Johan Gustafsson

The paper describes using kallisto, bustools, and kb-python to quantify RNA-seq data from bulk, single-cell, and single-nucleus samples.

The paper uses metabolic models to show brain energy metabolism minimizes enzyme synthesis and transport costs, supporting the astrocyte-neuron lactate shuttle theory.

The paper develops methods to generate context-specific genome-scale metabolic models from single-cell RNA-Seq data and shows that cell subtypes have unique metabolic profiles.

The paper introduces a method to address amplification bias in single-cell RNA-seq using unique molecular identifiers, showing it can correct gene abundance estimates in cases of pooled amplification paradox.