Search Results - "Lawrence-Dill, Carolyn J."

Transdisciplinary Graduate Training in Predictive Plant Phenomics.

Authors: Lawrence-Dill, Carolyn J. Heindel, Theodore J. Schnable, Patrick S. et al.

Source: Agronomy. May2018, Vol. 8 Issue 5, p73. 6p.

Wisconsin diversity panel phenotypes: spoken descriptions of plants and supporting data.

Authors: Yanarella, Colleen F. Fattel, Leila Kristmundsdóttir, Ásrún Ý. et al.

Source: BMC Research Notes. 1/23/2024, Vol. 17 Issue 1, p1-5. 5p.

Ten simple rules to ruin a collaborative environment.

Authors: Lawrence-Dill, Carolyn J. Allscheid, Robyn L. Boaitey, Albert et al.

Source: PLoS Computational Biology. 4/14/2022, Vol. 18 Issue 4, p1-11. 11p. 10 Illustrations.

Genome-wide association studies from spoken phenotypic descriptions: a proof of concept from maize field studies.

Authors: Yanarella, Colleen F Fattel, Leila Lawrence-Dill, Carolyn J

Source: G3: Genes | Genomes | Genetics. Sep2024, Vol. 14 Issue 9, p1-13. 13p.

Gene Ontology Meta Annotator for Plants (GOMAP).

Authors: Wimalanathan, Kokulapalan Lawrence-Dill, Carolyn J.

Source: Plant Methods. 5/25/2021, Vol. 17 Issue 1, p1-14. 14p.

Gene function annotations for the maize NAM founder lines.

Authors: Fattel, Leila Yanarella, Colleen F. Ngara, Blessing et al.

Source: BMC Research Notes. 1/2/2024, Vol. 17 Issue 1, p1-5. 5p.

An Interdisciplinary Graduate Course for Engineers, Plant Scientists, and Data Scientists in the Area of Predictive Plant Phenomics.

Authors: Heindel, Theodore J. Lawrence-Dill, Carolyn J. Dickerson, Julie A. et al.

Source: Proceedings of the ASEE Annual Conference & Exposition. 2017, p1673-1682. 10p.

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GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations.

Authors: Manchanda, Nancy Portwood II, John L. Woodhouse, Margaret R. et al.

Source: BMC Genomics. 3/2/2020, Vol. 21 Issue 1, p1-9. 9p. 2 Diagrams, 4 Charts, 1 Graph.

High-frequency random DNA insertions upon co-delivery of CRISPR-Cas9 ribonucleoprotein and selectable marker plasmid in rice.

Authors: Banakar, Raviraj Eggenberger, Alan L. Lee, Keunsub et al.

Source: Scientific Reports. 12/27/2019, Vol. 9 Issue 1, p1-13. 13p.

Training Students with T-shaped Interdisciplinary Studies in Predictive Plant Phenomics.

Authors: Dickerson, Julie A. Heindel, Theodore (Ted) J. Lawrence-Dill, Carolyn J. et al.

Source: Proceedings of the ASEE Annual Conference & Exposition. 2017, p5068-5079. 12p.

Standardized genome-wide function prediction enables comparative functional genomics: a new application area for Gene Ontologies in plants.

Authors: Fattel, Leila Psaroudakis, Dennis Yanarella, Colleen F et al.

Source: GigaScience. 2022, Vol. 11, p1-18. 18p.

Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning.

Authors: Zhou, Naihui Siegel, Zachary D. Zarecor, Scott et al.

Source: PLoS Computational Biology. 7/30/2018, Vol. 14 Issue 7, p1-16. 16p. 2 Color Photographs, 1 Diagram, 2 Charts, 3 Graphs.

Assessing plant performance in the Enviratron.

Authors: Bao, Yin Zarecor, Scott Shah, Dylan et al.

Source: Plant Methods. 10/23/2019, Vol. 15 Issue 1, pN.PAG-N.PAG. 1p.

Plant growth regulators interact with elevated temperature to alter heat stress signaling via the Unfolded Protein Response in maize.

Authors: Neill, Elena M. Byrd, Michael C. R. Billman, Thomas et al.

Source: Scientific Reports. 7/17/2019, Vol. 9 Issue 1, pN.PAG-N.PAG. 1p.