Evidence map›Paper›PMID 35881697›Full record

ArticleBioinformatics (Oxford, England)2022

Automatic DNA replication tract measurement to assess replication and repair dynamics at the single-molecule level.

Longjie Li, Arun Mouli Kolinjivadi, Kok Haur Ong, David M Young, Gabriel Pik Liang Marini, Sock Hoai Chan, Siao Ting Chong, Ee Ling Chew, Haoda Lu, Laurent Gole and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

12 authors at 4 institutions in 2 countries.

Longjie LiInstitute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
Arun Mouli KolinjivadiLee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore.
Kok Haur OngInstitute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
David M YoungInstitute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
Gabriel Pik Liang MariniBioinformatics Institute, A*STAR, Singapore 138671, Singapore.
Sock Hoai ChanCancer Genetics Service, Division of Medical Oncology, National Cancer Centre, Singapore 169610, Singapore.
Siao Ting ChongLee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore.
Ee Ling ChewCancer Genetics Service, Division of Medical Oncology, National Cancer Centre, Singapore 169610, Singapore.
Haoda LuBioinformatics Institute, A*STAR, Singapore 138671, Singapore.
Laurent GoleInstitute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
Weimiao YuInstitute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.ORCID 0000-0001-5092-1009
Joanne NgeowLee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore.
Agency for Science, Technology and Research · SGNanyang Technological University · SGDuke-NUS Medical School · SGNational Cancer Centre Singapore · SG

Funding

Ministry of Education, Singapore, Academic Research Fund Tier 1 2019-T1-001-018Nanyang Technological University Start-UpNational Cancer Centre Research Fund Terry Fox Grant NCCRF-YR2018-NOV-1National Research Foundation Singapore, Clinician Scientist NMRC/CSA-INV/0017/2017Singapore Ministry of Health's National Medical Research Council
6 · The paper itself

Abstract

motivationDNA fibre assay has a potential application in genomic medicine, cancer and stem cell research at the single-molecule level. A major challenge for the clinical and research implementation of DNA fibre assays is the slow speed in which manual analysis takes place as it limits the clinical actionability. While automatic detection of DNA fibres speeds up this process considerably, current publicly available software have limited features in terms of their user interface for manual correction of results, which in turn limit their accuracy and ability to account for atypical structures that may be important in diagnosis or investigative studies. We recognize that core improvements can be made to the GUI to allow for direct interaction with automatic results to preserve accuracy as well as enhance the versatility of automatic DNA fibre detection for use in variety of situations.

resultsTo address the unmet needs of diverse DNA fibre analysis investigations, we propose DNA Stranding, an open-source software that is able to perform accurate fibre length quantification (13.22% mean relative error) and fibre pattern recognition (R > 0.93) with up to six fibre patterns supported. With the graphical interface, we developed, user can conduct semi-automatic analyses which benefits from the advantages of both automatic and manual processes to improve workflow efficiency without compromising accuracy. AVAILABILITY AND IMPLEMENTATION: The software package is available at https://github.com/lgole/DNAStranding. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

DNASoftwareDNA ReplicationWorkflowDNA

Identifiers

PMID35881697
PMCPMC9477523
OpenAlexW4288037232

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.