A. Jeltsch, P. Bashtrykov, M. Dukatz, and S. Adam. Dataset, (2022)Related to: Dukatz et al.: "DNA methyltransferase DNMT3A forms interaction networks with the CpG site and flanking sequence elements for efficient methylation", Journal of Biological Chemistry, 2022. doi: 10.1016/j.jbc.2022.102462.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: D’Errico, G., Ortona, O., Capuano, F., & Vitagliano, V. (2004). Diffusion Coefficients for the Binary System Glycerol + Water at 25 °C. A Velocity Correlation Study. Journal of Chemical & Engineering Data, 49(6), 1665-1670. doi: 10.1021/je049917u.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Segur, J. B., & Oberstar, H. E. (1951). Viscosity of Glycerol and Its Aqueous Solutions. Industrial & Engineering Chemistry, 43(9), 2117-2120. doi: 10.1021/ie50501a040.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Cristancho, D., Delgado, D., Martínez, F., Abolghassemi Fakhree, M. A., & Jouyban, A. (2011). Volumetric properties of glycerol + water mixtures at several temperatures and correlation with the Jouyban-Acree model. Revista Colombiana de Ciencias Químico Farmacéuticas, 40. 92-115.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Derlacki, Z. J., Easteal, A. J., Edge, A. V. J., Woolf, L. A., & Roksandic, Z. (1985). Diffusion coefficients of methanol and water and the mutual diffusion coefficient in methanol-water solutions at 278 and 298 K. The Journal of Physical Chemistry, 89(24), 5318-5322. doi: 10.1021/j100270a039.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Mikhail, S. Z., & Kimel, W. R. (1961). Densities and Viscosities of Methanol-Water Mixtures. Journal of Chemical & Engineering Data, 6(4), 533-537. doi: 10.1021/je60011a015.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: González, B., Calvar, N., Gómez, E., & Domínguez, Á. (2007). Density, dynamic viscosity, and derived properties of binary mixtures of methanol or ethanol with water, ethyl acetate, and methyl acetate at T=(293.15, 298.15, and 303.15)K. The Journal of Chemical Thermodynamics, 39(12), 1578-1588. doi: 10.1016/j.jct.2007.05.004.
A. Jeltsch, and J. Broche. Dataset, (2023)Related to: Broche et al., Genome-wide deposition of 6-methyladenine in human DNA reduces the viability of HEK293 cells and directly influences gene expression, Communications Biology, in press.
A. Jeltsch, P. Schnee, M. Khella, S. Weirich, J. Pleiss, and P. Bashtrykov. Software, (2023)Related to: Mina S. Khella, Philipp Schnee, Sara Weirich, Tan Bui, Alexander Bröhm, Pavel Bashtrykov, Jürgen Pleiss, Albert Jeltsch: The T1150A cancer mutant of the protein lysine methyltransferase NSD2 can introduce H3K36 trimethylation. J Biol Chem, 2023, 5, 104796. doi: 10.1016/j.jbc.2023.104796.
A. Jeltsch, P. Bashtrykov, and S. Adam. Dataset, (2023)Related to: Sabrina Adam, Viviane Klingel, Nicole E Radde, Pavel Bashtrykov, Albert Jeltsch (2023) On the accuracy of the epigenetic copy machine: comprehensive specificity analysis of the DNMT1 DNA methyltransferase. Nucleic Acids Research, gkad465. doi: 10.1093/nar/gkad465.
A. Jeltsch, P. Bashtrykov, and N. Rajaram. Dataset, (2023)Related to: Rajaram N, Kouroukli AG, Bens S, Bashtrykov P, Jeltsch A. (2023) Development of super-specific epigenome editing by targeted allele-specific DNA methylation. Epigenetics & Chromatin 16, 41. doi: 10.1186/s13072-023-00515-5.
M. Häußler. Dataset, (2024)Related to: Häussler M, Prins A, Le Roes-Hill M, Wittig U, Pleiss, J. (2024) EnzymeML-based modeling workflow: from raw data to kinetic parameters. ChemCatChem.
A. Jeltsch, P. Bashtrykov, and C. Albrecht. Dataset, (2024)Related to: Albrecht, C.; Rajaram, N.; Broche, J.; Bashtrykov, P.; Jeltsch, A. Locus specific and stable DNA demethylation at the H19/IGF2 ICR1 by epigenome editing using a dCas9-SunTag system and the catalytic domain of TET1. Genes 2024, 15(1), 80. doi: 10.3390/genes15010080.
A. Jeltsch, P. Bashtrykov, L. Dossmann, and M. Emperle. Dataset, (2024)Related to: Dossmann et al.: Specific DNMT3C flanking sequence preferences facilitate methylation of young murine retrotransposons. Submitted for publication.