Qiwei Li

Assistant Professor

University of Texas at Dallas

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Qiwei Li is an Assistant Professor at the University of Texas at Dallas, United States. His research focuses on biostatistics, microbiome community detection, and spatial omics data analysis, as reflected in his recent publications. Notable works include the development of BISON for bi-clustering spatial omics data and MiCoDe for Bayesian analysis of microbiome communities.

Articles (23)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (7)

Julia Kozlitina

Associate Professor

University of Texas Southwestern Medical Center

UNITED STATES

View details

Michele Guindani

Professor

University of California, Los Angeles

UNITED STATES

View details

Nicole De Nisco

Assistant Professor

University of Texas at Dallas

UNITED STATES

View details

Alberto Cassese

University of Maastricht

NETHERLANDS

View details

Chul Moon

Assistant Professor

Southern Methodist University

UNITED STATES

View details

Min Chen

Professor

University of Texas at Dallas

UNITED STATES

View details

Philippe E. Zimmern

University of Texas Southwestern Medical Center

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Qiwei Li

Research Interests

Explore related searches

Contact this professor

About

Articles (23)

BISON: bi-clustering of spatial omics data with feature selection

MiCoDe: a web tool for performing microbiome community detection using a Bayesian weighted stochastic block model

Bladder Wall–Embedded Bacteria Associated With Increased Risk of Recurrence After Electrofulguration in Women With Antibiotic-Recalcitrant Urinary Tract Infection

A Generalized Bayesian Stochastic Block Model for Microbiome Community Detection

Health diagnosis associated with COVID-19 death in the United States: A retrospective cohort study using electronic health records

A regularized Bayesian Dirichlet-multinomial regression model for integrating single-cell-level omics and patient-level clinical study data

An interpretable Bayesian clustering approach with feature selection for analyzing spatially resolved transcriptomics data

Deep Learning-Based Automated Measurement of Murine Bone Length in Radiographs

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Bayesian Landmark-Based Shape Analysis of Tumor Pathology Images

Inflammatory markers for improved recurrent UTI diagnosis in postmenopausal women

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

AI-Powered Bayesian Statistics in Biomedicine

SAFARI: shape analysis for AI-segmented images

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Bayesian Analysis of Infectious Diseases: COVID-19 and Beyond.

A deep learning-based model for screening and staging pneumoconiosis

Comparison of inflammatory markers as moderators of depression outcomes: A CO-MED study

A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data

Urinary prostaglandin E2 as a biomarker for recurrent UTI in postmenopausal women

Bayesian modeling of spatial molecular profiling data via Gaussian process

Spatial molecular profiling: platforms, applications and analysis tools

MetaPrism: A versatile toolkit for joint taxa/gene analysis of metagenomic sequencing data

Collaborators (7)

Julia Kozlitina

Michele Guindani

Nicole De Nisco

Alberto Cassese

Chul Moon

Min Chen

Philippe E. Zimmern

Make your next move.