Intelligent Systems and Synthetic Biology Lab SynthBiolLab

Research

Full up to date-list of publications is available on Google Scholar.

Highlighted

Expanding functional protein sequence spaces using generative adversarial networks
Expanding functional protein sequence spaces using generative adversarial networks
Donatas Repecka, Vykintas Jauniskis, Laurynas Karpus, Elzbieta Rembeza, Irmantas Rokaitis, ..., Wissam Abuajwa, Otto Savolainen, Rolandas Meskys, Martin K. M. Engqvist, Aleksej Zelezniak
Nature Machine Intelligence   ·   04 Mar 2021   ·   doi:10.1038/s42256-021-00310-5
Controlling gene expression with deep generative design of regulatory DNA
Controlling gene expression with deep generative design of regulatory DNA
Jan Zrimec, Xiaozhi Fu, Azam Sheikh Muhammad, Christos Skrekas, Vykintas Jauniskis, ..., Devdatt Dubhashi, Verena Siewers, Florian David, Jens Nielsen, Aleksej Zelezniak
Nature Communications   ·   30 Aug 2022   ·   doi:10.1038/s41467-022-32818-8
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Jan Zrimec, Christoph S. Börlin, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Verena Siewers, Vilhelm Verendel, Jens Nielsen, Mats Töpel, Aleksej Zelezniak
Nature Communications   ·   01 Dec 2020   ·   doi:10.1038/s41467-020-19921-4
Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends
Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends
Jan Zrimec, Mariia Kokina, Sara Jonasson, Francisco Zorrilla, Aleksej Zelezniak
mBio   ·   26 Oct 2021   ·   doi:10.1128/mbio.02155-21

All

2023

The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost
The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost
Filip Buric, Sandra Viknander, Xiaozhi Fu, Oliver Lemke, Jan Zrimec, Lukasz Szyrwiel, Michael Mueleder, Markus Ralser, Aleksej Zelezniak
Cold Spring Harbor Laboratory   ·   04 Oct 2023   ·   doi:10.1101/2023.10.02.560091
Synthesis of Metal–Organic Frameworks through Enzymatically Recycled Polyethylene Terephthalate
Synthesis of Metal–Organic Frameworks through Enzymatically Recycled Polyethylene Terephthalate
Zhejian Cao, Xiaozhi Fu, Hao Li, Santosh Pandit, Francoise M. Amombo Noa, Lars Öhrström, Aleksej Zelezniak, Ivan Mijakovic
ACS Sustainable Chemistry & Engineering   ·   21 Sep 2023   ·   doi:10.1021/acssuschemeng.3c05222
Computational Scoring and Experimental Evaluation of Enzymes Generated by Neural Networks
Computational Scoring and Experimental Evaluation of Enzymes Generated by Neural Networks
Sean R. Johnson, Xiaozhi Fu, Sandra Viknander, Clara Goldin, Sarah Monaco, Aleksej Zelezniak, Kevin K. Yang
Cold Spring Harbor Laboratory   ·   04 Mar 2023   ·   doi:10.1101/2023.03.04.531015
The Impact of Acute Nutritional Interventions on the Plasma Proteome
The Impact of Acute Nutritional Interventions on the Plasma Proteome
Spyros I Vernardis, Vadim Demichev, Oliver Lemke, Nana-Maria Grüning, Christoph Messner, ..., Aleksej Zelezniak, Nicholas J Wareham, Claudia Langenberg, I Sadaf Farooqi, Markus Ralser
The Journal of Clinical Endocrinology & Metabolism   ·   20 Jan 2023   ·   doi:10.1210/clinem/dgad031
Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan
Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan
Clara Correia-Melo, Stephan Kamrad, Roland Tengölics, Christoph B. Messner, Pauline Trebulle, ..., Vadim Demichev, Michael Mülleder, Balázs Papp, Mohammad Tauqeer Alam, Markus Ralser
Cell   ·   01 Jan 2023   ·   doi:10.1016/j.cell.2022.12.007

