We use deep learning to decipher gene regulatory sequences and protein-DNA interactions, trained on diverse multi-species data. Our accurate models reconstruct gene networks, assess genetic variation impacts, aid GWAS candidate identification, and guide gene editing for expression modulation.

Meetings attendee and report writer with background in computational biology and plant biochemistry.

Evolutionary biologist with affinity to gene regulation and sequence analysis.

Deep learning monk with focus on gene regulation and genetic variation.

Multi-omics specialist and programming wizard with interest in plant stress resistance.

Adept of multi-omics integration and metabolic modelling.

Single cell explorer, gene expression engineer.

Gene regulation designer, deep learning acolyte.

Game designer with affinity to molecular networks and plant-environment interaction.

Aficionado of eGWAS and gene regulatory networks of plant heat stress response.

Investigating the relationship between chromosome structure and gene expression.

Deep learning adept investigating plant promoter activity.

A sprouting talent in machine learning with interest in evolution of plant gene regulation.