ArticleNucleic acids research2020
Malaria.tools-comparative genomic and transcriptomic database for Plasmodium species.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Review
- Timing of dense granule biogenesis in asexual malaria parasites.Microbiology (Reading, England) · 2023Article
- Significance of RNA N6-methyladenosine regulators in the diagnosis and subtype classification of coronary heart disease using the Gene Expression Omnibus database.Frontiers in cardiovascular medicine · 2023Article
- CRISPR-Cas13 in malaria parasite: Diagnosis and prospective gene function identification.Frontiers in microbiology · 2023Review
- An update on cerebral malaria for therapeutic intervention.Molecular biology reports · 2022Review
- A reverse vaccinology approach on transmembrane carbonic anhydrases from Plasmodium species as vaccine candidates for malaria prevention.Malaria journal · 2022Article
- Hybrid Deep Learning Based on a Heterogeneous Network Profile for Functional Annotations ofInternational journal of molecular sciences · 2021Article
- Dual RNA Sequencing Meta-analysis inmSystems · 2021Article
- LSTrAP-Crowd: prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data.BMC biology · 2020Article
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Authors and funding
2 authors.
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Abstract
Malaria is a tropical parasitic disease caused by the Plasmodium genus, which resulted in an estimated 219 million cases of malaria and 435 000 malaria-related deaths in 2017. Despite the availability of the Plasmodium falciparum genome since 2002, 74% of the genes remain uncharacterized. To remedy this paucity of functional information, we used transcriptomic data to build gene co-expression networks for two Plasmodium species (P. falciparum and P. berghei), and included genomic data of four other Plasmodium species, P. yoelii, P. knowlesi, P. vivax and P. cynomolgi, as well as two non-Plasmodium species from the Apicomplexa, Toxoplasma gondii and Theileria parva. The genomic and transcriptomic data were incorporated into the resulting database, malaria.tools, which is preloaded with tools that allow the identification and cross-species comparison of co-expressed gene neighbourhoods, clusters and life stage-specific expression, thus providing sophisticated tools to predict gene function. Moreover, we exemplify how the tools can be used to easily identify genes relevant for pathogenicity and various life stages of the malaria parasite. The database is freely available at www.malaria.tools.
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