| Metabolic dependencies drive species co-occurrence in diverse microbial communities A Zelezniak, S Andrejev, O Ponomarova, DR Mende, P Bork, KR Patil Proceedings of the National Academy of Sciences 112 (20), 6449-6454, 2015 | 544 | 2015 |
| Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection CB Messner, V Demichev, D Wendisch, L Michalick, M White, A Freiwald, ... Cell systems 11 (1), 11-24. e4, 2020 | 349 | 2020 |
| Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies M Tramontano, S Andrejev, M Pruteanu, M Klünemann, M Kuhn, ... Nature microbiology 3 (4), 514-522, 2018 | 159 | 2018 |
| Functional metabolomics describes the yeast biosynthetic regulome M Mülleder, E Calvani, MT Alam, RK Wang, F Eckerstorfer, A Zelezniak, ... Cell 167 (2), 553-565. e12, 2016 | 127 | 2016 |
| Expanding functional protein sequence spaces using generative adversarial networks D Repecka, V Jauniskis, L Karpus, E Rembeza, I Rokaitis, J Zrimec, ... Nature Machine Intelligence, 1-10, 2021 | 123 | 2021 |
| Ultra-fast proteomics with Scanning SWATH CB Messner, V Demichev, N Bloomfield, JSL Yu, M White, M Kreidl, ... Nature biotechnology 39 (7), 846-854, 2021 | 109 | 2021 |
| Metabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes A Zelezniak, TH Pers, S Soares, ME Patti, KR Patil PLoS computational biology 6 (4), e1000729, 2010 | 99 | 2010 |
| The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization MT Alam, V Olin-Sandoval, A Stincone, MA Keller, A Zelezniak, BF Luisi, ... Nature communications 8 (1), 16018, 2017 | 98 | 2017 |
| Designing and interpreting ‘multi-omic’experiments that may change our understanding of biology R Haas, A Zelezniak, J Iacovacci, S Kamrad, SJ Townsend, M Ralser Current Opinion in Systems Biology 6, 37-45, 2017 | 89 | 2017 |
| A time-resolved proteomic and prognostic map of COVID-19 V Demichev, P Tober-Lau, O Lemke, T Nazarenko, C Thibeault, ... Cell systems 12 (8), 780-794. e7, 2021 | 80 | 2021 |
| The metabolic background is a global player in Saccharomyces gene expression epistasis MT Alam, A Zelezniak, M Mülleder, P Shliaha, R Schwarz, F Capuano, ... Nature Microbiology 1 (3), 1-10, 2016 | 80 | 2016 |
| Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803 A Montagud, A Zelezniak, E Navarro, PF de Córdoba, JF Urchueguía, ... Biotechnology journal 6 (3), 330-342, 2011 | 80 | 2011 |
| Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes A Zelezniak, S Sheridan, KR Patil PLoS computational biology 10 (4), e1003572, 2014 | 75 | 2014 |
| Machine learning predicts the yeast metabolome from the quantitative proteome of kinase knockouts A Zelezniak, J Vowinckel, F Capuano, CB Messner, V Demichev, ... Cell systems 7 (3), 269-283. e6, 2018 | 73 | 2018 |
| Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition J Vowinckel, A Zelezniak, R Bruderer, M Mülleder, L Reiter, M Ralser Scientific reports 8 (1), 4346, 2018 | 63 | 2018 |
| Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure J Zrimec, CS Börlin, F Buric, AS Muhammad, R Chen, V Siewers, ... Nature communications 11 (1), 1-16, 2020 | 62 | 2020 |
| Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours T Yamada, AS Waller, J Raes, A Zelezniak, N Perchat, A Perret, ... Molecular systems biology 8 (1), 581, 2012 | 42 | 2012 |
| Plastic-degrading potential across the global microbiome correlates with recent pollution trends J Zrimec, M Kokina, S Jonasson, F Zorrilla, A Zelezniak MBio 12 (5), e02155-21, 2021 | 32 | 2021 |
| Bayesian genome scale modelling identifies thermal determinants of yeast metabolism G Li, Y Hu, J Zrimec, H Luo, H Wang, A Zelezniak, B Ji, J Nielsen Nature Communications 12 (1), 190, 2021 | 30 | 2021 |
| metaGEM: reconstruction of genome scale metabolic models directly from metagenomes F Zorrilla, F Buric, KR Patil, A Zelezniak Nucleic acids research 49 (21), e126-e126, 2021 | 25 | 2021 |
Markus RalserCharité Berlin & University of OxfordVerified email at charite.de
