Wei Vivian Li

RNASeek: A Cross-Phyla Generative Foundation Model for Multipurpose RNA Modeling and Reinforcement Learning-Based Design

RNASeek is a generative foundation model for RNA sequence design and functional prediction, using reinforcement learning to optimize RNA properties like stability and cleavage activity.

A Machine Learning Approach to Predicting Dyspnea with Noninvasive Biomarkers

This study uses machine learning to predict dyspnea using noninvasive biomarkers, achieving higher accuracy than observational estimates in a healthy population.

Spatial Transcriptomics Using Archived Formalin-Fixed Paraffin-Embedded Core Needle Biopsy Tissues Revealed Unique Transcriptomic Signatures in Kidney Transplant Rejections

This study uses spatial transcriptomics on FFPE kidney biopsy tissues to identify distinct transcriptomic signatures for different types of kidney transplant rejections.

Harmonizing Heterogeneous Single-Cell Gene Expression Data with Individual-Level Covariate Information

This paper introduces scINSIGHT2, a method for integrating scRNA-seq data with individual-level covariates, showing it effectively harmonizes datasets and captures biological insights.

Analyzing RNA-Seq Data from Chlamydia with Super Broad Transcriptomic Activation: Challenges, Solutions, and Implications for Other Systems

The paper addresses challenges in differential expression analysis of Chlamydia RNA-Seq data by proposing normalization methods that better capture transcriptomic activation, validated through qRT-PCR.

scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

scINSIGHT improves analysis of heterogeneous single-cell data by identifying coordinated gene expression patterns across biological conditions.

MAAPER: model-based analysis of alternative polyadenylation using 3' end-linked reads

MAAPER analyzes alternative polyadenylation using nearSite reads, accurately predicting PASs and examining APA events with robust statistics across bulk and single-cell RNA samples.

mbImpute: an accurate and robust imputation method for microbiome data

mbImpute improves microbiome data analysis by accurately imputing non-biological zeros, enhancing the detection of disease-related taxa in type 2 diabetes and colorectal cancer data.

scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data

scLink constructs sparse gene co-expression networks from single-cell RNA sequencing data using statistical modeling, showing improved performance in simulation and real data studies.

scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

scDesign2 generates high-fidelity synthetic single-cell gene expression data with gene correlations, enabling benchmarking of experimental protocols and computational methods.

Predicting long-term multicategory cause of death in patients with prostate cancer: random forest versus multinomial model

This study compares random forest and multinomial models for predicting 6-category cause of death in prostate cancer patients, finding random forest achieves 59.1% accuracy versus 50.4% for multinomial models.

AIDE: annotation-assisted isoform discovery with high precision

AIDE improves mRNA isoform discovery by using annotation to enhance precision and reduce errors in RNA-seq data analysis.

A statistical simulator scDesign for rational scRNA-seq experimental design

scDesign is a statistical simulator that helps optimize scRNA-seq experimental design by assessing sequencing parameters and generating synthetic datasets for method development.

EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences

EpiAlign is a new alignment tool for comparing chromatin state sequences across epigenomic data, identifying common patterns and cell-type-specific features.

scImpute: Accurate And Robust Imputation For Single Cell RNA-Seq Data

scImpute is a statistical method that imputes dropout values in scRNA-seq data, improving clustering, differential expression analysis, and gene expression dynamics studies.