In silico-driven analysis of the

Consolata Gakii, Billiah Kemunto Bwana, Grace Gathoni Mugambi, Esther Mukoya, Paul O Mireji, Richard Rimiru

Abstract read

In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

3 citing papers in PubMed.

Genome and transcriptome-based identification and expression profiling of chemosensory gene families across developmental stages and tissues in Sirex noctilio (Hymenoptera: Siricidae).Insect molecular biology · 2026
Article
VectorBase.org updates: bioinformatic resources for invertebrate vectors of human pathogens and related organisms.Current opinion in insect science · 2022
Review
Annotations of novel antennae-expressed genes in male Glossina morsitans morsitans tsetse flies.PloS one · 2022
Article

4 · The record

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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

6 authors.

Consolata GakiiDepartment of Mathematics, Computing and Information Technology, University of Embu, Embu, Eastern, Kenya.

Billiah Kemunto BwanaDepartment of Biological Sciences, University of Embu, Embu, Eastern, Kenya.

Grace Gathoni MugambiSchool of Computing and Information Technology, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Nairobi, Kenya.

Esther MukoyaSchool of Computing and Information Technology, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Nairobi, Kenya.

Paul O MirejiBiotechnology Research Center, Kenya Agricultural & Livestock Research Organization, Nairobi, Nairobi, Kenya.

Richard RimiruSchool of Computing and Information Technology, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-throughput sequencing generates large volumes of biological data that must be interpreted to make meaningful inference on the biological function. Problems arise due to the large number of characteristics METHODOLOGY: In this study we analyzed the transcriptome of RESULTS AND DISCUSSION: Among the significantly expressed chemosensory genes (FDR < 0.05) in response to Ɛ-nonalactone were gustatory receptors (GrIA and Gr28b), ionotrophic receptors (Ir41a and Ir75a), odorant binding proteins (Obp99b, Obp99d, Obp59a and Obp28a) and the odorant receptor (Or67d). Several non-chemosensory genes with no assigned function in the NCBI database were co-expressed with the chemosensory genes. Exposure to a repellent (δ-nonalactone) did not show any significant change between the treatment and control samples. We generated a coexpression network with 276 edges and 130 nodes. Genes CAH3, Ahcy, Ir64a, Or67c, Ir8a and Or67a had node degree values above 11 and therefore could be regarded as the top hub genes in the network. Association rule mining showed a relation between various genes based on their appearance in the same itemsets as consequent and antecedent.

Indexed as

Association rule miningCo-expression networkDiscretizationIn silico analysisRNASeq data

Identifiers

PMID34249514

DOI10.7717/peerj.11691

PMCPMC8255069

What OpenQuestion holds

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LicenceCC BY

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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.