Finding ciliary genes: a computational approach
Related Experiment Video
Updated: May 13, 2026

Artificial Intelligence Approaches to Assessing Primary Cilia
Published on: May 1, 2021
Johan Henriksson1, Brian P Piasecki, Kristina Lend
1Department of Biosciences and Nutrition, Center for Biosciences at NOVUM, Karolinska Institute, Huddinge, Sweden. mahogny@areta.org
Abstract:
In the nematode worm Caenorhabditis elegans and several other animal species, many ciliary genes are regulated by RFX (Regulatory Factor binding to the X-box) transcription factors (TFs), which bind to X-box promoter motifs and thereby directly activate ciliary gene expression. This setup (RFX TF/X-box/ciliary gene) makes it possible to search for novel ciliary gene candidates genome-wide by using the X-box promoter motif as a search parameter. We present a computational approach that (i) identifies and extracts from whole genomes genes and the corresponding promoter sequences and annotations; (ii) searches through promoters for regulatory sequence elements (like promoter motifs) by using training sets of known instances of these elements; (iii) scores (evaluates) and sorts all positive hits in a database; and (iv) outputs a list of candidate genes and promoters with a given regulatory sequence element. Evolutionary conservation across species (orthology) of genes, promoters, or regulatory sequence elements is used as an important strengthening feature during the overall search approach. Our computational approach is set up in a modular fashion: not every part needs to be used for a particular search effort. In principle, our approach has broad applications. It applies to any group of genes that share common (conserved) regulation through common (conserved) regulatory sequence elements.
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