Martin J. Lercher

About Martin J. Lercher

Martin J. Lercher, With an exceptional h-index of 50 and a recent h-index of 35 (since 2020), a distinguished researcher at Heinrich-Heine-Universität Düsseldorf, specializes in the field of Models of cellular growth, Evolutionary systems biology.

His recent articles reflect a diverse array of research interests and contributions to the field:

It takes two to think

Sugar transporters spatially organize microbiota colonization along the longitudinal root axis of Arabidopsis

Machine learning models for the prediction of enzyme properties should be tested on proteins not used for model training

Optimal density of bacterial cells

A general prediction model for substrates of transport proteins

Mathematical properties of optimal fluxes in cellular reaction networks at balanced growth

Thinking about science

Nearly half of all bacterial gene families are biased toward specific chromosomal positions

Martin J. Lercher Information

University

Position

Professor of Computational Cell Biology

Citations(all)

13305

Citations(since 2020)

5071

Cited By

10119

hIndex(all)

50

hIndex(since 2020)

35

i10Index(all)

100

i10Index(since 2020)

69

Email

University Profile Page

Heinrich-Heine-Universität Düsseldorf

Google Scholar

View Google Scholar Profile

Martin J. Lercher Skills & Research Interests

Models of cellular growth

Evolutionary systems biology

Top articles of Martin J. Lercher

Title

Journal

Author(s)

Publication Date

It takes two to think

Nature Biotechnology

Itai Yanai

Martin J Lercher

2024/1/8

Sugar transporters spatially organize microbiota colonization along the longitudinal root axis of Arabidopsis

Cell Host & Microbe

Eliza P-I Loo

Paloma Durán

Tin Yau Pang

Philipp Westhoff

Chen Deng

...

2024/4/10

Machine learning models for the prediction of enzyme properties should be tested on proteins not used for model training

bioRxiv

Alexander Kroll

Martin J Lercher

2023/2/7

Optimal density of bacterial cells

PLOS Computational Biology

Tin Yau Pang

Martin J Lercher

2023/6/12

A general prediction model for substrates of transport proteins

bioRxiv

Alexander Kroll

Nico Niebuhr

Gregory Butler

Martin J Lercher

2023

Mathematical properties of optimal fluxes in cellular reaction networks at balanced growth

PLOS Computational Biology

Hugo Dourado

Wolfram Liebermeister

Oliver Ebenhöh

Martin J Lercher

2023/6/6

Thinking about science

Science

Itai Yanai

Martin J Lercher

2023/11/10

Nearly half of all bacterial gene families are biased toward specific chromosomal positions

bioRxiv

Xiao-Pan Hu

Martin J Lercher

2023

A general model to predict small molecule substrates of enzymes based on machine and deep learning

Nature communications

Alexander Kroll

Sahasra Ranjan

Martin KM Engqvist

Martin J Lercher

2023/5/15

Drug-target interaction prediction using a multi-modal transformer network demonstrates high generalizability to unseen proteins

bioRxiv

Alexander Kroll

Sahasra Ranjan

Martin J Lercher

2023/8/22

Metabolic complexity increases adaptability

bioRxiv

Claus Jonathan Fritzemeier

Sajjad Ghaffarinasab

Felix Lieder

Balazs Szappanos

Florian Jarre

...

2023

Growth balance analysis models of cyanobacteria for understanding resource allocation strategies

bioRxiv

Sajjad Ghaffarinasab

Martin J Lercher

Hugo Dourado

2023/4/18

A multimodal Transformer Network for protein-small molecule interactions enhances drug-target affinity and enzyme-substrate predictions

A Kroll

S Ranjan

MJ Lercher

2023/8/22

Make science disruptive again

Nature Biotechnology

Itai Yanai

Martin J Lercher

2023/4

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning

Nature Communications

Alexander Kroll

Yvan Rousset

Xiao-Pan Hu

Nina A Liebrand

Martin J Lercher

2023/7/12

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow

bioRxiv

Xiao-Pan Hu

Stefan Schroeder

Martin J Lercher

2022/11/15

Growth Mechanics: General principles of optimal cellular resource allocation in balanced growth

bioRxiv

Hugo Dourado

Wolfram Liebermeister

Oliver Ebenhöh

Martin J Lercher

2022/10/28

Growth‐mediated negative feedback shapes quantitative antibiotic response

Molecular systems biology

S Andreas Angermayr

Tin Yau Pang

Guillaume Chevereau

Karin Mitosch

Martin J Lercher

...

2022/9

What puzzle are you in?

Genome Biology

Itai Yanai

Martin J Lercher

2022/8/25

The substrate scopes of enzymes: a general prediction model based on machine and deep learning

bioRxiv

Alexander Kroll

Sahasra Ranjan

Martin KM Engqvist

Martin J Lercher

2022/5/25

See List of Professors in Martin J. Lercher University(Heinrich-Heine-Universität Düsseldorf)

Co-Authors

H-index: 86
Laurence D Hurst

Laurence D Hurst

University of Bath

H-index: 85
Andreas P.M. Weber

Andreas P.M. Weber

Heinrich-Heine-Universität Düsseldorf

H-index: 82
Christian von Mering

Christian von Mering

Universität Zürich

H-index: 62
Peter Westhoff

Peter Westhoff

Heinrich-Heine-Universität Düsseldorf

H-index: 46
Itai Yanai

Itai Yanai

New York University

H-index: 41
Veronica G. Maurino

Veronica G. Maurino

Rheinische Friedrich-Wilhelms-Universität Bonn

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