Advancing machine learning applications in synthetic biology: The TIPs fellowship training spotlight

The first TIPs fellowship training spotlight

At the forefront of our mission to integrate computational intelligence with biotechnology, the Translator Interpreter Pre-seeding (TIPs) initiative is building practical pipelines for representing and processing genetic sequences for machine learning applications. This year, TIPs has welcomed a team of fellows who are applying the platform to address key research challenges in genomics, synthetic biology, and biomedical discovery.

Through hands-on mentorship, structured training, and targeted research objectives, the fellows are advancing projects that strengthen the foundation of TIPs’ approach to data encoding, predictive analytics, and biological insight generation.

Projects driving the fellowship

The three fellows in this cohort bring diverse expertise and research interests, but share a common focus: to leverage TIPs’ encoding schemes in real-world machine learning applications.

1. Gene fusion prediction for biomedical discovery: Claudine is applying TIPs to detect and predict disease-related gene fusions, including those linked to lung cancer, diabetes, and rheumatoid arthritis. Her work aims to move beyond manual curation, advancing automated genomic diagnostics to support next-generation biomedical research.

2. Plasmid vector representation and domain prediction: Eiroll is mapping and analyzing plasmid vectors—critical tools in molecular cloning and synthetic biology. Using TIPs and machine learning methods, he aims to create a predictive interactive map that supports vector selection for specific recombinant cloning strategies.

3. Viral genome analysis and variant prediction: Shynne is focusing on viral genome sequence representation to enhance variant prediction accuracy. Her goal is to provide computational tools that aid in early detection and monitoring of viral mutations, contributing to public health preparedness.

Why this matters?

By combining the computational power of TIPs with the creativity and expertise of its fellows, the program is helping to expand the frontiers of synthetic biology, not only in the Philippines but across various domains globally. The research outcomes are expected to contribute to more accurate predictions, faster experimental design, and greater accessibility of advanced bioinformatics tools for local and global researchers.

About TIPs training

The TIPs Training Program offers structured learning and project-based mentorship in bioinformatics, machine learning, and synthetic biology applications. Fellows gain direct experience in applying TIPs encoding schemes to high-impact research challenges, building both technical skills and domain expertise.