Evidence map›Paper›PMID 39538127›Full record

ArticleBMC genomics2024

Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps.

Karthick Raja Arulprakasam, Janelle Wing Shan Toh, Herman Foo, Mani R Kumar, An-Nikol Kutevska, Emilia Emmanuelle Davey, Marek Mutwil, Guillaume Thibault

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Karthick Raja ArulprakasamSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.ORCID http://orcid.org/0000-0002-0403-2910
Janelle Wing Shan TohSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Herman FooSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Mani R KumarSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
An-Nikol KutevskaSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Emilia Emmanuelle DaveySchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Marek MutwilSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore. mutwil@ntu.edu.sg.ORCID http://orcid.org/0000-0002-7848-0126
Guillaume ThibaultSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore. thibault@ntu.edu.sg.ORCID http://orcid.org/0000-0002-7926-4812

Funding

Ministry of Education - Singapore MOET32020-0001Ministry of Education - Singapore MOET32022-0002Ministry of Education - Singapore RG96/22
6 · The paper itself

Abstract

In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze connectivity information from the full-texts and abstracts of 24,237 and 150,538 research publications concerning Caenorhabditis elegans and Drosophila melanogaster, respectively. This approach has effectively identified 200,219 and 1,194,587 interactions within the C. elegans and Drosophila biomaps, respectively. Utilizing Cytoscape Web, we have developed a searchable online biomaps that link relevant keywords to their corresponding PubMed IDs, thus providing seamless access to an extensive knowledge network encompassing C. elegans and Drosophila. Our work highlights the transformative potential of integrating artificial intelligence with bioinformatics to deepen our understanding of complex biological systems. By revealing the intricate web of relationships among key entities in C. elegans and Drosophila, we offer invaluable insights that promise to propel advancements in genetics, developmental biology, neuroscience, longevity, and beyond. We also provide details and discuss significant nodes within both biomaps, including the insulin/IGF-1 signaling (IIS) and the notch pathways. Our innovative methodology sets a robust foundation for future research aimed at unravelling complex biological networks across diverse organisms. The two databases are available at worm.bio-map.com and drosophila.bio-map.com.

Indexed as

Caenorhabditis elegansDrosophila melanogasterAnimalsComputational BiologyPublicationsSignal TransductionBiological databasesC. elegansComputational biologyData visualizationDrosophilaGenetic interactionsNatural language processingNetwork analysisProtein-protein interactionsText mining

Identifiers

PMID39538127
PMCPMC11562368

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.