DIPER: Detection and Identification of Pathogens using Edit distance-tolerant Resistive CAM

Itay Merlin; Esteban Garzon; Alex Fish; Leonid Yavits

doi:10.1109/TC.2023.3315829

DIPER: Detection and Identification of Pathogens using Edit distance-tolerant Resistive CAM

Itay Merlin, Esteban Garzon, Alex Fish, Leonid Yavits

Bar-Ilan University

Research output: Contribution to journal › Article › peer-review

Abstract

We propose a novel resistive edit distance-tolerant content addressable memory for computational genomics applications, particularly for detection and identification of pathogens of pandemic importance. Unlike state-of-the-art approximate search solutions that tolerate small number of replacements between the query pattern and the stored data, DIPER tolerates insertions and deletions, ubiquitous in genomics. DIPER achieves up to 1.7× higher <italic>F</italic>₁ score for high-quality DNA reads and up to 6.2× higher <italic>F</italic>₁ score for DNA reads with 15% error rate, compared to state-of-the-art DNA classification tool Kraken2. Simulated at 500MHz, DIPER provides 910× average speedup over Kraken2.

Original language	American English
Pages (from-to)	1-12
Number of pages	12
Journal	IEEE Transactions on Computers
Volume	73
Issue number	10
DOIs	https://doi.org/10.1109/TC.2023.3315829
State	Published - 2024

Keywords

Bioinformatics
DNA
DNA detection and classification
Genomics
Hamming distances
Pandemics
Pathogens
Sequential analysis
approximate search
content addressable memory
memristors
resistive memory

All Science Journal Classification (ASJC) codes

Software
Theoretical Computer Science
Hardware and Architecture
Computational Theory and Mathematics

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10.1109/TC.2023.3315829

Cite this

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title = "DIPER: Detection and Identification of Pathogens using Edit distance-tolerant Resistive CAM",

abstract = "We propose a novel resistive edit distance-tolerant content addressable memory for computational genomics applications, particularly for detection and identification of pathogens of pandemic importance. Unlike state-of-the-art approximate search solutions that tolerate small number of replacements between the query pattern and the stored data, DIPER tolerates insertions and deletions, ubiquitous in genomics. DIPER achieves up to 1.7× higher F1 score for high-quality DNA reads and up to 6.2× higher F1 score for DNA reads with 15% error rate, compared to state-of-the-art DNA classification tool Kraken2. Simulated at 500MHz, DIPER provides 910× average speedup over Kraken2.",

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AU - Merlin, Itay

AU - Garzon, Esteban

AU - Fish, Alex

AU - Yavits, Leonid

N1 - Publisher Copyright: Author

PY - 2024

Y1 - 2024

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KW - Hamming distances

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KW - Pathogens

KW - Sequential analysis

KW - approximate search

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KW - memristors

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JF - IEEE Transactions on Computers

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DIPER: Detection and Identification of Pathogens using Edit distance-tolerant Resistive CAM

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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