alex-sneddon.bsky.social
@alex-sneddon.bsky.social
Research Fellow @ Australian National University @ ARC CoE MACSYS
• Machine learning • RNA • Nanopore sequencing • Epitranscriptomics
• Machine learning • RNA • Nanopore sequencing • Epitranscriptomics
New preprint 🚀 We uncover and correct systematic bias in nanopore-based RNA modification detection. ModkitOpt optimises pipelines using validated sites, increasing true positives while reducing unvalidated calls across contexts.
💻: github.com/comprna/modk...
📄: www.biorxiv.org/content/10.6...
💻: github.com/comprna/modk...
📄: www.biorxiv.org/content/10.6...
Resolving systematic bias in nanopore-based RNA modification detection
Nanopore direct RNA sequencing has accelerated the growth of the epitranscriptomics field, yet nanopore-based RNA modification landscapes are generally unreliable due to the heuristic and unvalidated ...
www.biorxiv.org
January 8, 2026 at 7:22 AM
New preprint 🚀 We uncover and correct systematic bias in nanopore-based RNA modification detection. ModkitOpt optimises pipelines using validated sites, increasing true positives while reducing unvalidated calls across contexts.
💻: github.com/comprna/modk...
📄: www.biorxiv.org/content/10.6...
💻: github.com/comprna/modk...
📄: www.biorxiv.org/content/10.6...
From last year: a short video from the ARC Centre of Excellence MACSYS @macsys.bsky.social where I talk about my research on bringing domain knowledge into data-driven AI methods for complex biology
Meet Dr Alex Sneddon - a MACSYS Research Fellow at The Australian National University. Alex's research focuses on incorporating domain-specific knowledge into the data-driven AI methods that she uses to help MACSYS unlock insights from complex biological datasets.
📹VIDEO: youtu.be/GVsMQ0E3Aok
📹VIDEO: youtu.be/GVsMQ0E3Aok
Dr Alex Sneddon - MACSYS Research Fellow, ANU
YouTube video by MACSYS
youtu.be
January 8, 2026 at 4:45 AM
From last year: a short video from the ARC Centre of Excellence MACSYS @macsys.bsky.social where I talk about my research on bringing domain knowledge into data-driven AI methods for complex biology