Quaid Morris

HERACLES improves lineage reconstruction accuracy and scalability by optimizing cell coordinates in hyperbolic space using a composite likelihood model of CRISPR editing.

This study shows that systemic iron sequestration via hepcidin reduces CD8+ T cells in pancreas cancer, linking iron dysregulation to tumoral immunity.

The paper uses high-content imaging and machine learning to study how perturbing essential genes affects subcellular organization in yeast, revealing cascade effects and a threshold for cell death.

Ordered lineage recording in lung cancer xenografts shows pre-transplant glycolytic and lineage-heritable expression states predict metastatic colonization, while ENO1 alone predicts onward spread.

This study identifies DNA binding motifs for 98 human transcription factors using meSMiLE-seq, revealing methylation-sensitive binding preferences for some TFs.

The paper uses GHT-SELEX to show many human TFs have high intrinsic sequence specificity and complex DNA binding, often matching in vivo ChIP-seq results.

The paper introduces enFoldX, a structure-based method for predicting TCR:pMHC binding using AlphaFold3 ensembles, achieving high accuracy for cognate vs. non-cognate classification.

This paper evaluates generalist large language models (LLMs) in tumor genomic interpretation tasks, finding they can complement or outperform task-specific models in some cases.

Orthrus is a Mamba-based RNA foundation model pre-trained with biological augmentations and contrastive learning, achieving better mRNA property prediction than existing models with less fine-tuning data.

Metient infers cancer type-specific metastatic spread patterns using gradient-based optimization, revealing new insights into metastasis mechanisms and treatment strategies.

The paper evaluates cross-platform DNA motif discovery tools using 4,237 experiments to identify reliable transcription factor binding motifs and highlights challenges in motif detection.

The paper examines how geography, ancestry, age, and sex influence the prevalence of somatic autosomal mosaic chromosomal alterations in blood across diverse populations.

LoPhy reconstructs the joint evolution of SNVs and CNAs from longitudinal single-cell data, revealing their roles in AML progression and therapy resistance.

This study uses spatial omics to identify distinct tumor microenvironment profiles in Black and White American TNBC patients, linking them to different immunosuppressive mechanisms and clinical outcomes.

mRNABench evaluates self-supervised mRNA foundation models using 13 datasets and 81 tasks to assess their ability to predict mRNA properties.

The paper introduces DAMUTA, a model that distinguishes DNA damage and misrepair processes in mutational signatures, showing improved resolution over existing methods in pan-cancer analysis.

This study identifies At-RS31 as a plant-specific splicing factor that regulates alternative splicing and integrates TOR and ABA signaling pathways through its binding targets and interactions with other splicing factors.

The paper introduces a dynamic clustering approach for genomics cohorts based on trait-specific genomic signals, revealing patterns beyond predefined racial or continental categories.

The paper identifies genomic binding sites of 166 poorly characterized human transcription factors, revealing that some bind to dark matter DNA and others to regulatory regions.

The paper systematically determines the sequence specificity of 332 poorly characterized human transcription factors, identifying over 4,000 experiments and revealing tens of thousands of new TF binding sites.

The paper introduces EuPRI, a resource of RNA motifs for 34,736 RBPs across 690 eukaryotes, expanding motif knowledge and enabling functional and evolutionary insights.

The paper investigates the evolution of chromosome 4p loss in basal breast cancer, identifying C4orf19 as a novel gene that suppresses proliferation and is part of a kinase module.

The paper develops viRNAtrap, a deep learning-based pipeline to identify and characterize viral expression in cancer, revealing new viruses and endogenous viruses linked to poor survival.

The paper benchmarks 31 subclonal reconstruction algorithms on simulated tumours, finding that algorithm choice significantly impacts performance and no single algorithm excels across all tasks.

Pairtree reconstructs clone trees from multiple bulk DNA samples to infer cancer evolutionary histories with higher accuracy and scalability.

This paper introduces SubMARine, a polynomial-time algorithm for reconstructing tumor clone trees that efficiently captures uncertainty and scales to large datasets.

The paper identifies binding specificities of human RNA-binding proteins using HTR-SELEX, revealing that 70% bind linear sequences and 30% bind structured motifs, with novel roles for ZC3H12A/B/C in viral transcript degradation.

This study identifies RIN/G3BP-bound mRNAs in Drosophila and shows they are short, stable, and highly translated, suggesting RIN stabilizes and enhances their translation.

This study develops quantitative metrics and simulated datasets to evaluate subclonal reconstruction methods in tumours.

TrackSig estimates mutation evolutionary trajectories from bulk tumor sequencing data, showing improved accuracy in detecting subclonal populations and signature activity changes compared to baseline methods.