Michael Love

Associate Professor

University of North Carolina at Chapel Hill

United States

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About

Michael Love is an Associate Professor at the University of North Carolina at Chapel Hill, USA. His research areas include computational biology, genomics, and RNA sequencing analysis, with a focus on differential testing and classification of genetic interactions. His recent articles explore topics such as the socio-economic factors associated with breast cancer, etiological heterogeneity in multinomial outcomes, and advanced methods for transcript quantification.

Articles (15)

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2025

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2024

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (13)

Katherine Hoadley

Assistant Professor

University of North Carolina at Chapel Hill

UNITED STATES

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Di Wu

University of North Carolina

UNITED STATES

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Rob Patro

University of Maryland

UNITED STATES

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Michael Love

Research Interests

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Articles (15)

Tree-based differential testing using inferential uncertainty for RNA-seq

Genomic Analysis Reveals Racial and Age-Related Differences in the Somatic Landscape of Breast Cancer and the Association with Socioeconomic Factors

Probabilistic classification of gene-by-treatment interactions on molecular count phenotypes

Assessing etiological heterogeneity for multinomial outcome with two-phase outcome-dependent sampling design

Diffsig: Associating Risk Factors with Mutational Signatures

Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population

Context-aware transcript quantification from long-read RNA-seq data with Bambu

Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features

SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty

bootRanges: flexible generation of null sets of genomic ranges for hypothesis testing

matchRanges: generating null hypothesis genomic ranges via covariate-matched sampling

excluderanges: exclusion sets for T2T-CHM13, GRCm39, and other genome assemblies

RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets

Molecular and Clinical Characterization of Postpartum-Associated Breast Cancer in the Carolina Breast Cancer Study Phase I–III, 1993–2013

Collaborators (13)

Katherine Hoadley

Di Wu

Noor Pratap Singh

Benjamin Calhoun

Jonathan Göke

Stuart Lee

Sarah Van Alsten

Pepper Schedin

Avi Srivastava

Mikhail Dozmorov

William Valdar

Xiaohua Gao

Rob Patro

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