Omics Analysis of Transcription Control by BRD4. Dissertation, ix, 205 pp. (2023)