Evidence map›Paper›PMID 38989623›Full record

ArticleNucleic acids research2024

CilioGenics: an integrated method and database for predicting novel ciliary genes.

Mustafa S Pir, Efe Begar, Ferhan Yenisert, Hasan C Demirci, Mustafa E Korkmaz, Asli Karaman, Sofia Tsiropoulou, Elif Nur Firat-Karalar, Oliver E Blacque, Sukru S Oner and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. 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.

  1. Primary cilia: sensors of biliary homeostasis and disease.Nature reviews. Gastroenterology & hepatology · 2026
    Review
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  20. Cilia and transcription: a mini review.Frontiers in cell and developmental biology · 2025
    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

13 authors.

Mustafa S PirRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.ORCID 0000-0002-4645-7626
Efe BegarDepartment of Molecular Biology and Genetics, Koc University, Istanbul 34450, Turkiye.
Ferhan YenisertRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.
Hasan C DemirciRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.
Mustafa E KorkmazRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.
Asli KaramanIstanbul Medeniyet University, Science and Advanced Technologies Research Center (BILTAM), 34700 Istanbul, Turkiye.
Sofia TsiropoulouSchool of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.
Elif Nur Firat-KaralarDepartment of Molecular Biology and Genetics, Koc University, Istanbul 34450, Turkiye.
Oliver E BlacqueSchool of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.
Sukru S OnerIstanbul Medeniyet University, Science and Advanced Technologies Research Center (BILTAM), 34700 Istanbul, Turkiye.
Osman DolucaIzmir University of Economics, Faculty of Engineering, Department of Biomedical Engineering, Izmir, Turkiye.
Sebiha CevikRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.
Oktay I KaplanRare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye.ORCID 0000-0002-8733-0920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uncovering the full list of human ciliary genes holds enormous promise for the diagnosis of cilia-related human diseases, collectively known as ciliopathies. Currently, genetic diagnoses of many ciliopathies remain incomplete (1-3). While various independent approaches theoretically have the potential to reveal the entire list of ciliary genes, approximately 30% of the genes on the ciliary gene list still stand as ciliary candidates (4,5). These methods, however, have mainly relied on a single strategy to uncover ciliary candidate genes, making the categorization challenging due to variations in quality and distinct capabilities demonstrated by different methodologies. Here, we develop a method called CilioGenics that combines several methodologies (single-cell RNA sequencing, protein-protein interactions (PPIs), comparative genomics, transcription factor (TF) network analysis, and text mining) to predict the ciliary capacity of each human gene. Our combined approach provides a CilioGenics score for every human gene that represents the probability that it will become a ciliary gene. Compared to methods that rely on a single method, CilioGenics performs better in its capacity to predict ciliary genes. Our top 500 gene list includes 258 new ciliary candidates, with 31 validated experimentally by us and others. Users may explore the whole list of human genes and CilioGenics scores on the CilioGenics database (https://ciliogenics.com/).

Indexed as

CiliaCiliopathiesDatabases, GeneticTranscription FactorsData MiningGenomicsHumansSingle-Cell AnalysisSoftwareTranscription Factors

Identifiers

PMID38989623
PMCPMC11317154

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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.