ArticleScientific reports2018
Improved strategy for the curation and classification of kinases, with broad applicability to other eukaryotic protein groups.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- KiNext: a portable and scalable workflow for the identification and classification of protein kinases.BMC bioinformatics · 2024Article
- Fatty acid- and retinol-binding protein 6 does not control worm fatty acid content in Caenorhabditis elegans but might play a role in Haemonchus contortus parasitism.Parasites & vectors · 2023Article
- The transcriptome of Balamuthia mandrillaris trophozoites for structure-guided drug design.Scientific reports · 2021Article
- High-quality nuclear genome for Sarcoptes scabiei-A critical resource for a neglected parasite.PLoS neglected tropical diseases · 2020Article
- Expanded complement of Niemann-Pick type C2-like protein genes in Clonorchis sinensis suggests functions beyond sterol binding and transport.Parasites & vectors · 2020Article
- High-quality Schistosoma haematobium genome achieved by single-molecule and long-range sequencing.GigaScience · 2019Article
- Dauer signalling pathway model for Haemonchus contortus.Parasites & vectors · 2019Article
- Comparative bioinformatic analysis suggests that specific dauer-like signalling pathway components regulate Toxocara canis development and migration in the mammalian host.Parasites & vectors · 2019Article
- Interactive online application for the prediction, ranking and prioritisation of drug targets in Schistosoma haematobium.Parasites & vectors · 2018Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Despite the substantial amount of genomic and transcriptomic data available for a wide range of eukaryotic organisms, most genomes are still in a draft state and can have inaccurate gene predictions. To gain a sound understanding of the biology of an organism, it is crucial that inferred protein sequences are accurately identified and annotated. However, this can be challenging to achieve, particularly for organisms such as parasitic worms (helminths), as most gene prediction approaches do not account for substantial phylogenetic divergence from model organisms, such as Caenorhabditis elegans and Drosophila melanogaster, whose genomes are well-curated. In this paper, we describe a bioinformatic strategy for the curation of gene families and subsequent annotation of encoded proteins. This strategy relies on pairwise gene curation between at least two closely related species using genomic and transcriptomic data sets, and is built on recent work on kinase complements of parasitic worms. Here, we discuss salient technical aspects of this strategy and its implications for the curation of protein families more generally.
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