A considered selection of HiScript projects across bioinformatics, machine learning and web development — from exploratory analysis to practical software.
Explore work by discipline. Project labels describe the current shape of each repository and avoid implying that every experiment is a finished product.
Showing all 6 projects.
Jupyter-based analysis of ALAS1 RNA-seq expression and read-count data, including statistics, regression, clustering, outlier analysis and Random Forest classification.
View repository →A computational re-analysis of public soybean root-associated bacterial 16S rRNA data using a QIIME 2 workflow to investigate genotype, developmental stage and root-associated compartment.
View repository →An exploratory Python workflow using TCGA copy-number variation data and Random Forest classification, with patient-level feature aggregation, model metrics and feature-importance analysis.
View repository →A Django-based web application project using Python with production-oriented dependencies including Gunicorn, PostgreSQL connectivity and environment configuration.
View repository →A business website implementation using HTML, CSS, Bootstrap and JavaScript, demonstrating responsive frontend development and branded web content.
View repository →A Django web project for a blog-style website, demonstrating another application of Python web development within the HiScript portfolio.
View repository →The portfolio is intentionally interdisciplinary: technical learning becomes work that can be inspected, explained, improved and eventually shipped.
Computational methods can help researchers work with genomic, expression and microbiome data.
Machine learning is used as a method for exploration, classification and analysis rather than as an end in itself.
Web projects turn ideas and workflows into accessible interfaces and working digital systems.
HiScript works across technology, research and learning. If you have a problem, project idea or technical challenge, start a conversation.
