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ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-efficient Genome Analysis., , , , , , , , , and 3 other author(s). ACM Trans. Archit. Code Optim., 21 (1): 19:1-19:29 (March 2024)TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering., , , , , , , , and . CoRR, (2022)AirLift: A Fast and Comprehensive Technique for Remapping Alignments between Reference Genomes., , , , , , , and . CoRR, (2019)ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis., , , , , , , , , and 3 other author(s). CoRR, (2022)MetaStore: High-Performance Metagenomic Analysis via In-Storage Computing., , , , , , , , , and 2 other author(s). CoRR, (2023)SeGraM: a universal hardware accelerator for genomic sequence-to-graph and sequence-to-sequence mapping., , , , , , , , , and 8 other author(s). ISCA, page 638-655. ACM, (2022)FastRemap: a tool for quickly remapping reads between genome assemblies., , , , , and . Bioinform., 38 (19): 4633-4635 (2022)RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes., , , , , , and . Bioinform., 39 (Supplement-1): 297-307 (2023)A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers., , , , , , , and . CoRR, (2022)RowPress: Amplifying Read Disturbance in Modern DRAM Chips., , , , , , , , and . ISCA, page 28:1-28:18. ACM, (2023)