Virtual-Internship Goal
This project aims to replicate and extend a published methodology for identifying minimal gene panels that can serve as biomarkers for disease diagnosis. Using machine learning-based feature selection techniques, the team will develop noninvasive diagnostic tools for conditions like Gastric Cancer, building on approaches that successfully differentiated COVID-19 from Influenza in a prior study.
Virtual Internship Details
- Project Type: Research-focused with practical applications.
- Eligibility: Open to undergraduate and graduate students with an interest in bioinformatics, machine learning, or biotechnology.
- Timeline: Any 3 weeks in July
- Project Lead: STEM-Away Alumni with a Master’s in Biotechnology, published researcher in Scientific Reports, and project lead for 2 bioinformatics virtual-internships.
- Qualification: Applicants must successfully complete the evaluation for 🟢 Combo: GEOQuest, Bioconductor-Intro
- How to Apply: Reply to this post or send a DM to @stemaway. Check this link for details.
Technologies & Skills Involved
- Differential Expression Analysis: Similar to GEOQuest/Bioconductor approaches (optional, depending on time constraints).
- Machine Learning-Based Feature Selection: Using RapidMiner or Python libraries (e.g., Scikit-learn).
- Filter Methods: For biomarker identification (e.g., correlation-based, statistical tests).
- R Programming: For bioinformatics data analysis and visualization.
- Clinical Application Design: Develop frameworks for translating biomarkers into noninvasive diagnostic tools.
Team Composition (5-7 Members)
1. Bioinformatics Analysts
- Responsibilities:
- Perform differential expression analysis on disease datasets (if time permits).
- Implement machine learning-based feature selection methods using RapidMiner or Python.
- Compare and evaluate different feature selection approaches (e.g., wrapper, filter methods).
- Validate findings using statistical methods (e.g., p-values, ROC curves).
- Skills Needed: R programming, basic machine learning, bioinformatics fundamentals.
2. Translational Researchers
- Responsibilities:
- Evaluate the biological significance of identified biomarkers.
- Design validation experiments for biomarker panels (e.g., in silico or wet-lab validation).
- Develop frameworks for clinical application of the biomarkers (e.g., diagnostic kits, blood tests).
- Conduct literature reviews for comparative analysis and benchmarking.
- Skills Needed: Biology/biotech knowledge, research skills, basic bioinformatics understanding.
