Emily S. Bellis Data-verified
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Assistant Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Emily S. Bellis investigates the evolutionary biology and genomics of parasitic plants and their hosts, as well as the genetic variation and mutation rates in animal populations. Her work on parasitic plants includes research into resolving intergenotypic resistance in sorghum to witchweed (Striga) and identifying strigolactone biosynthesis alleles that confer resistance to Striga parasitism. Bellis has also studied the ecological and physiological threats posed by dodders to farmlands in Eastern Africa and conducted comparative phylogeographic analyses of invasive Cuscuta species in Kenya to inform management strategies.
In parallel, her research extends to animal evolution, including studies on transposable element mutation rates and variability in Daphnia magna. Bellis has also explored the application of remote sensing and deep learning techniques for detecting intra-field variation in crop yield, specifically in rice. Her scholarly contributions are reflected in a h-index of 15, with 60 total publications and 864 citations. She is a Co-Principal Investigator on a National Science Foundation grant totaling $1,999,484, focused on understanding invasion and disease ecology and evolution through computational data education. Bellis collaborates actively with colleagues at Arkansas State University, including Jason Causey, Brett Hale, Asela Wijeratne, and Ahmed A. Hashem.
Metrics
- h-index: 16
- Publications: 60
- Citations: 885
Selected Publications
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Predicting Gene Expression Responses to Cold in Arabidopsis thaliana Using Natural Variation in DNA Sequence (2025)
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Cell Wall Dynamics in the Parasitic Plant (<i>Striga</i>) and Rice Pathosystem (2024)
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Global genotype by environment prediction competition reveals that diverse modeling strategies can deliver satisfactory maize yield estimates (2024)
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Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction (2024)
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Global Genotype by Environment Prediction Competition Reveals That Diverse Modeling Strategies Can Deliver Satisfactory Maize Yield Estimates (2024)
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Predicting gene expression responses to environment in <i>Arabidopsis thaliana</i> using natural variation in DNA sequence (2024)
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Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach (2024)
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Climate biogeography of <i>Arabidopsis thaliana</i> : Linking distribution models and individual variation (2023)
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Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism (2023)
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Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant (2023)
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Resolving intergenotypic <i>Striga</i> resistance in sorghum (2023)
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Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa (2023)
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Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa (2023)
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Resolving intergenotypic <i>Striga</i> resistance in sorghum (2022)
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A transcriptome atlas of <i>Striga hermonthica</i> germination (2022)
Federal Grants 1 $1,999,484 total
Understanding Invasion and Disease Ecology and Evolution through Computational Data Education
Collaboration Network
Top Collaborators
- Physiological and ecological warnings that dodders pose an exigent threat to farmlands in Eastern Africa
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Comparative phylogeographic analysis of <scp><i>Cuscuta campestris</i></scp> and <scp><i>Cuscuta reflexa</i></scp> in Kenya: Implications for management of highly invasive vines
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
Showing 5 of 10 shared publications
- Climate biogeography of <i>Arabidopsis thaliana</i> : Linking distribution models and individual variation
- The geography of parasite local adaptation to host communities
- Predicting gene expression responses to environment in <i>Arabidopsis thaliana</i> using natural variation in DNA sequence
- The geography of parasite local adaptation to host communities
- Climate biogeography of <i>Arabidopsis thaliana:</i> linking distribution models and individual variation
Showing 5 of 8 shared publications
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
- Cell Wall Dynamics in the Parasitic Plant (<i>Striga</i>) and Rice Pathosystem
- A transcriptome atlas of <i>Striga hermonthica</i> germination
Showing 5 of 8 shared publications
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
- Genomic signatures of host-specific selection in a parasitic plant
- A transcriptome atlas of <i>Striga hermonthica</i> germination
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
- Cell Wall Dynamics in the Parasitic Plant (<i>Striga</i>) and Rice Pathosystem
- A transcriptome atlas of <i>Striga hermonthica</i> germination
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
- Cell Wall Dynamics in the Parasitic Plant (<i>Striga</i>) and Rice Pathosystem
- A transcriptome atlas of <i>Striga hermonthica</i> germination
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Transcriptome atlas of <i>Striga</i> germination: Implications for managing an intractable parasitic plant
- Cell Wall Dynamics in the Parasitic Plant (<i>Striga</i>) and Rice Pathosystem
- A transcriptome atlas of <i>Striga hermonthica</i> germination
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Resolving intergenotypic <i>Striga</i> resistance in sorghum
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning
- The geography of parasite local adaptation to host communities
- The geography of parasite local adaptation to host communities
- Genomic signatures of host-specific selection in a parasitic plant
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- COVID19 Diagnosis Using Chest X-rays and Transfer Learning
- Genomic signatures of host-specific selection in a parasitic plant
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- COVID19 Diagnosis Using Chest X-rays and Transfer Learning
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Strigolactone biosynthesis <i>lgs1</i> mutant alleles mined from the sorghum accession panel are a promising resource of resistance to witchweed (<i>Striga</i>) parasitism
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
- Harnessing the strigolactone biosynthesis mutant lgs1 to combat food insecurity in Africa
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