2022

Toward learning the principles of plant gene regulation
Toward learning the principles of plant gene regulation
Jan Zrimec, Aleksej Zelezniak, Kristina Gruden
Trends in Plant Science   ·   01 Dec 2022   ·   doi:10.1016/j.tplants.2022.08.010
Learning deep representations of enzyme thermal adaptation
Learning deep representations of enzyme thermal adaptation
Gang Li, Filip Buric, Jan Zrimec, Sandra Viknander, Jens Nielsen, Aleksej Zelezniak, Martin K. M. Engqvist
Protein Science   ·   22 Nov 2022   ·   doi:10.1002/pro.4480
Controlling gene expression with deep generative design of regulatory DNA
Controlling gene expression with deep generative design of regulatory DNA
Jan Zrimec, Xiaozhi Fu, Azam Sheikh Muhammad, Christos Skrekas, Vykintas Jauniskis, ..., Devdatt Dubhashi, Verena Siewers, Florian David, Jens Nielsen, Aleksej Zelezniak
Nature Communications   ·   30 Aug 2022   ·   doi:10.1038/s41467-022-32818-8
Data mining of Saccharomyces cerevisiae mutants engineered for increased tolerance towards inhibitors in lignocellulosic hydrolysates
Data mining of Saccharomyces cerevisiae mutants engineered for increased tolerance towards inhibitors in lignocellulosic hydrolysates
Elena Cámara, Lisbeth Olsson, Jan Zrimec, Aleksej Zelezniak, Cecilia Geijer, Yvonne Nygård
Biotechnology Advances   ·   01 Jul 2022   ·   doi:10.1016/j.biotechadv.2022.107947
Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells
Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells
Rasool Saghaleyni, Magdalena Malm, Noah Moruzzi, Jan Zrimec, Ronia Razavi, ..., Thomas Svensson, Diane Hatton, Jens Nielsen, Jonathan L. Robinson, Johan Rockberg
Cell Reports   ·   01 Jun 2022   ·   doi:10.1016/j.celrep.2022.110936
A proteomic survival predictor for COVID-19 patients in intensive care
A proteomic survival predictor for COVID-19 patients in intensive care
Vadim Demichev, Pinkus Tober-Lau, Tatiana Nazarenko, Oliver Lemke, Simran Kaur Aulakh, ..., Kathryn Lilley, Michael Mülleder, Leif Erik Sander, Florian Kurth, Markus Ralser
PLOS Digital Health   ·   18 Jan 2022   ·   doi:10.1371/journal.pdig.0000007

2021

Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends
Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends
Jan Zrimec, Mariia Kokina, Sara Jonasson, Francisco Zorrilla, Aleksej Zelezniak
mBio   ·   26 Oct 2021   ·   doi:10.1128/mbio.02155-21
metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Francisco Zorrilla, Filip Buric, Kiran R Patil, Aleksej Zelezniak
Nucleic Acids Research   ·   06 Oct 2021   ·   doi:10.1093/nar/gkab815
A time-resolved proteomic and prognostic map of COVID-19
A time-resolved proteomic and prognostic map of COVID-19
Vadim Demichev, Pinkus Tober-Lau, Oliver Lemke, Tatiana Nazarenko, Charlotte Thibeault, ..., Denise Treue, Michael Hummel, Victor M. Corman, Christian Drosten, Christof von Kalle
Cell Systems   ·   01 Aug 2021   ·   doi:10.1016/j.cels.2021.05.005
Potential for improved retention rate by personalized antiseizure medication selection: A register‐based analysis
Potential for improved retention rate by personalized antiseizure medication selection: A register‐based analysis
Samuel Håkansson, Markus Karlander, David Larsson, Zamzam Mahamud, Sara Garcia‐Ptacek, Aleksej Zelezniak, Johan Zelano
Epilepsia   ·   09 Jul 2021   ·   doi:10.1111/epi.16987
Learning the Regulatory Code of Gene Expression
Learning the Regulatory Code of Gene Expression
Jan Zrimec, Filip Buric, Mariia Kokina, Victor Garcia, Aleksej Zelezniak
Frontiers in Molecular Biosciences   ·   10 Jun 2021   ·   doi:10.3389/fmolb.2021.673363
Ultra-fast proteomics with Scanning SWATH
Ultra-fast proteomics with Scanning SWATH
Christoph B. Messner, Vadim Demichev, Nic Bloomfield, Jason S. L. Yu, Matthew White, ..., Florian Kurth, Kathryn S. Lilley, Michael Mülleder, Stephen Tate, Markus Ralser
Nature Biotechnology   ·   25 Mar 2021   ·   doi:10.1038/s41587-021-00860-4
Expanding functional protein sequence spaces using generative adversarial networks
Expanding functional protein sequence spaces using generative adversarial networks
Donatas Repecka, Vykintas Jauniskis, Laurynas Karpus, Elzbieta Rembeza, Irmantas Rokaitis, ..., Wissam Abuajwa, Otto Savolainen, Rolandas Meskys, Martin K. M. Engqvist, Aleksej Zelezniak
Nature Machine Intelligence   ·   04 Mar 2021   ·   doi:10.1038/s42256-021-00310-5
Benchmarking accuracy and precision of intensity‐based absolute quantification of protein abundances in <i>Saccharomyces cerevisiae</i>
Benchmarking accuracy and precision of intensity‐based absolute quantification of protein abundances in Saccharomyces cerevisiae
Benjamín J. Sánchez, Petri‐Jaan Lahtvee, Kate Campbell, Sergo Kasvandik, Rosemary Yu, Iván Domenzain, Aleksej Zelezniak, Jens Nielsen
PROTEOMICS   ·   23 Feb 2021   ·   doi:10.1002/pmic.202000093
Bayesian genome scale modelling identifies thermal determinants of yeast metabolism
Bayesian genome scale modelling identifies thermal determinants of yeast metabolism
Gang Li, Yating Hu, Jan Zrimec, Hao Luo, Hao Wang, Aleksej Zelezniak, Boyang Ji, Jens Nielsen
Nature Communications   ·   08 Jan 2021   ·   doi:10.1038/s41467-020-20338-2

