Predictive and Accelerated Metabolic Engineering Network (PAcMEN)

Marie Curie-Innovative Training Networks


Duration: 2016-2020

Coordinator: Technical University of Denmark

Lighting up yeast cell factories by transcription factor-based biosensors - Vasil D'ambrosio, Michael K. Jensen

Engineering microbial fatty acid metabolism for biofuels and biochemicals - Eko Roy Marella, Carina Holkenbrink, Varena Siewers, Irina Borodina

pyTFA and matTFA: a Python package and a Matlab toolbox for Thermodynamics-based Flux Analysis - Pierre Salvy, Georgios Fengos, Meric Ataman, Thomas Pathier, Keng C Soh, Vassily Hatzimanikatis

Modular 5′-UTR hexamers for context-independent tuning of protein expression in eukaryotes - Søren D Petersen, Jie Zhang, Jae S Lee, Tadas Jakočiūnas, Lise M Grav, Helene F Kildegaard, Jay D Keasling, Michael K Jensen

Advances in synthetic biology of oleaginous yeast Yarrowia lipolytica for producing non-native chemicals - Farshad Darvishi, Mehdi Ariana, Eko Roy Marella, Irina Borodina

Saccharomyces cerevisiae displays a stable transcription start site landscape in multiple conditions - Christoph S Boerlin, Nevena Cvetesic, Petter Holland, David Bergenholm, Verena Siewers, Boris Lenhard, Jens Nielsen

Genome editing in Kluyveromyces and Ogataea yeasts using a broad-host-range Cas9/gRNA co-expression plasmid - Hannes Juergens, Javier A Varela, Arthur R Gorter de Vries, Thomas Perli, Veronica J M Gast, Nikola Y Gyurchev, Arun S Rajkumar, Robert Mans, Jack T Pronk, Jonh P Morrissey, Jean-Marc G Daran.

Assigning enzyme sequences to orphan and novel reactions using knowledge of substrate reactive sites - Noushin Hadadi, Homa MohamadiPeyhani, Ljubisa Miskovic, Marianne Seijo, Vassily Hatzimanikatis

​​Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima - Gang Li, Kersten S. Rabe, Jens Nielsen and Martin K. M. Engqvist

ETFL: A formulation for flux balance models accounting for expression, thermodynamics, and resource allocation constraints - Pierre Salvy,  Vassily Hatzimanikatis

​​A bioinformatic pipeline to analyze ChIP-exo datasets - Christoph S Börlin, David Bergenholm, Petter Holland, Jens Nielsen


Research training


PAcMEN is a European training network, which offers excellent training in biotech research and innovation for 16 talented young scientists. PhD students will carry out cutting-edge research in metabolic engineering, modeling, systems and synthetic biology. In collaboration with industrial partners, they will create novel solutions for sustainable production of fuels and chemicals. The graduates will be prepared through research, business, and entrepreneurship training to launch their careers in industry or academia. 

Research Projects