Mary Qu Yang Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Professor - STEM
faculty
Information Science
Research Areas
Biography and Research Information
OverviewAI-generated summary
Mary Qu Yang's research focuses on the application of computational methods, including machine learning and artificial intelligence, to address complex challenges in health and medicine. Her work investigates the analytical validity of diagnostic assays, such as circulating tumor DNA sequencing for precision oncology, and explores the use of machine learning for enhancing disease classification, including Alzheimer's disease. Yang also contributes to the field of cancer drug development by studying artificial intelligence applications and characterizing the tumor microenvironment's impact on breast cancer prognosis.
Her research extends to understanding molecular mechanisms and genetic regulation, with publications examining gene regulation in autism spectrum disorder development and integrating single-cell transcriptome analysis for characterizing therapeutic responses in chronic myeloid leukemia. Yang leads a research group and has a notable publication record, indicated by an h-index of 30 and over 5,000 citations. Her collaborations include researchers from the National Center for Toxicological Research and the University of Arkansas for Medical Sciences, contributing to a network of 15 shared publications with key collaborators.
Metrics
- h-index: 30
- Publications: 197
- Citations: 5,199
Selected Publications
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Single-Cell Transcriptomic Analysis Unveils Key Regulators and Signaling Pathways in Lung Adenocarcinoma Progression (2025)
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Characterizing the Tumor Microenvironment and Its Prognostic Impact in Breast Cancer (2024)
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Novel Thienopyrimidine-Hydrazinyl Compounds Induce DRP1-Mediated Non-Apoptotic Cell Death in Triple-Negative Breast Cancer Cells (2024)
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cnnImpute: missing value recovery for single cell RNA sequencing data (2024)
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A Deep Learning-Based Model for Gene Regulatory Network Inference (2023)
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Analysis of Single-Cell RNA Sequencing Data Unveils Novel Immune Prognostic Biomarkers (2023)
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Exploring Barriers to Diversity, Equity, and Inclusion in Communication Sciences and Disorders Students (2023)
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Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples (2022)
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Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples (2022)
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Integrating Single-Cell Transcriptome and Network Analysis to Characterize the Therapeutic Response of Chronic Myeloid Leukemia (2022)
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Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples (2022)
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Missing Value Recovery for Single Cell RNA Sequencing Data (2021)
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Gene Regulation Analysis Reveals Perturbations of Autism Spectrum Disorder during Neural System Development (2021)
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Brain Tumor Segmentation Using Deep Neural Networks and Survival Prediction (2021)
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Merging Deep Learning and Data Analytics for Inferring Coronavirus Human Adaptive Transmutability and Transmissibility (2021)
ARA Academy 2023 ARA Fellow
Dr. Yang established the Systems Genomics Laboratory at UALR. She holds degrees in engineering, physics, electrical and computer engineering, and a PhD in Computational Science and Physics from Purdue University. She completed postdoctoral training in Human Genomics and Bioinformatics at the National Human Genome Research Institute (NHGRI) and worked as a Research Fellow there from 2008-2012.
Policy Impact
Established the MidSouth Bioinformatics Center at UALR, building computational genomics infrastructure that supports health research and precision medicine across the state.
Growth Areas
['Population Health Innovations & Clinical Research']
Collaboration Network
Top Collaborators
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
Showing 5 of 6 shared publications
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples
- Additional file 3 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
- Additional file 2 of Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples
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