Publikationen von M. Huska

Love, M. I.; Huska, M.; Jurk, M.; Schöpflin, R.; Starick, S. R.; Schwahn, K.; Cooper, S. B.; Yamamoto, K. R.; Thomas-Chollier, M.; Vingron, M. et al.; Meijsing, S. H.: Role of the chromatin landscape and sequence in determining cell type-specific genomic glucocorticoid receptor binding and gene regulation. Nucleic Acids Research (London) 45 (4), S. 1805 - 1819 (2017)

Huska, M.; Vingron, M.: Improved Prediction of Non-methylated Islands in Vertebrates Highlights Different Characteristic Sequence Patterns. PLoS Computational Biology 12 (12), e1005249 (2016)

Eduati, F.; Mangravite, L. M.; Wang, T.; Tang, H.; Bare, J. C.; Huang, R.; Norman, T.; Kellen, M.; Menden, M. P.; Yang, J. et al.; Zhan, X.; Zhong, R.; Xiao, G.; Xia, M.; Abdo, N.; Kosyk, O.; Collaboration, N.-N.-U. D. T.; van Bömmel, A.; Caffrey, B.; Heinig, M.; Huska, M.; Mammana, A.; Perner, J.; Vingron, M.; Friend, S.; Dearry, A.; Simeonov, A.; Tice, R. R.; Rusyn, I.; Wright, F. A.; Stolovitzky, G.; Xie, Y.; Saez-Rodriguez, J.: Prediction of human population responses to toxic compounds by a collaborative competition. Nat Biotechnol 33 (9), S. 933 - 940 (2015)

Marsico, A.; Huska, M.; Lasserre, J.; Hu, H.; Vucicevic, D.; Musahl, A.; Ørom, U. A.; Vingron, M.: PROmiRNA: a new miRNA promoter recognition method uncovers the complex regulation of intronic miRNAs. Genome Biology 14 (8), S. R84 - R84 (2013)

Huska, M. R.: Using machine learning to predict and better understand DNA methylation and genomic enhancers. Dissertation, viii, 143 S., Freie Universität, Berlin (2018)