Dilan Pathirana

PEtab Select provides a standardized format and software for automated model selection in systems biology, supporting diverse modeling frameworks and enabling efficient evaluation of large model spaces.

The paper develops a mathematical model of the canonical AhR pathway to identify which biochemical steps drive ligand-specific transcriptional responses using qPCR data from mouse macrophages.

The paper introduces a data-driven framework to predict collective synaptic plasticity outcomes by considering protein allocation and spatial competition among synapses.

This paper develops a mathematical model of oncolytic virus therapy in zebrafish to capture tumor dynamics and inform future cancer treatments.

The paper identifies a subset of CD8+ TILs in HPV-HNSCC enriched for interferon-stimulated genes that are transcriptionally inert to TCR stimulation and may hinder T-cell differentiation.

The paper introduces a new adjoint method for computing gradients in ODE models of biochemical reaction networks using steady-state data, achieving up to 4.4x speedup in simulation time for large-scale models.

This paper applies mini-batch optimization to ODE models, improving efficiency and results on a cancer signaling dataset.