We were very excited to celebrate two successful PhD defenses last Monday, November 11, 2024! We’d like to wish Lukas Breitwieser and Can Firtina a very warm congratulations on their achievements.
[You can read more on Lukas’s PhD defense and work here (link will be posted soon)]
Can’s thesis on “Enabling Fast, Accurate, and Efficient Real-Time Genome Analysis via New Algorithms and Techniques” made significant contributions to mitigating noise in sequencing data and analysis by [1] building a better understanding of the types of noise, and [2] developing new algorithms and techniques that can tolerate and reduce noise, thus allowing for accurate, scalable, and real-time analysis of sequencing data and enabling new applications in genome analysis.
The core contributions of Can’s thesis found solutions for different types of noise and enabled new innovative applications, including:
- BLEND addresses noise in basecalled sequencing data analysis by providing an effective hash-based search method for noise tolerance.
- RawHash targets noise in raw nanopore sequencing data to reduce noise and enable hash-based search for raw signals.
- RawHash2 improves our understanding of noise in raw nanopore signals, allowing for better noise reduction.
- Rawsamble enables a new application by overlapping raw nanopore signals to build assemblies without basecalling.
You can find all links to these works, below.
Future Directions:
Can is now on the job market for tenure-track faculty positions and research positions in industry. Going forward, he is interested in 1) improving end-to-end genome analysis using raw sequencing data by developing algorithms that analyze raw nanopore signals to use the analysis with and without basecalling, 2) designing fast and accurate algorithms for constructing reference-quality genome assemblies from scratch to make personalized genome analysis universally accessible, and 3) co-designing hardware and software for efficient genome analysis by leveraging emerging technologies to optimize performance and energy efficiency, enabling applications like real-time, in-the-field genomic analysis.
You can follow his activity and see what he’s up to on LinkedIn, X, Bluesky and his website.
Advisor: Onur Mutlu
Co-Examiners:
Reetuparna Das (University of Michigan)
Hasindu Gamaarachchi (UNSW Sydney)
Benjamin Langmead (Johns Hopkins University)
Heng Li (Harvard Medical School)
Chair: Janos Vörös
Can Firtina (defended 11 November 2024)
Thesis title: “Enabling Fast, Accurate, and Efficient Real-Time Genome Analysis via New Algorithms and Techniques”
[Slides (pdf) (pptx)]
Related PhD works:
For a full list of all Can’s contributions and all related links, see his website.
[1] “BLEND: a fast, memory-efficient and accurate mechanism to find fuzzy seed matches in genome analysis”, Can Firtina, Jisung Park, Mohammed Alser, Jeremie S Kim, Damla Senol Cali, Taha Shahroodi, Nika Mansouri Ghiasi, Gagandeep Singh, Konstantinos Kanellopoulos, Can Alkan, and Onur Mutlu
[Paper: NAR Genomics and Bioinformatics] [arXiv version] [BLEND code]
[2] “RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes”, Can Firtina, Nika Mansouri Ghiasi, Joel Lindegger, Gagandeep Singh, Meryem Banu Cavlak, Haiyu Mao, and Onur Mutlu, In Proceedings of the 31st Annual Conference on Intelligent Systems for Molecular Biology (ISMB) and the 22nd European Conference on Computational Biology (ECCB)
[Paper: Bioinformatics] [RawHash code]
[3] “RawHash2: Mapping Raw Nanopore Signals Using Hash-Based Seeding and Adaptive Quantization”, Can Firtina, Melina Soysal, Joël Lindegger, and Onur Mutlu
[Paper: Bioinformatics] [arXiv version] [RawHash2 code (integrated into the RawHash code)]
