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utsabghimire/README.md

Hi there, I'm Utsab

I'm a computational and molecular biologist unraveling the complexities of plant biology through data science and machine learning.

🌱 About Me

I currently explore how gene regulatory networks control plant senescence and stress responses. I integrate high‑throughput sequencing, proteomics and metabolomics to answer fundamental questions in plant biology and develop predictive models using machine learning.

  • 🔬 Research Interests: senescence, stress physiology, gene regulatory networks, single‑cell and bulk transcriptomics, proteomics and metabolomics.
  • 🧠 Technical Skills: Python (NumPy, Pandas, scikit‑learn, PyTorch), R (Seurat, WGCNA), Bash, HPC/Unix, Docker, Git.
  • 📊 Data Expertise: bulk RNA‑seq, single‑cell RNA‑seq (10× & SMART‑seq), proteomics, metabolomics, phenomic datasets.
  • 🤖 Machine Learning: gradient boosted trees (XGBoost, CatBoost), convolutional neural networks (CNNs), predictive modeling for biomass and trait prediction.

🚀 Projects

Here are some of the repositories I’ve been working on:

Project Description
broccoli‑scRNA‑seq Single‑cell RNA‑seq analysis pipeline for broccoli inflorescences, focusing on senescence and developmental trajectories.
bulk‑rnaseq‑postharvest‑pipeline Workflow for processing and analyzing bulk RNA‑seq data from postharvest plant tissues.
Postharvest_RNAseq Analyses exploring gene expression changes during postharvest senescence.
biomass-ml-prediction Machine learning models for cover crop biomass and C:N ratio prediction using CatBoost, XGBoost, and neural networks; includes feature engineering, weather‑based feature extraction, and example notebooks.
broccoli-proteomics-senescence Proteomics analysis pipeline for TMT‑based postharvest senescence in broccoli; includes scripts for loading, preprocessing, exploratory analysis (PCA and volcano plots), differential testing, and a command‑line workflow.

📈 GitHub Stats

Top Languages

🧰 Toolbox

Here are some tools and technologies I work with regularly:

Python R Docker PyTorch Git Linux

📫 How to Reach Me

Here’s how you can get in touch with me:

🎯 Goals

  • Deepen my understanding of plant senescence and stress‑induced gene regulation.
  • Apply cutting‑edge machine learning techniques to biological data.
  • Collaborate on open‑source projects and share reproducible workflows.

Thanks for visiting my profile! ⭐ Feel free to explore my repositories, and don’t hesitate to connect or reach out if our interests align.

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  1. broccoli-scRNA-seq broccoli-scRNA-seq Public

    Single‑cell RNA‑seq analysis pipeline for broccoli inflorescences, focusing on senescence and developmental trajectories.

    R

  2. bulk-rnaseq-postharvest-pipeline bulk-rnaseq-postharvest-pipeline Public

    Processing bulk RNA-seq from postharvest broccoli: QC, trimming, alignment, and HPC.

    1

  3. Postharvest_RNAseq Postharvest_RNAseq Public

    Analyses exploring gene expression changes during postharvest senescence

    R

  4. biomass-ml-prediction biomass-ml-prediction Public

    Machine learning models for cover crop biomass and C:N ratio prediction using XGBoost, CatBoost, and neural networks.

    Python

  5. broccoli-proteomics-senescence broccoli-proteomics-senescence Public

    Proteomics data analysis pipeline for TMT-based postharvest senescence study in broccoli; Python scripts for loading, preprocessing, analysis and visualisation.

    Python

  6. rnaseq-interactive-demo rnaseq-interactive-demo Public

    Interactive notebook and Streamlit app demonstrating an RNA-seq analysis pipeline from raw data to differential expression and visualisation.

    Python