Johan Henriksson

The paper analyzes the biosynthetic potential of the Bacillus cereus group using genomic data, identifying many novel biosynthetic gene clusters.

Sismis is a machine learning tool that accurately detects and classifies secretion systems in bacterial (meta)genomes, identifying many previously unknown systems.

This paper introduces Bascet and Zorn, tools for scalable single-cell metagenomic analysis, demonstrating their utility on mock and human saliva samples.

The paper develops a scalable CRISPR-Cas9 system for Plasmodium berghei to enable genome-wide knockout screens.

CRISPR-MIP replaces PCR for sgRNA quantification, revealing GC and oversampling biases in pooled CRISPR screens.

The paper identifies a JUNB+ epigenetic state in CD4 T cells associated with proliferation, exhaustion, and memory formation, and develops a new machine learning tool to analyze its regulation.

The paper develops BTyperDB, a global atlas of Bacillus cereus sensu lato genomes, to improve pathogen surveillance and identify emerging lineages.

The paper shows that neuronal activity and stress during a critical period regulate olfactory receptor expression in Drosophila by modulating gene regulatory mechanisms.

The paper profiles single-cell transcriptomes from the human first trimester fetal-maternal interface, revealing cellular composition and interactions critical for placentation.

FACSanadu provides an open-source tool for visualizing and quantifying flow cytometry data, supporting length profile data from the COPAS Biosorter.