Vicky Yao

A network of bZIP transcription factors and inhibitors enforces differentially proliferative and cytotoxic states in T cells

This study identifies bZIP transcription factors and inhibitors that influence T-cell proliferation and cytotoxicity under exhaustion conditions.

Reference-guided pseudotime inference across species and biological contexts

Cavebear improves pseudotime inference by using reference species time-series data to guide ordering of cells in query species or conditions without time labels.

MONTE enables unified pan-cancer tumor purity estimation andmethylation correction from bulk DNA methylation arrays

MONTE provides a unified framework for tumor purity estimation and methylation correction from bulk DNA methylation data, improving accuracy and generalizability across cancer types.

Alternative splicing reshapes protein interaction networks through structured, directional rewiring across cancers

The paper analyzes alternative splicing's impact on protein interaction networks across cancers, identifying structured rewiring patterns and their association with patient survival.

Ontology-aware DNA methylation classification with a curated atlas ofhuman tissues and cell types

The paper introduces an ontology-aware classification framework for DNA methylation data using a curated atlas of healthy human tissues and cell types, identifying CpG sites that accurately classify tissues and cell types.

ARUNA: Slice-based self-supervised imputation for upscaling DNA methylation sequencing assays

Aruna upscales sparse DNA methylation data from RRBS to whole-genome resolution using a self-supervised denoising autoencoder, outperforming existing methods in simulations and real data.

Interpretable phenotype decoding from multi-condition sequencing data with ALPINE

ALPINE is a supervised NMF framework that disentangles technical and phenotypic factors in multi-condition sequencing data, improving condition-specific signal isolation and interpretability.

Benchmarking gene embeddings from sequence, expression, network, and text models for functional prediction tasks

This study benchmarks 38 gene embedding methods across three functional prediction tasks, finding literature-based embeddings perform best overall, while sequence-based models excel in genetic interactions.

Disentangling associations between complex traits and cell types with seismic

Seismic identifies cell-type-specific associations with complex traits by integrating scRNA-seq and GWAS, revealing trait-relevant cell groups and gene drivers.

Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer

Splitpea quantifies changes in protein interaction networks due to alternative splicing in cancer by analyzing domain-domain interactions and differential exon usage data from TCGA and GTEx.

ANDES: a novel best-match approach for enhancing gene set analysis in embedding spaces

ANDES enhances gene set analysis in embedding spaces by comparing gene sets and achieving state-of-the-art performance in enrichment analysis.

Joint embedding of biological networks for cross-species functional alignment

This paper introduces ETNA, a joint embedding method for cross-species functional alignment using biological networks and sequence orthologs, showing improved preservation of gene functional relationships.

The proto-oncogene DEK regulates neuronal excitability and tau accumulation in Alzheimer's disease vulnerable neurons

The paper identifies DEK as a driver of tau pathology in Alzheimer's disease vulnerable neurons using in silico modeling and experimental validation.

Neuron-Glia Signaling Regulates the Onset of the Antidepressant Response

This study identifies neuron-glia signaling mechanisms underlying the delayed antidepressant response to SSRIs in mice using single-cell sequencing.

Selective neuronal vulnerability in Alzheimer’s disease: a network-based analysis

This study identifies a functional gene module associated with selective neuronal vulnerability in Alzheimer’s disease using integrated molecular and genetic data from mice and humans.

Transcriptome Analysis of Adult C. elegans Cells Reveals Tissue-specific Gene and Isoform Expression

This study analyzes the transcriptomes of four major tissues in adult C. elegans to identify tissue-specific genes, isoforms, and regulatory patterns, providing a resource for understanding adult multicellular biology.