Benjamin A. Hall

The paper generates organoid models of Barrett oesophagus and oesophageal adenocarcinoma to study disease progression and therapy response.

This study models B-cell differentiation and leukaemogenesis using a logical framework to show how mutation timing and order affect disease progression in BCP-ALL.

OmniPath integrates molecular knowledge from 168 resources to support multi-omics analysis, offering curated data, predictions, and tools for causal modeling across bulk, single-cell, and spatial data.

This study validates folding energy estimates for variant interpretation, showing that while correlation coefficients are low, the method can improve prediction accuracy by identifying and addressing outlier residues.

The paper characterizes Tet2-mutant HSCs using multi-omic data and identifies ECM molecules as regulators of self-renewal in pre-leukemic HSCs.

The paper shows that prior NOTCH1 mutation in aging esophageal epithelium alters the selection of subsequent somatic mutations, increasing NOTCH2 mutants and decreasing TP53 mutants.

This study develops a computational framework to model M1 and M2 macrophages in RA, identifying potential therapeutic targets through Boolean modeling and gene expression validation.

The paper shows that p53 and DN_Maml1 mutations have different clonal fitness responses to cell crowding in epithelial tissues, consistent with mutation distributions in human datasets.

The paper compares methods for analysing lineage tracing datasets and recommends an approximate Bayesian computation approach for parameter estimation.

The paper introduces a library of discrete target functions for cell signalling models using BioModelAnalyzer, showing they can predict genetic perturbations with limited data.