Jonathan L. Robinson

Brain energy metabolism is optimized to minimize the cost of enzyme synthesis and transport

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

Standard-GEM supports reproducible development of genome-scale metabolic models

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

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.

Transcriptome analysis of EPO and GFP HEK293 Cell-lines Reveal Shifts in Energy and ER Capacity Support Improved Erythropoietin Production in HEK293F Cells

The paper compares transcriptomic profiles of HEK293 cell lines producing erythropoietin or GFP to identify factors associated with improved erythropoietin production.

Addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seq

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.

Machine learning-based investigation of the cancer protein secretory pathway

The paper uses machine learning and differential expression analysis to identify secretory pathway genes associated with cancer characteristics, finding KIF20A and KIF23 as key genes across multiple cancer types.