Leonard A. Harris Data-verified
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Assistant Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Leonard A. Harris, Assistant Professor at the University of Arkansas, investigates complex human pathologies through computational modeling and systems biology approaches. His research focuses on developing and applying computational tools to understand disease mechanisms at a molecular and cellular level. He has published work on immune digital twins for complex human pathologies, in vitro models of tumor heterogeneity, and the role of epithelial–mesenchymal transition genes in small cell lung cancer.
Dr. Harris also studies biochemical models of cell death, such as necroptosis, and integrates multi-omics data to unify tumor growth mechanisms. His group develops software for analyzing high-throughput datasets, exemplified by the visualization tool "Thunor." Current funded work includes an NIH/National Cancer Institute grant for $187,596 to uncover molecular networks underlying non-genetic heterogeneity in cancer cell populations.
His scholarship metrics include an h-index of 19, with over 2,000 citations across 94 publications. He collaborates with researchers at the University of Arkansas, including L. Lynn Harris, Alexandra Gutierrez Vega, Karthik Nayani, and Homa Ghaiedi.
Metrics
- h-index: 19
- Publications: 98
- Citations: 2,102
Selected Publications
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A Computational Model of Tumor Interactions with Bone-Resident Cells Predicts Tumor-Type-Specific Responses to Perturbations (2026)
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Melanoma RNA-seq and dose-response data from GDSC for ML+mechanistic modeling (2026)
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Melanoma RNA-seq and dose-response data from GDSC for ML+mechanistic modeling (2026)
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Capturing Multi-Scale Dynamics of Aortic Valve Calcification With a Coupled Fluid–Structure and Systems Biology Model (2025)
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Immune digital twins for complex human pathologies: applications, limitations, and challenges (2024)
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Liquid crystalline collagen assemblies as substrates for directed alignment of human Schwann cells (2024)
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#52. Computational modeling of signaling pathways and cell-cell interactions driving tumor-induced bone disease (2024)
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Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia (2023)
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Concepts of multi-level dynamical modelling: Understanding mechanisms of squamous cell carcinoma development in Fanconi anemia (2023)
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Unified tumor growth mechanisms from multimodel inference and dataset integration (2023)
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Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity (2023)
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A biochemical necroptosis model explains cell-type-specific responses to cell death cues (2023)
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Processes in DNA damage response from a whole-cell multi-omics perspective (2022)
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Involvement of epithelial-mesenchymal transition genes in small cell lung cancer phenotypic plasticity (2022)
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Unified Tumor Growth Mechanisms from Multimodel Inference and Dataset Integration (2022)
Federal Grants 1 $187,596 total
Uncovering the molecular networks underlying non-genetic heterogeneity in cancer cell populations
Collaboration Network
Top Collaborators
- An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability
- Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity
- Thunor: visualization and analysis of high-throughput dose–response datasets
- Unified tumor growth mechanisms from multimodel inference and dataset integration
- A heterogeneous drug tolerant persister state in BRAF-mutant melanoma is characterized by ion channel dysregulation and susceptibility to ferroptosis
Showing 5 of 9 shared publications
- An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability
- Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity
- Thunor: visualization and analysis of high-throughput dose–response datasets
- A heterogeneous drug tolerant persister state in BRAF-mutant melanoma is characterized by ion channel dysregulation and susceptibility to ferroptosis
- Real-time luminescence enables continuous drug–response analysis in adherent and suspension cell lines
Showing 5 of 7 shared publications
- A biochemical necroptosis model explains cell-type-specific responses to cell death cues
- Thunor: visualization and analysis of high-throughput dose–response datasets
- Unified tumor growth mechanisms from multimodel inference and dataset integration
- Processes in DNA damage response from a whole-cell multi-omics perspective
- Unsupervised logic-based mechanism inference for network-driven biological processes
Showing 5 of 7 shared publications
- An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability
- Real-time luminescence enables continuous drug–response analysis in adherent and suspension cell lines
- Real-time luminescence enables continuous drug-response analysis in adherent and suspension cell lines
- Unified tumor growth mechanisms from multimodel inference and dataset integration
- Unsupervised logic-based mechanism inference for network-driven biological processes
- Unified Tumor Growth Mechanisms from Multimodel Inference and Dataset Integration
- Thunor: visualization and analysis of high-throughput dose–response datasets
- Processes in DNA damage response from a whole-cell multi-omics perspective
- An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability
- A heterogeneous drug tolerant persister state in BRAF-mutant melanoma is characterized by ion channel dysregulation and susceptibility to ferroptosis
- Real-time luminescence enables continuous drug–response analysis in adherent and suspension cell lines
- Real-time luminescence enables continuous drug-response analysis in adherent and suspension cell lines
- A biochemical necroptosis model explains cell-type-specific responses to cell death cues
- Distinct execution modes of a biochemical necroptosis model explain cell type-specific responses and variability to cell-death cues
- A biochemical necroptosis model explains cell-type-specific responses to cell death cues
- Distinct execution modes of a biochemical necroptosis model explain cell type-specific responses and variability to cell-death cues
- Unified tumor growth mechanisms from multimodel inference and dataset integration
- Unified Tumor Growth Mechanisms from Multimodel Inference and Dataset Integration
- Unified tumor growth mechanisms from multimodel inference and dataset integration
- Unified Tumor Growth Mechanisms from Multimodel Inference and Dataset Integration
- Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity
- Involvement of epithelial-mesenchymal transition genes in small cell lung cancer phenotypic plasticity
- Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity
- Involvement of epithelial-mesenchymal transition genes in small cell lung cancer phenotypic plasticity
- Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity
- Involvement of epithelial-mesenchymal transition genes in small cell lung cancer phenotypic plasticity
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