Browsing by Author "Mutlu, Onur"

Now showing items 1-7 of 7

    • Accelerating genome analysis: a primer on an ongoing journey 

      Alser, M.; Zülal, Bingöl; Cali, D. S.; Kim, J.; Ghose, S.; Alkan, Can; Mutlu, Onur (IEEE, 2020)
      Genome analysis fundamentally starts with a process known as read mapping, where sequenced fragments of an organism's genome are compared against a reference genome. Read mapping is currently a major bottleneck in the ...

    • Apollo: A sequencing-technology-independent, scalable and accurate assembly polishing algorithm 

      Fırtına, C.; Kim, J. S.; Alser, M.; Şenol Cali, D.; Çiçek, A. Ercüment; Alkan, Can; Mutlu, Onur (Oxford University Press, 2020-03)
      Motivation: Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further ...

    • FastRemap: a tool for quickly remapping reads between genome assemblies 

      Kim, J. S.; Firtina, C.; Cavlak, M. B.; Cali, D. S.; Alkan, Can; Mutlu, Onur (Oxford University Press, 2022-08-17)
      Motivation: A genome read dataset can be quickly and efficiently remapped from one reference to another similar reference (e.g., between two reference versions or two similar species) using a variety of tools, e.g., the ...

    • GateKeeper-GPU: fast and accurate pre-alignment filtering in short read mapping 

      Bingöl, Zülal; Alser, Mohammed; Mutlu, Onur; Öztürk, Özcan; Alkan, Can (IEEE, 2021-06-24)
      We introduce GateKeeper-GPU, a fast and accurate pre-alignment filter that efficiently reduces the need for expensive sequence alignment. GateKeeper-GPU improves the filtering accuracy of GateKeeper, and by exploiting the ...

    • GenASM: a high-performance, low-power approximate string matching acceleration framework for genome sequence analysis 

      Şenol-Çalı, D.; Kalsi, G. S.; Bingöl, Zülal; Fırtına, C.; Subramanian, L.; Kim, J. S.; Ausavarungnirun, R.; Alser, M.; Gomez-Luna, J.; Boroumand, A.; Norion, A.; Scibisz, A.; Subramoneyon, S.; Alkan, Can; Ghose, S.; Mutlu, Onur (IEEE Computer Society, 2020)
      Genome sequence analysis has enabled significant advancements in medical and scientific areas such as personalized medicine, outbreak tracing, and the understanding of evolution. To perform genome sequencing, devices extract ...

    • Shouji: a fast and efficient pre-alignment filter for sequence alignment 

      Alser, Mohammed; Hassan, H.; Kumar, A.; Mutlu, Onur; Alkan, Can (Oxford University Press, 2019)
      The ability to generate massive amounts of sequencing data continues to overwhelm the processing capability of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design ...

    • Technology dictates algorithms: recent developments in read alignment 

      Alser, Mohammed; Rotman, J.; Deshpande, D.; Taraszka, K.; Shi, H.; Baykal, P. I.; Yang, H. T.; Xue, V.; Knyazev, S.; Singer, B. D.; Balliu, B.; Koslicki, D.; Skums, P.; Zelikovsky, A.; Alkan, Can; Mutlu, Onur; Mangul, S. (BioMed Central, 2021-08-26)
      Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to ...