Dongya Jia

Computational modeling of cancer cell metabolism along the catabolic-anabolic axes

This paper develops a computational model of cancer metabolism integrating catabolic and anabolic pathways, identifying four metabolic phenotypes and their association with patient survival.

Chaotic dynamics for homeostatic hematopoiesis

The paper studies chaotic dynamics in hematopoiesis using mouse data, showing leukocyte fluctuations are chaotic and can transition to oscillations with B cell accumulation.

Drug-tolerant idling melanoma cells exhibit theory-predicted metabolic low-low phenotype

The paper identifies a drug-tolerant metabolic state in melanoma cells that reduces both glycolysis and oxidative phosphorylation, supporting survival but limiting growth.

Testing the Gene Expression Classification of the EMT Spectrum

The paper uses computational methods to classify gene expression profiles into epithelial, hybrid E/M, and mesenchymal categories based on EMT dynamics and scoring metrics.

Towards Decoding the Metabolic Plasticity in Cancer: Coupling of Gene Regulation and Metabolic Pathways

The paper models the coupling of gene regulation and metabolic pathways in cancer, showing AMPK and HIF-1 activity correlates with metabolic pathway activities in tumor samples.

RACIPE: A computational tool for Modeling Gene Regulatory Circuits using Randomization

RACIPE is a computational tool that models gene regulatory circuits by randomizing parameters to identify robust dynamical features without requiring detailed kinetic data.

Interrogating the Topological Robustness of Gene Regulatory Circuits

The paper introduces RACIPE, a computational method to assess the robustness of gene regulatory circuits by analyzing their dynamical behavior under parameter perturbations, showing topology dominates over kinetic parameters.