Aly Azeem Khan

The paper analyzes the impact of CYP2C19 genotype on SSRI side effects and discontinuation rates in a large sample of individuals.

This paper introduces Sprox-seq, a multi-omic technique that maps protein interactions and mRNA in human germinal centers, revealing distinct B cell maturation pathways and spatially-enriched immune regulatory complexes.

This study uses a CRISPR screen and AI to identify new drug targets for psoriasis, finding ALOX5 and OXTR as promising candidates with validated therapeutic effects.

The paper argues that scaling model capacity alone is insufficient for Virtual Cells, emphasizing the need for contextual diversity and causal representation learning over data volume.

DecoderTCR improves TCR-pMHC interaction prediction using pretraining and entropy-guided decoding, achieving high AUROC scores without epitope-specific training.

This study uses a multivariate GWAS approach to identify genetic loci associated with reading ability and dyslexia, finding 35 new genome-wide significant loci and estimating SNP heritability at 24%.

PRSformer predicts disease risk from large-scale genotypes using deep learning, outperforming linear models and summary-statistic methods in multi-ancestry cohorts.

This study shows large language models can accurately prioritize causal genes at GWAS loci, outperforming existing methods and offering a scalable solution.

The paper introduces a physical model and improved analysis methods for quantifying protein complexes from Prox-seq data, enhancing accuracy and robustness.

ATAT automates spatial transcriptomics analysis by aligning and traversing tissue samples using self-supervised learning, improving gene expression modeling without manual annotation.

SpinAdapt is an unsupervised RNA correction algorithm that enables transfer of molecular models between labs without requiring patient-level data, improving reproducibility and privacy.

FiberAI automates DNA-fiber analysis in microscopy images, achieving high accuracy in detection and segmentation, and enables efficient measurement of replication checkpoint integrity.

Pseudocell Tracer infers cellular trajectories from scRNA-seq data by simulating pseudocells in a virtual cell-state axis, revealing transcription factor dynamics during B cell immunoglobulin class switch recombination.