An analytical theory of balanced cellular growth

por Hugo Dourado, Martin J. Lercher
Publicado 2020

Modeling photosynthetic resource allocation connects physiology with evolutionary environments

por Esther M. Sundermann, Martin J. Lercher, David Heckmann
Publicado 2021

Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast

por Deya Alzoubi, Abdelmoneim Amer Desouki, Martin J. Lercher
Publicado 2019

On the optimality of the enzyme-substrate relationship in bacteria.

por Hugo Dourado, Matteo Mori, Terence Hwa, Martin J Lercher
Publicado 2021

On the optimality of the enzyme–substrate relationship in bacteria

por Hugo Dourado, Matteo Mori, Terence Hwa, Martin J. Lercher
Publicado 2021

Deep learning allows genome-scale prediction of Michaelis constants from structural features.

por Alexander Kroll, Martin K M Engqvist, David Heckmann, Martin J Lercher
Publicado 2021

Energy efficiency trade-offs drive nucleotide usage in transcribed regions

por Wei-Hua Chen, Guanting Lu, Peer Bork, Songnian Hu, Martin J. Lercher
Publicado 2016

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

por David Heckmann, Colton J. Lloyd, Nathan Mih, Yuanchi Ha, Daniel C. Zielinski, Zachary B. Haiman, Abdelmoneim Amer Desouki, Martin J. Lercher, Bernhard O. Palsson
Publicado 2018

Adaptive evolution of complex innovations through stepwise metabolic niche expansion

por Balázs Szappanos, Jonathan Fritzemeier, Bálint Csörgő, Viktória Lázár, Xiaowen Lu, Gergely Fekete, Balázs Bálint, Róbert Herczeg, István Nagy, Richard A. Notebaart, Martin J. Lercher, Csaba Pál, Balázs Papp
Publicado 2016