2020

Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra
Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra
Filip Buric, Jan Zrimec, Aleksej Zelezniak
Patterns   ·   01 Dec 2020   ·   doi:10.1016/j.patter.2020.100137
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Jan Zrimec, Christoph S. Börlin, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Verena Siewers, Vilhelm Verendel, Jens Nielsen, Mats Töpel, Aleksej Zelezniak
Nature Communications   ·   01 Dec 2020   ·   doi:10.1038/s41467-020-19921-4
Transcriptome analysis of EPO and GFP HEK293 Cell-lines Reveal Shifts in Energy and ER Capacity Support Improved Erythropoietin Production in HEK293F Cells
Transcriptome analysis of EPO and GFP HEK293 Cell-lines Reveal Shifts in Energy and ER Capacity Support Improved Erythropoietin Production in HEK293F Cells
Rasool Saghaleyni, Magdalena Malm, Jan Zrimec, Ronia Razavi, Num Wistbacka, ..., Aleksej Zelezniak, Thomas Svensson, Jens Nielsen, Jonathan L. Robinson, Johan Rockberg
Cold Spring Harbor Laboratory   ·   16 Sep 2020   ·   doi:10.1101/2020.09.16.299966
Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection
Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection
Christoph B. Messner, Vadim Demichev, Daniel Wendisch, Laura Michalick, Matthew White, ..., Norbert Suttorp, Martin Witzenrath, Florian Kurth, Leif Erik Sander, Markus Ralser
Cell Systems   ·   01 Jul 2020   ·   doi:10.1016/j.cels.2020.05.012
Parallel factor analysis enables quantification and identification of highly-convolved data independent-acquired protein spectra
Parallel factor analysis enables quantification and identification of highly-convolved data independent-acquired protein spectra
Filip Buric, Jan Zrimec, Aleksej Zelezniak
Cold Spring Harbor Laboratory   ·   23 Apr 2020   ·   doi:10.1101/2020.04.21.052654
Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in <i>Saccharomyces cerevisiae</i>
Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae
Benjamín J. Sánchez, Petri-Jaan Lahtvee, Kate Campbell, Sergo Kasvandik, Rosemary Yu, Iván Domenzain, Aleksej Zelezniak, Jens Nielsen
Cold Spring Harbor Laboratory   ·   24 Mar 2020   ·   doi:10.1101/2020.03.23.998237

