Computational Models
Autonomous construction of 3D leaves
An assessment of deep generative networks in creating realistic 3D data
Writer
Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial
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Computational Models
An assessment of deep generative networks in creating realistic 3D data
Rachel Shekar ·
Cells, Genes & Molecules
Surveying machine learning methods to improve detection of binding sites.
Rachel Shekar ·
Computational Models
Predicting phenology can provide insight into better management.
Rachel Shekar ·
Cells, Genes & Molecules
Bioengineering boosts photosynthesis and increases yields in food crops for the first time ever.
Rachel Shekar ·
Cells, Genes & Molecules
A model designed to study circadian effects on physiology becomes more broadly useful when the clock regulates metabolites.
Rachel Shekar ·
Cells, Genes & Molecules
A new gene-to-phenotype network for shoot branching.
Rachel Shekar ·
Computational Models
Measuring the impact of brace roots on lodging resistance in maize.
Rachel Shekar ·
Computational Models
The closeness of plants affects architectural plasticity and carbon uptake.
Rachel Shekar ·
Cells, Genes & Molecules
A new study uses computational modelling to determine how and why cotton quality develops.
Rachel Shekar ·
Computational Models
A new study highlights areas of compatibility and strategies to move towards better communication and collaboration.
Rachel Shekar ·
Growth & Development
Using computational models to overcome the shortcomings of high throughput phenotyping field data.
Rachel Shekar ·
Computational Models
The Quantitative Plant website is a comprehensive database of public datasets for plant phenotyping, image analysis software tools and models for plants.
Rachel Shekar ·