skip to content

Department of Computer Science and Technology

Friday, 24 May, 2024 - 12:00 to 13:00
Mike Sikic, Genome Institute of Singapore
Lecture Theatre 2, Computer Laboratory, William Gates Building

This presentation will explore advancements in genomic research, starting with de novo assembly, where Šikić's lab leads with novel applications of long reads technology. Herro, an innovative AI-based error correction model, increases the accuracy of simplex nanopore reads up to two orders of magnitude, starting a new era of genome sequencing with long and ultra reads whose accuracy exceeds 99.95 %. The talk will also introduce GNNOME, the lab's pioneering GNN-driven de novo assembly tool, unlocking the potential to decode increasingly complex genomes across various ploidy and aneuploidy levels—a future lab goal.

In the second part, the talk will highlight the RNA 3D structure determination project. The lab has developed RiNALMo, the largest RNA language model with 650 million parameters. RiNALMo achieves previously unseen generalisation in downstream applications, such as secondary structure and splice site predictions.


Mile Šikić is the group leader at the Genome Institute of Singapore and a professor of computer science at the University of Zagreb, Croatia. Throughout his scientific career, he has specialized in developing algorithms and AI methods for genomics. His laboratory has created several cutting-edge tools, including the Racon consensus tool, the Raven de novo assembler, and the Edlib sequence aligner. Recently, the focus of his lab has shifted towards integrating AI into the de novo assembly process and innovating AI models to make RNA druggable.

In the initial decade of his career, Dr Šikić was engaged in various industry projects related to computer and mobile networks. He is an accomplished entrepreneur, having founded several ventures, including a hedge fund.

Hybrid: Meeting ID: 255 432 5137 Passcode: 360730
Seminar series: 
Artificial Intelligence Research Group Talks