Andy Pereira
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Professor
Also affiliated: Pohang University of Science and Technology (2009); Commonwealth Scientific and Industrial Research Organisation (2009); Centre de Coopération Internationale en Recherche Agronomique pour le Développement (2009); Louisiana State University Agricultural Center (2022); Max Planck Society (1985–1989); University of Botswana (2017); International Rice Research Institute (2009–2010); Temasek Life Sciences Laboratory (2009); National University of Singapore (2009); Iowa State University (1985–1986); Huazhong Agricultural University (2009); University of Arkansas System (2012–2026); CPB Netherlands Bureau for Economic Policy Analysis (1999); Graduate School Experimental Plant Sciences (1992–1999); Institute of Plant and Microbial Biology, Academia Sinica (2009); Schlumberger (Ireland) (1998); Research International (United States) (2000–2006); New Mexico Consortium (2017); Centre for BioSystems Genomics (2001–2006); Agrico (Netherlands) (2005); Fayetteville Public Library (2015); Instituut voor Landbouw en Visserijonderzoek (1995); Bioinformatics Institute (2008); Plant Industry (2009); Human Growth Foundation (2024); ACT Government (2009); Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (2010); University of California, Davis (2009); Virginia Tech (2007–2017); Wageningen University & Research (1991–2022)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Andy Pereira's research program focuses on the genetic dissection of complex traits in rice (Oryza sativa) and Arabidopsis, with a particular emphasis on understanding responses to environmental stressors. His work investigates the genetic underpinnings of traits such as grain yield, grain quality, and drought resistance. Pereira utilizes high-throughput molecular markers, including SNP markers, to map quantitative trait loci (QTLs) associated with these traits in diverse rice populations, such as recombinant inbred line (RIL) populations.
His recent publications explore the genetic basis of grain chalkiness, chlorophyll content under drought, and grain yield components under high nighttime temperature stress. Pereira also employs network-based machine learning approaches to predict transcription factors involved in drought resistance. Collaborations include numerous shared publications with researchers at the University of Arkansas at Fayetteville, such as Julie A. Thomas and Yheni Dwiningsih. With an h-index of 51, 243 publications, and over 12,620 citations, Pereira is recognized as a highly cited researcher.
Metrics
- h-index: 51
- Publications: 244
- Citations: 12,700
Selected Publications
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High nighttime temperature (HNT)-responsive MicroRNA profiles in developing caryopses and flag leaves of 13 rice varieties (2026)
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Integrative Genomic Analyses to Unravel Genomic Regions and Candidate Genes Associated with Flag Leaf Photosynthesis at the Reproductive Stage in Rice (2025)
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Rice master regulator ‘HYR’ enhances growth and defense mechanisms with consequences for fall armyworm growth and host selection (2025)
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Effects of measurement methods and growing conditions on phenotypic expression of photosynthesis in seven diverse rice genotypes (2023)
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High Daytime Temperature Responsive MicroRNA Profiles in Developing Grains of Rice Varieties with Contrasting Chalkiness (2023)
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Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress (2023)
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Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress (2022)
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Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population (2022)
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QTL mapping of panicle architecture and yield-related traits between two US rice cultivars 'LaGrue' and 'Lemont' (2021)
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Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers (2021)
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Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel (2021)
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Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions (2021)
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Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance (2021)
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The Arabidopsis Proteins AtNHR2A and AtNHR2B Are Multi-Functional Proteins Integrating Plant Immunity With Other Biological Processes (2020)
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Genetic Mapping Identifies Consistent Quantitative Trait Loci for Yield Traits of Rice under Greenhouse Drought Conditions (2020)
Collaboration Network
Top Collaborators
- Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers
- Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
Showing 5 of 8 shared publications
- Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
Showing 5 of 6 shared publications
- Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers
- Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance
- Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- High Daytime Temperature Responsive MicroRNA Profiles in Developing Grains of Rice Varieties with Contrasting Chalkiness
- Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
- Identification of QTLs and Candidate Loci Associated with Drought-Related Traits of the K/Z RIL Rice Population
- QTL mapping of panicle architecture and yield-related traits between two US rice cultivars 'LaGrue' and 'Lemont'
- Integrative Genomic Analyses to Unravel Genomic Regions and Candidate Genes Associated with Flag Leaf Photosynthesis at the Reproductive Stage in Rice
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
- High Daytime Temperature Responsive MicroRNA Profiles in Developing Grains of Rice Varieties with Contrasting Chalkiness
- High nighttime temperature (HNT)-responsive MicroRNA profiles in developing caryopses and flag leaves of 13 rice varieties
- Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance
- Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance
- Quantitative Trait Loci and Candidate Gene Identification for Chlorophyll Content in RIL Rice Population under Drought Conditions
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