Plant scientist working where molecular biology meets data science.
CRISPR gene editing · plant transformation · multi-omics · machine learning
I build more resilient crops — from a single edited gene to thousands analyzed at once. At Soilcea, I develop transgene-free, CRISPR-edited citrus to fight Huanglongbing (citrus greening), and I use multi-omics and machine learning to understand how plants grow, age, and defend themselves.
- 🔬 At the bench: CRISPR/Cas9 & base editing, Agrobacterium-mediated transformation, tissue culture & regeneration, molecular cloning.
- 💻 At the keyboard: bulk & single-cell RNA-seq, whole-genome sequencing, proteomics, metabolomics, and reproducible HPC pipelines.
- 🤖 For prediction: gradient-boosted trees and neural networks for crop traits, biomass, and the signals hidden in omics data.
- 🎓 PhD, Horticultural Sciences — University of Florida.
Languages
ML & data
Bioinformatics & omics
Tools
| Project | What it does |
|---|---|
| broccoli-scRNA-seq | Single-cell RNA-seq pipeline for broccoli inflorescences — senescence & developmental trajectories. |
| bulk-rnaseq-postharvest-pipeline | QC, trimming, alignment & HPC workflow for bulk RNA-seq from postharvest tissue. |
| biomass-ml-prediction | ML models for cover-crop biomass & C:N ratio (CatBoost, XGBoost, neural nets) with weather features. |
| broccoli-proteomics-senescence | TMT-based proteomics pipeline — preprocessing, PCA, volcano plots, differential testing. |
| rnaseq-interactive-demo | Interactive notebook + Streamlit app — RNA-seq from raw data to differential expression. |
Peer-reviewed work in plant postharvest biology, senescence genomics, and ML for agriculture — published in Postharvest Biology and Technology, Vegetable Research, and Agricultural & Environmental Letters. 👉 Full publication list on Google Scholar
Thanks for stopping by. If our interests overlap — crop biotech, omics, or ML for plants — I'd love to connect.
🌐 utsabghimire.github.io