Publications of the group Biochemical Network Analysis
Showing entries 21 - 30 out of 42
2023
Buchner, B., Clement, T. J., de Groot, D. H., & Zanghellini, J. (2023). ecmtool: fast and memory-efficient enumeration of elementary conversion modes. Bioinformatics (Oxford, England), 39(3), Article btad095. https://doi.org/10.1093/bioinformatics/btad095
Schaier, M., Theiner, S., Baier, D., Braun, G., Berger, W., & Koellensperger, G. (2023). Multiparametric Tissue Characterization Utilizing the Cellular Metallome and Immuno-Mass Spectrometry Imaging. JACS Au, 3(2), 419-428. https://doi.org/10.1021/jacsau.2c00571
2022
Schoeberl, A., Gutmann, M., Theiner, S., Corte-Rodriguez, M., Braun, G., Vician, P., Berger, W., & Koellensperger, G. (2022). The copper transporter CTR1 and cisplatin accumulation at the single-cell level by LA-ICP-TOFMS. Frontiers in Molecular Biosciences, 9, Article 1055356. https://doi.org/10.3389/fmolb.2022.1055356
El Abiead, Y., Bueschl, C., Panzenboeck, L., Wang, M., Doppler, M., Seidl, B., Zanghellini, J., Dorrestein, P. C., & Koellensperger, G. (2022). Heterogeneous multimeric metabolite ion species observed in LC-MS based metabolomics data sets. Analytica Chimica Acta, 1229, Article 340352. https://doi.org/10.1016/j.aca.2022.340352
Mildau, K., van der Hooft, J. J. J., Flasch, M., Warth, B., El Abiead, Y., Koellensperger, G., Zanghellini, J., & Bueschl, C. (2022). Homologue Series Detection and Management in LC-MS data with homologueDiscoverer. Bioinformatics, 38(22), 5139-5140. Article btac647. https://doi.org/10.1093/bioinformatics/btac647
Gotsmy, M., Brunmair, J., Bueschl, C., Gerner, C., & Zanghellini, J. (2022). Probabilistic quotient's work and pharmacokinetics' contribution: countering size effect in metabolic time series measurements. BMC Bioinformatics, 23(1), Article 379. https://doi.org/10.1186/s12859-022-04918-1
Bueschl, C., Doppler, M., Varga, E., Seidl, B., Flasch, M., Warth, B., & Zanghellini, J. (2022). PeakBot: machine-learning-based chromatographic peak picking. Bioinformatics, 38(13), 3422-3428. https://doi.org/10.1093/bioinformatics/btac344
Müller, S., Szeliova, D., & Zanghellini, J. (2022). Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth. PLoS Computational Biology, 18(2), Article e1009843. https://doi.org/10.1371/journal.pcbi.1009843
2021
Buchner, B. A., & Zanghellini, J. (2021). EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search. BMC Bioinformatics, 22(1), Article 547. https://doi.org/10.1186/s12859-021-04417-9
Müller, S., Szeliova, D., & Zanghellini, J. (2021). Elementary vectors and autocatalytic sets for computational models of cellular growth. bioRxiv. https://doi.org/10.1101/2021.10.31.466640
Showing entries 21 - 30 out of 42