Author

Mihail Anton

Science for Life LaboratoryORCID 0000-0002-7753-9042Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 4 Research Focus:benchmarking· 2 Approach:experimental assay· 2 Research Focus:gene regulatory network inference· 2 Research Focus:software / tool· 2 Organism:yeast· 2 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Jens NielseniD· 5 shared Eduard Johannes KerkhoveniD· 4 shared Feiran LiiD· 3 shared Lars M. BlankiD· 3 shared Ulf W. LiebaliD· 3 shared Andreas DrägeriD· 2 shared Benjamín J. SáncheziD· 2 shared Costas D. MaranasiD· 2 shared

Activity by Year

2022-2024 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

5 shared papersSystems Biology

Jens NielsenORCID

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models

Karthik Raman, Miroslav Kratochvíl, Brett G. Olivier, Matthias König, Pratyay Sengupta, Dinesh Kumar Kuppa Baskaran, Tung V. N. Nguyen, Daniel Lobo, St. Elmo Wilken, Krishna Kumar Tiwari, Aswathy K. Raghu, Indumathi Palanikumar, Lavanya Raajaraam, Maziya Ibrahim, Sanjaay Balakrishnan, , Rahuman S. Malik‐Sheriff

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

bioRxiv · Sep 24, 2024 · PreprintSystems Biology

Yeast9: A Consensus Yeast Metabolic Model Enables Quantitative Analysis of Cellular Metabolism By Incorporating Big Data

Chengyu Zhang, Benjamín J. Sánchez, Feiran Li, Cheng Wei Quan Eiden, William T. Scott, Ulf W. Liebal, Lars M. Blank, Hendrik G. Mengers, Mihail Anton, Albert Enrique Tafur Rangel, Sebastián N. Mendoza, Lixin Zhang, Jens Nielsen, Hongzhong Lu, Eduard Johannes Kerkhoven

Yeast9 improves yeast metabolic modeling by integrating multi-omics data, showing better prediction of growth rates and gene function than transcriptomics.

bioRxiv · Dec 3, 2023 · PreprintSystems Biology

Standard-GEM supports reproducible development of genome-scale metabolic models

Mihail Anton, Eivind Almaas, Famke Bäuerle, Moritz E. Beber, Rui Benfeitas, Sara Benito-Vaquerizo, Lars M. Blank, Frederick Clasen, Claudia de Buck, Andreas Dräger, John M. Hancock, Vassily Hatzimanikatis A, Matthias König, Dimitra Lappa, Feiran Li, , Eduard Johannes Kerkhoven

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

bioRxiv · Mar 21, 2023 · PreprintSystems Biology

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

Johan Gustafsson, Mihail Anton, Fariba Roshanzamir, Rebecka J. Jörnsten, Eduard Johannes Kerkhoven, Jonathan L. Robinson, Jens Nielsen

The paper develops methods to generate context-specific genome-scale metabolic models from single-cell RNA-Seq data and shows that cell subtypes have unique metabolic profiles.

Proceedings of the National Academy of Sciences · Jan 31, 2023Peer-reviewedSystems Biology

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Iván Domenzain, Benjamín J. Sánchez, Mihail Anton, Eduard Johannes Kerkhoven, Aarón Millán-Oropeza, Céline Henry, Verena Siewers, John P. Morrissey, Nikolaus Sonnenschein, Jens Nielsen

The paper upgrades the GECKO method to create enzyme-constrained models for yeast and human, revealing common metabolic adaptations under stress.

Nature Communications · Jun 30, 2022Peer-reviewedSystems Biology