Allen J. Gies
Research Associate, DNA Sequencing Core Manager
Also affiliated: Stowers Institute for Medical Research (2024); University of Arkansas Medical Center (2022–2024); Arkansas Children's Research Institute (2020); University of Oklahoma Health Sciences Center (1997)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Allen J. Gies investigates the integration of multi-omics data to understand biological systems and disease, with a focus on triple-negative breast cancer and hepatocellular carcinoma. His work includes the development of computational tools for quantitative proteomics, such as the proteoDA package. Gies has explored the impact of sample storage on microbiome profiles and the role of exosomal microRNAs as biomarkers for chemotherapy response in breast cancer. He also studies epigenetic control mechanisms protecting tumor-infiltrating lymphocytes from metabolic exhaustion and examines exosomal microRNA and protein profiles related to hepatitis B virus-associated hepatocellular carcinoma. Gies collaborates with researchers at the University of Arkansas for Medical Sciences, including Stephanie D. Byrum and Charity L. Washam, with whom he has co-authored multiple publications.
Metrics
- h-index: 11
- Publications: 35
- Citations: 546
Positions
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Research Associate, DNA Sequencing Core Manager publications 2016–2026University of Arkansas for Medical Sciences Institution web page
Selected Publications
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Loss of FAM60A disrupts Sin3/HDAC control of the Hippo signaling and promotes oncogenic YAP1 activation (2026)
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8572 A 30% Maternal Caloric Restriction Alters Expression of Musashi Targets in the Neonatal and Adult Pituitary Proteomes of FVB Mice (2024)
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Maternal undernutrition results in transcript changes in male offspring that may promote resistance to high fat diet induced weight gain (2024)
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Beyond the Sin3/HDAC Complex: FAM60A emerges as a regulator of RNA Splicing (2024)
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Characterization of methionine dependence in melanoma cells (2023)
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Exosomal MicroRNA and Protein Profiles of Hepatitis B Virus-Related Hepatocellular Carcinoma Cells (2023)
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Musashi Exerts Control of Gonadotrope Target mRNA Translation During the Mouse Estrous Cycle (2023)
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Targeting mitochondria in the aged cerebral vasculature with SS-31, a proteomic study of brain microvessels (2023)
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proteoDA: a package for quantitative proteomics (2023)
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The beneficial effects of SS-31 on aging mice cerebral microvasculature (2023)
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Characterization of methionine dependence in melanoma cells (2023)
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Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy (2023)
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Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy (2023)
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Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy (2023)
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Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy (2023)
Collaboration Network
Top Collaborators
- Multi-omics data integration considerations and study design for biological systems and disease
- proteoDA: a package for quantitative proteomics
- Circulating Exosomal microRNAs as Predictive Biomarkers of Neoadjuvant Chemotherapy Response in Breast Cancer
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer
Showing 5 of 21 shared publications
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Characterization of methionine dependence in melanoma cells
- Characterization of methionine dependence in melanoma cells
- Methionine stress induces a ferroptotic gene signature in methionine dependent cancer cells
- Abstract 1029: Epigenetic control of tumor-infiltrating lymphocyte metabolic-exhaustion
Showing 5 of 9 shared publications
- Multi-omics data integration considerations and study design for biological systems and disease
- proteoDA: a package for quantitative proteomics
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer
- Exosomal MicroRNA and Protein Profiles of Hepatitis B Virus-Related Hepatocellular Carcinoma Cells
Showing 5 of 7 shared publications
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Exosomal MicroRNA and Protein Profiles of Hepatitis B Virus-Related Hepatocellular Carcinoma Cells
- Characterization of methionine dependence in melanoma cells
- Targeting mitochondria in the aged cerebral vasculature with SS-31, a proteomic study of brain microvessels
- Characterization of methionine dependence in melanoma cells
Showing 5 of 7 shared publications
- Multi-omics data integration considerations and study design for biological systems and disease
- proteoDA: a package for quantitative proteomics
- Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer
- Characterization of methionine dependence in melanoma cells
- Characterization of methionine dependence in melanoma cells
Showing 5 of 6 shared publications
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Characterization of methionine dependence in melanoma cells
- Characterization of methionine dependence in melanoma cells
- Abstract 1029: Epigenetic control of tumor-infiltrating lymphocyte metabolic-exhaustion
- Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion
- Characterization of methionine dependence in melanoma cells
- Characterization of methionine dependence in melanoma cells
- Abstract 1029: Epigenetic control of tumor-infiltrating lymphocyte metabolic-exhaustion
- Multi-omics data integration considerations and study design for biological systems and disease
- Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer
- Characterization of methionine dependence in melanoma cells
- Characterization of methionine dependence in melanoma cells
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
- Supplementary Data from Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy
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