Evidence map›Paper›PMID 36685727›Full record

ArticleNAR genomics and bioinformatics2023

BLEND: a fast, memory-efficient and accurate mechanism to find fuzzy seed matches in genome analysis.

Can Firtina, Jisung Park, Mohammed Alser, Jeremie S Kim, Damla Senol Cali, Taha Shahroodi, Nika Mansouri Ghiasi, Gagandeep Singh, Konstantinos Kanellopoulos, Can Alkan and 1 more

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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

11 authors.

Can FirtinaETH Zurich, Zurich 8092, Switzerland.ORCID https://orcid.org/0000-0002-6548-7863
Jisung ParkETH Zurich, Zurich 8092, Switzerland.
Mohammed AlserETH Zurich, Zurich 8092, Switzerland.
Jeremie S KimETH Zurich, Zurich 8092, Switzerland.ORCID https://orcid.org/0000-0001-6153-9008
Damla Senol CaliCarnegie Mellon University, Pittsburgh, PA 15213, USA.
Taha ShahroodiTU Delft, 2600 AA Delft, Netherlands.
Nika Mansouri GhiasiETH Zurich, Zurich 8092, Switzerland.
Gagandeep SinghETH Zurich, Zurich 8092, Switzerland.
Konstantinos KanellopoulosETH Zurich, Zurich 8092, Switzerland.
Can AlkanBilkent University, Ankara 06800, Turkey.ORCID https://orcid.org/0000-0002-5443-0706
Onur MutluETH Zurich, Zurich 8092, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values. However, these hash values can be used only for finding exact-matching seeds as the conventional hashing methods assign distinct hash values for different seeds, including highly similar seeds. Finding only exact-matching seeds causes either (i) increasing the use of the costly sequence alignment or (ii) limited sensitivity. We introduce

Identifiers

PMID36685727
PMCPMC9853099

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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.