Post-doctoral Research Projects at Imperial College London (ICL)

DNA Storage technology Research and Development

At SCALE lab, and with our collaborators in Europe, I worked researching and developing the technologies and algorithms central to the nascent high-capacity storage technology which utilises DNA as a storage medium. This new technology has the potential to overcome the limitations of current storage mediums, has the capacity to store vast amounts of data per unit volume (theoretically 455 EB/g) and provides a medium that could be stable for thousands of years when desiccated and chilled in storage.

• Alnasir, J., Heinis, T., Sokolovskii, R (2023). Survey of Information Encoding Techniques for DNA. arXiv.org, Cornell University. [ ACM Comp. Surveys ]

• Alnasir, J (2021). Encoding information into DNA. Mathematical Foundations in Bioinformatics (MatBio '21), King's College London. [ MatBio '21 Slides ]

• Alnasir, J. (2021). DNA Storage Error Simulator: A Tool for Simulating Errors in Synthesis, Storage, PCR and Sequencing. bioRxiv, Cold Spring Harbor Laboratory. [ preprint ]

Pipeline for discovering viral insertions in 100,000 genomes UK

I ran a large-scale genomic analysis using the pipeline I developed to discover viral insertions in the UK 100,000 genomes project. Having identified an existing attempted solution as unfit for purpose, I architected and implemented a distributed HPC (High-Performance Computing) genomics pipeline to search for viral insertions into human genomes. This work is in accordance with the Genomics England Clinical Interpretation Partnership (GeCIP), an international consortium of researchers, clinicians and trainees, established to improve understanding and practice of clinical genomics, and uncover new medical insights for patients. I am a GeCIP member working at Imperial using Genomics Englands infrastructure and data sets, particularly the 100K genomes.

• Alnasir, J. (2021). Fifteen quick tips for success with HPC, i.e., responsibly BASHing that Linux cluster. PLOS Computational Biology, Cambridge. [ Read ]

COVID-19 Research

I have actively contributed to the COVID-19 research effort. Specifically, my focus is on the application of distributed computing architectures (i.e. supercomputing & high-performance computing, grid and cloud computing) for COVID-19 research tasks. My research paper on this — Distributed Computing in a Pandemic: A Review of Technologies Available for Tackling COVID-19 — has been accepted for publication in a distributed computing journal. It comprehensively surveys the use of such architectures, their configurations and the tasks they can be applied to, as well as providing guidance for conducting such research and applying it to future work. To this end, I have also published technical guidance on the use of HPC (High-Performance Computing) infrastructure in my recent paper: Fifteen quick tips for success with HPC, i.e., responsibly BASHing that Linux cluster. This has been published in the top journal PLOS Computational Biology, Cambridge.

Distributed Computing in a Pandemic

• Alnasir, J. (2020). Distributed Computing in a Pandemic: A Review of Technologies available for Tackling COVID-19. ADCAIJ (Advances in Distributed Computing and Artificial Intelligence Journal), 11(1) (recently accepted). [ ADCAIJ ]