Evidence map›Paper›PMID 38468275›Full record

ArticleAlgorithms for molecular biology : AMB2024

Finding maximal exact matches in graphs.

Nicola Rizzo, Manuel Cáceres, Veli Mäkinen

Abstract read
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In one paragraph

Article in Algorithms for molecular biology : AMB, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nicola RizzoDepartment of Computer Science, University of Helsinki, Pietari Kalmin katu 5, P.O. Box 68, Helsinki, 00014, Finland. nicola.rizzo@helsinki.fi.ORCID http://orcid.org/0000-0002-2035-6309
Manuel CáceresDepartment of Computer Science, University of Helsinki, Pietari Kalmin katu 5, P.O. Box 68, Helsinki, 00014, Finland.ORCID http://orcid.org/0000-0003-0235-6951
Veli MäkinenDepartment of Computer Science, University of Helsinki, Pietari Kalmin katu 5, P.O. Box 68, Helsinki, 00014, Finland.ORCID http://orcid.org/0000-0003-4454-1493

Funding

Academy of Finland 352821H2020 Marie Skłodowska-Curie Actions 956229
6 · The paper itself

Abstract

backgroundWe study the problem of finding maximal exact matches (MEMs) between a query string Q and a labeled graph G. MEMs are an important class of seeds, often used in seed-chain-extend type of practical alignment methods because of their strong connections to classical metrics. A principled way to speed up chaining is to limit the number of MEMs by considering only MEMs of length at least

resultsIn this paper we show an

conclusionsWe show that seed-chain-extend type of alignment methods can be implemented on top of indexable Elastic Founder Graphs by providing an efficient way to produce the seeds between a set of queries and the graph. The code is available in https://github.com/algbio/efg-mems .

Indexed as

Bidirectional BWTFounder graphsr-indexSequence to graph alignmentSuffix tree

Identifiers

PMID38468275
PMCPMC10929130

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.