Cellular location shapes quaternary structure of enzymes von Abrusán, György, Zelezniak, Aleksej

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Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure von Zrimec, Jan, Börlin, Christoph S., Buric, Filip, Muhammad, Azam Sheikh, Chen, Rhongzen, Siewers, Verena, Verendel, Vilhelm, Nielsen, Jens, Töpel, Mats, Zelezniak, Aleksej

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Metabolic dependencies drive species co-occurrence in diverse microbial communities von Zelezniak, Aleksej, Andrejev, Sergej, Ponomarova, Olga, Mende, Daniel R., Bork, Peer, Patil, Kiran Raosaheb

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Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends von Zrimec, Jan, Kokina, Mariia, Jonasson, Sara, Zorrilla, Francisco, Zelezniak, Aleksej

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Bayesian genome scale modelling identifies thermal determinants of yeast metabolism von Li, Gang, Hu, Yating, Jan Zrimec, Luo, Hao, Wang, Hao, Zelezniak, Aleksej, Ji, Boyang, Nielsen, Jens

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Ultra-fast proteomics with Scanning SWATH von Messner, Christoph B., Demichev, Vadim, Bloomfield, Nic, Yu, Jason S. L., White, Matthew, Kreidl, Marco, Egger, Anna-Sophia, Freiwald, Anja, Ivosev, Gordana, Wasim, Fras, Zelezniak, Aleksej, Jürgens, Linda, Suttorp, Norbert, Sander, Leif Erik, Kurth, Florian, Lilley, Kathryn S., Mülleder, Michael, Tate, Stephen, Ralser, Markus

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Functional Metabolomics Describes the Yeast Biosynthetic Regulome von Mülleder, Michael, Calvani, Enrica, Alam, Mohammad Tauqeer, Wang, Richard Kangda, Eckerstorfer, Florian, Zelezniak, Aleksej, Ralser, Markus

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Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes von Zelezniak, Aleksej, Sheridan, Steven, Patil, Kiran Raosaheb

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Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection von Messner, Christoph B., Demichev, Vadim, Wendisch, Daniel, Michalick, Laura, White, Matthew, Freiwald, Anja, Textoris-Taube, Kathrin, Vernardis, Spyros I., Egger, Anna-Sophia, Kreidl, Marco, Ludwig, Daniela, Kilian, Christiane, Agostini, Federica, Zelezniak, Aleksej, Thibeault, Charlotte, Pfeiffer, Moritz, Hippenstiel, Stefan, Hocke, Andreas, von Kalle, Christof, Campbell, Archie, Hayward, Caroline, Porteous, David J., Marioni, Riccardo E., Langenberg, Claudia, Lilley, Kathryn S., Kuebler, Wolfgang M., Mülleder, Michael, Drosten, Christian, Suttorp, Norbert, Witzenrath, Martin, Kurth, Florian, Sander, Leif Erik, Ralser, Markus

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Expanding functional protein sequence spaces using generative adversarial networks von Repecka, Donatas, Jauniskis, Vykintas, Karpus, Laurynas, Rembeza, Elzbieta, Rokaitis, Irmantas, Zrimec, Jan, Poviloniene, Simona, Laurynenas, Audrius, Viknander, Sandra, Abuajwa, Wissam, Savolainen, Otto, Meskys, Rolandas, Engqvist, Martin K. M., Zelezniak, Aleksej

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The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization von Alam, Mohammad Tauqeer, Olin-Sandoval, Viridiana, Stincone, Anna, Keller, Markus A., Zelezniak, Aleksej, Luisi, Ben F., Ralser, Markus

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Controlling gene expression with deep generative design of regulatory DNA von Zrimec, Jan, Fu, Xiaozhi, Muhammad, Azam Sheikh, Skrekas, Christos, Jauniskis, Vykintas, Speicher, Nora K., Börlin, Christoph S., Verendel, Vilhelm, Chehreghani, Morteza Haghir, Dubhashi, Devdatt, Siewers, Verena, David, Florian, Nielsen, Jens, Zelezniak, Aleksej

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SALARECON connects the Atlantic salmon genome to growth and feed efficiency von Zakhartsev, Maksim, Rotnes, Filip, Gulla, Marie, Øyås, Ove, van Dam, Jesse C J, Suarez-Diez, Maria, Grammes, Fabian, Hafþórsson, Róbert Anton, van Helvoirt, Wout, Koehorst, Jasper J, Schaap, Peter J, Jin, Yang, Mydland, Liv Torunn, Gjuvsland, Arne B, Sandve, Simen R, Martins Dos Santos, Vitor A P, Vik, Jon Olav

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From AI-driven synthetic biology to prediction of molecular phenotypes von Zelezniak, Aleksej

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Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts von Zelezniak, Aleksej, Vowinckel, Jakob, Capuano, Floriana, Messner, Christoph B., Demichev, Vadim, Polowsky, Nicole, Mülleder, Michael, Kamrad, Stephan, Klaus, Bernd, Keller, Markus A., Ralser, Markus

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Learning the Regulatory Code of Gene Expression von Zrimec, Jan, Buric, Filip, Kokina, Mariia, Garcia, Victor, Zelezniak, Aleksej

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Performance of Regression Models as a Function of Experiment Noise von Li, Gang, Zrimec, Jan, Ji, Boyang, Geng, Jun, Larsbrink, Johan, Zelezniak, Aleksej, Nielsen, Jens, Engqvist, Martin KM

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Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells von Saghaleyni, Rasool, Malm, Magdalena, Moruzzi, Noah, Zrimec, Jan, Razavi, Ronia, Wistbacka, Num, Thorell, Hannes, Pintar, Anton, Hober, Andreas, Edfors, Fredrik, Chotteau, Veronique, Berggren, Per-Olof, Grassi, Luigi, Zelezniak, Aleksej, Svensson, Thomas, Hatton, Diane, Nielsen, Jens, Robinson, Jonathan L., Rockberg, Johan

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Metabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes von Zelezniak, Aleksej, Pers, Tune H, Soares, Simão, Patti, Mary Elizabeth, Patil, Kiran Raosaheb

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Assessing the laboratory performance of AI-generated enzymes

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