Evidence map›Paper›PMID 39867462›Full record

ArticleData mining and knowledge discovery2025

Missing value replacement in strings and applications.

Giulia Bernardini, Chang Liu, Grigorios Loukides, Alberto Marchetti-Spaccamela, Solon P Pissis, Leen Stougie, Michelle Sweering

Abstract read
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In one paragraph

Article in Data mining and knowledge discovery, 2025. 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
–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

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

7 authors.

Giulia BernardiniDepartment of Mathematics, Informatics and Geosciences, University of Trieste, Trieste, Italy.
Chang LiuMedical Center, Zhejiang University, Zhejiang, China.
Grigorios LoukidesDepartment of Informatics, King's College London, London, UK.
Alberto Marchetti-SpaccamelaDepartment of Computer, Automatic and Management Engineering, La Sapienza University of Rome, Rome, Italy.
Solon P PissisCWI, Amsterdam, The Netherlands.
Leen StougieCWI, Amsterdam, The Netherlands.
Michelle SweeringCWI, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Missing values arise routinely in real-world sequential (string) datasets due to: (1) imprecise data measurements; (2) flexible sequence modeling, such as binding profiles of molecular sequences; or (3) the existence of confidential information in a dataset which has been deleted deliberately for privacy protection. In order to analyze such datasets, it is often important to replace each missing value, with one or more

Indexed as

Forbidden patternsMissing value replacementString algorithmsString sanitization

Identifiers

PMID39867462
PMCPMC11754389

What OpenQuestion holds

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Registered trials

None linked

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.