2018

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts
Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts
Aleksej Zelezniak, Jakob Vowinckel, Floriana Capuano, Christoph B. Messner, Vadim Demichev, ..., Michael Mülleder, Stephan Kamrad, Bernd Klaus, Markus A. Keller, Markus Ralser
Cell Systems   ·   01 Sep 2018   ·   doi:10.1016/j.cels.2018.08.001
Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies
Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies
Melanie Tramontano, Sergej Andrejev, Mihaela Pruteanu, Martina Klünemann, Michael Kuhn, ..., Aleksej Zelezniak, Georg Zeller, Peer Bork, Athanasios Typas, Kiran Raosaheb Patil
Nature Microbiology   ·   19 Mar 2018   ·   doi:10.1038/s41564-018-0123-9
Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition
Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition
Jakob Vowinckel, Aleksej Zelezniak, Roland Bruderer, Michael Mülleder, Lukas Reiter, Markus Ralser
Scientific Reports   ·   12 Mar 2018   ·   doi:10.1038/s41598-018-22610-4
The Response to Past Climate Perturbations Explains Extremely Low Genetic Diversity in the Genome of an Abundant Ice-Age Remnant, the Alpine Marmot
The Response to Past Climate Perturbations Explains Extremely Low Genetic Diversity in the Genome of an Abundant Ice-Age Remnant, the Alpine Marmot
Toni I. Gossmann​, Achchuthan Shanmugasundram​, Stefan Börno, Ludovic Duvaux, Christophe Lemaire​, ..., Dominique Allaine, Aurelie Cohas, John J. Welch, Bernd Timmermann​, Markus Ralser
SSRN Electronic Journal   ·   01 Jan 2018   ·   doi:10.2139/ssrn.3219259

2017

The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization
The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization
Mohammad Tauqeer Alam, Viridiana Olin-Sandoval, Anna Stincone, Markus A. Keller, Aleksej Zelezniak, Ben F. Luisi, Markus Ralser
Nature Communications   ·   10 Jul 2017   ·   doi:10.1038/ncomms16018

2016

Functional Metabolomics Describes the Yeast Biosynthetic Regulome
Functional Metabolomics Describes the Yeast Biosynthetic Regulome
Michael Mülleder, Enrica Calvani, Mohammad Tauqeer Alam, Richard Kangda Wang, Florian Eckerstorfer, Aleksej Zelezniak, Markus Ralser
Cell   ·   01 Oct 2016   ·   doi:10.1016/j.cell.2016.09.007
Precise label-free quantitative proteomes in high-throughput by microLC and data-independent SWATH acquisition
Precise label-free quantitative proteomes in high-throughput by microLC and data-independent SWATH acquisition
Jakob Vowinckel, Aleksej Zelezniak, Artur Kibler, Roland Bruderer, Michael Muelleder, Lukas Reiter, Markus Ralser
Cold Spring Harbor Laboratory   ·   05 Sep 2016   ·   doi:10.1101/073478
The metabolic background is a global player in Saccharomyces gene expression epistasis
The metabolic background is a global player in Saccharomyces gene expression epistasis
Mohammad Tauqeer Alam, Aleksej Zelezniak, Michael Mülleder, Pavel Shliaha, Roland Schwarz, ..., Stefan Christen, Kiran Raosaheb Patil, Bernd Timmermann, Kathryn S. Lilley, Markus Ralser
Nature Microbiology   ·   01 Feb 2016   ·   doi:10.1038/nmicrobiol.2015.30

2015

Metabolic dependencies drive species co-occurrence in diverse microbial communities
Metabolic dependencies drive species co-occurrence in diverse microbial communities
Aleksej Zelezniak, Sergej Andrejev, Olga Ponomarova, Daniel R. Mende, Peer Bork, Kiran Raosaheb Patil
Proceedings of the National Academy of Sciences   ·   04 May 2015   ·   doi:10.1073/pnas.1421834112

2014

Contribution of Network Connectivity in Determining the Relationship between Gene Expression and Metabolite Concentration Changes
Contribution of Network Connectivity in Determining the Relationship between Gene Expression and Metabolite Concentration Changes
Aleksej Zelezniak, Steven Sheridan, Kiran Raosaheb Patil
PLoS Computational Biology   ·   24 Apr 2014   ·   doi:10.1371/journal.pcbi.1003572

2012

Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours
Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours
Takuji Yamada, Alison S Waller, Jeroen Raes, Aleksej Zelezniak, Nadia Perchat, Alain Perret, Marcel Salanoubat, Kiran R Patil, Jean Weissenbach, Peer Bork
Molecular Systems Biology   ·   01 Jan 2012   ·   doi:10.1038/msb.2012.13

2011

Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium <i>Synechocystis</i> sp. PCC6803
Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803
Arnau Montagud, Aleksej Zelezniak, Emilio Navarro, Pedro Fernández de Córdoba, Javier F. Urchueguía, Kiran Raosaheb Patil
Biotechnology Journal   ·   11 Jan 2011   ·   doi:10.1002/biot.201000109

2010

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes
Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes
Aleksej Zelezniak, Tune H. Pers, Simão Soares, Mary Elizabeth Patti, Kiran Raosaheb Patil
PLoS Computational Biology   ·   01 Apr 2010   ·   doi:10.1371/journal.pcbi.1000729