Evidence map›Paper›PMID 35473587›Full record

ArticleAlgorithms for molecular biology : AMB2022

Efficient privacy-preserving variable-length substring match for genome sequence.

Yoshiki Nakagawa, Satsuya Ohata, Kana Shimizu

Abstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yoshiki NakagawaDepartment of Computer Science and Engineering, Waseda University, Tokyo, Japan.
Satsuya OhataSelf-employment, Tokyo, Japan.
Kana ShimizuDepartment of Computer Science and Engineering, Waseda University, Tokyo, Japan. shimizu.kana@waseda.jp.

Funding

JST CREST JPMJCR19F6MEXT/JSPS KAKENHI 19K12209MEXT/JSPS KAKENHI 21H04871/21H05052
6 · The paper itself

Abstract

The development of a privacy-preserving technology is important for accelerating genome data sharing. This study proposes an algorithm that securely searches a variable-length substring match between a query and a database sequence. Our concept hinges on a technique that efficiently applies FM-index for a secret-sharing scheme. More precisely, we developed an algorithm that can achieve a secure table lookup in such a way that [Formula: see text] is computed for a given depth of recursion where [Formula: see text] is an initial position, and V is a vector. We used the secure table lookup for vectors created based on FM-index. The notable feature of the secure table lookup is that time, communication, and round complexities are not dependent on the table length N, after the query input. Therefore, a substring match by reference to the FM-index-based table can also be conducted independently against the database length, and the entire search time is dramatically improved compared to previous approaches. We conducted an experiment using a human genome sequence with the length of 10 million as the database and a query with the length of 100 and found that the query response time of our protocol was at least three orders of magnitude faster than a non-indexed database search protocol under the realistic computation/network environment.

Indexed as

FM-indexLCP arrayMaximal exact matchPrivate genome sequence searchSecret sharingSecure multiparty computationSuffix array

Identifiers

PMID35473587
PMCPMC9040336

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.