Subhani Upadhyaya

Research Interests

A Biotechnology graduate with a strong foundation in molecular biology and translational research, specialized in qPCR-based biomarker analysis and nucleic acid diagnostics, with hands-on experience in RNA/DNA workflows, cDNA synthesis, assay standardization, and statistical interpretation. I have conducted independent and collaborative laboratory work across molecular biology, cancer biology, and bioinformatics. Currently, I am working on AI-powered computational pathology project automating IHC biomarker scoring in breast cancer using deep learning.

Research & Projects

  • 2026 – Comp. path.
    Current
    AI-powered IHC Biomarker Scoring in Breast Cancer — CMDN

    Deep learning project automating ER, PR, HER2, and Ki-67 scoring across 1,216+ de-identified breast cancer cases at CMDN.

    • Contributing to a deep learning project automating IHC biomarker scoring (ER, PR, HER2, Ki-67) across a de-identified dataset of 1,216+ breast cancer cases.
    • Conducting feasibility review and infrastructure setup of a full computational pathology pipeline spanning stain normalization, WSI tiling, classical ML, and deep learning foundation models.
    Deep learning Whole-slide imaging IHC scoring Stain normalization Foundation models
  • 2024–25 Thesis
    Expression Analysis of circulating miR-34a and miR-146a in Healthy, Pre-diabetic and Diabetic Patients in Nepal

    Undergraduate Thesis Project, Kathmandu University

    • Pilot study to investigate the role of circulating miR-34a and miR-146a and their potential as biomarkers in diabetes progression.
    • Obtained ethical clearance from the Institutional Review Committee (IRC), Dhulikhel Hospital, followed by participant recruitment under informed consent, and questionnaires.
    • Collected and processed patient blood samples, performed HbA1c testing in collaboration with the Department of Biochemistry at Dhulikhel Hospital.
    • RNA extraction and isolation, cDNA synthesis, and qPCR performed for expression profiling from serum samples.
    • Applied ΔCt, ΔΔCt, and ROC curve analysis to compare expression across healthy, pre-diabetic, and diabetic groups.
    • Conducted ROC curve and AUC statistical evaluation using Python (pandas, NumPy, Matplotlib, scikit-learn).
    qPCR microRNA RNA extraction cDNA synthesis ROC / AUC scikit-learn

    Poster Presentation Winner — World DNA Day 2025, Biotechnology Society of Nepal

  • 2023 Bioinformatics
    Comparative evolutionary studies of the hemoglobin gene in different vertebrates

    Bioinformatics Project, Junior Year, Kathmandu University

    • Utilized bioinformatics tools and genomic databases to analyze hemoglobin gene conservation, phylogenetics, and evolutionary dynamics across 11 vertebrate species.
    • The study highlighted evolutionary conservation patterns, functional divergence, and syntenic relationships among vertebrate hemoglobin genes.
    • Key methodologies included multiple sequence alignment (MSA), phylogenetic tree construction, synteny analysis, and functional annotation of alpha and beta hemoglobin genes.
    MSA Phylogenetics Synteny analysis Functional annotation
  • Aug–Nov 2023 Applied biotech
    Development of Spirulina (microalgae) based cookies

    Kathmandu University (August 8, 2023 – November 30, 2023)

    • Implemented efficient methods for harvesting Spirulina, including filtration and drying techniques to ensure purity and quality of biomass for extracting phycocyanin dye.
    • Prepared growth media and cultivated Spirulina under optimized growth parameters, including pH, temperature, and light exposure to achieve high biomass yield.
    • Designed a nutrient-dense Spirulina-based food prototype, a health-conscious product leveraging microalgae's high protein and nutrient content.
    Microalgae Biomass cultivation Phycocyanin Food biotechnology
  • 2022 Environmental
    Physicochemical and Microbiological Assessment of Processed Drinking Water in Kathmandu Valley

    Chemistry Project, Sophomore Year, Kathmandu University

    • Assessed compliance with WHO, EPA, and NDWQS standards by running key lab tests: spectrophotometry, flame photometry, titration, and microbial assays.
    • Performed membrane filtration-based microbial detection (M-Endo and EMB agar).
    • Conducted statistical analysis and risk evaluation based on pH, EC, nitrate, phosphate, and contamination levels.
    Spectrophotometry Microbial assays WHO standards Public health

Articles & Blog