Evidence map›Paper›PMID 34162895›Full record

ArticleScientific reports2021

Genome assembly using quantum and quantum-inspired annealing.

A S Boev, A S Rakitko, S R Usmanov, A N Kobzeva, I V Popov, V V Ilinsky, E O Kiktenko, A K Fedorov

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
6.3field-weighted citation impact, top 3% of its field
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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. A primer for quantum computing and its applications to healthcare and biomedical research.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  8. Article
  9. Review
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  11. The Future of Drug Development with Quantum Computing.Methods in molecular biology (Clifton, N.J.) · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society, Interface · 2022
    Review
  18. Article
  19. Article
  20. 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

8 authors at 2 institutions in 1 country.

A S BoevRussian Quantum Center, Skolkovo, Moscow, 143025, Russia.
A S RakitkoGenotek ltd., Moscow, 105120, Russia.
S R UsmanovRussian Quantum Center, Skolkovo, Moscow, 143025, Russia.
A N KobzevaRussian Quantum Center, Skolkovo, Moscow, 143025, Russia.
I V PopovGenotek ltd., Moscow, 105120, Russia.
V V IlinskyGenotek ltd., Moscow, 105120, Russia.
E O KiktenkoRussian Quantum Center, Skolkovo, Moscow, 143025, Russia.
A K FedorovRussian Quantum Center, Skolkovo, Moscow, 143025, Russia. akf@rqc.ru.
Russian Quantum Center · RUMoscow Institute of Physics and Technology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in DNA sequencing open prospects to make whole-genome analysis rapid and reliable, which is promising for various applications including personalized medicine. However, existing techniques for de novo genome assembly, which is used for the analysis of genomic rearrangements, chromosome phasing, and reconstructing genomes without a reference, require solving tasks of high computational complexity. Here we demonstrate a method for solving genome assembly tasks with the use of quantum and quantum-inspired optimization techniques. Within this method, we present experimental results on genome assembly using quantum annealers both for simulated data and the [Formula: see text]X 174 bacteriophage. Our results pave a way for a significant increase in the efficiency of solving bioinformatics problems with the use of quantum computing technologies and, in particular, quantum annealing might be an effective method. We expect that the new generation of quantum annealing devices would outperform existing techniques for de novo genome assembly. To the best of our knowledge, this is the first experimental study of de novo genome assembly problems both for real and synthetic data on quantum annealing devices and quantum-inspired techniques.

Indexed as

AlgorithmsBacteriophage phi X 174Computational BiologyComputer SimulationDatasets as TopicDNA, ViralGenome, ViralGenomicsHumansMathematicsQuantum TheorySequence Analysis, DNADNA, Viral

Identifiers

PMID34162895
PMCPMC8222255
OpenAlexW3016448351

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.