Machine learning: data visualization.
Machine learning: predicted vs actual targets.
Machine learning: feature selection.
Machine learning: correlation heatmap.
A bubble chart for GMO% of all upland cotton planted across USA in 2018.
A bubble chart for GMO% of all corn planted across USA in 2018.
A bubble chart for GMO% of all soybeans planted in 2018.
The main subjects in Data Sciences.
A python scatterplot matrix for maize gene expression.
A Venn diagram: Data Science vs IT and Business.
The most popular R libraries in 2018.
RNA-seq analysis: A heatmap of similarities across the samples and treatments.
A heatmap for clustering gene expression levels across samples and treatments.
An MA plot to visualize differential gene expression between samples.
Machine learning and its applications.
Visualization of syntenic regions across the genomes of different species/subspecies.
Data sciences are crucial for successful business.
Visualization of multiple commercial hybrids produced from an elite inbred.
A chord diagram for genic contributions to the phenotypes by the SNF orthologs.
The popular python libraries of 2018.
Linear regression in scatterplot charts for the soybean traits from multi-environment trials.
3D scatter plot of crop yield, disease rating and seed quality from variety trials.
The popular python frameworks of 2017.
A correlation matrix of soybean traits from multi-environment trials.
Scatterplot matrices among crop traits arranged by correlation.
A 3D plot generated using Python.
A gene database of the plant species created using SQL.
Data visualization of crop yield from field trials using D3.js.