ArticlePLoS computational biology2019
Predicting gene expression in the human malaria parasite Plasmodium falciparum using histone modification, nucleosome positioning, and 3D localization features.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Chromatin state dynamics during the Plasmodium falciparum intraerythrocytic development cycle.BMC genomics · 2026Article
- Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma.PLoS computational biology · 2025Article
- Transcriptome analysis reveals a de novo DNA element that may interact with chromatin-associated proteins in Plasmodium berghei during erythrocytic development.Scientific reports · 2025Article
- A quantitative benchmark of neural network feature selection methods for detecting nonlinear signals.Scientific reports · 2024Article
- Epigenetic Regulation and Chromatin Remodeling in Malaria Parasites.Annual review of microbiology · 2023Review
- Novel insights into the role of long non-coding RNA in the human malaria parasite, Plasmodium falciparum.Nature communications · 2023Article
- The role of long noncoding RNAs in malaria parasites.Trends in parasitology · 2023Review
- Inhibitors of ApiAP2 protein DNA binding exhibit multistage activity against Plasmodium parasites.PLoS pathogens · 2022Article
- Predicting which genes will respond to transcription factor perturbations.G3 (Bethesda, Md.) · 2022Article
- Histone Modification Landscapes as a Roadmap for Malaria Parasite Development.Frontiers in cell and developmental biology · 2022Review
- Differential contribution to gene expression prediction of histone modifications at enhancers or promoters.PLoS computational biology · 2021Article
- Peculiarities ofInternational journal of molecular sciences · 2021Review
- Identification of long regulatory elements in the genome of Plasmodium falciparum and other eukaryotes.PLoS computational biology · 2021Article
- Deep Learning Methods in Predicting Gene Expression Levels for the Malaria Parasite.Frontiers in genetics · 2021Article
- Dynamic Chromatin Structure and Epigenetics Control the Fate of Malaria Parasites.Trends in genetics : TIG · 2021Review
- From Genes to Transcripts, a Tightly Regulated Journey inFrontiers in cellular and infection microbiology · 2020Review
- The role of epigenetics and chromatin structure in transcriptional regulation in malaria parasites.Briefings in functional genomics · 2019Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Empirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organism's complex life cycle. To better understand this regulatory machinery, we assembled a rich collection of genomic and epigenomic data sets, including information about transcription factor (TF) binding motifs, patterns of covalent histone modifications, nucleosome occupancy, GC content, and global 3D genome architecture. We used these data to train machine learning models to discriminate between high-expression and low-expression genes, focusing on three distinct stages of the red blood cell phase of the Plasmodium life cycle. Our results highlight the importance of histone modifications and 3D chromatin architecture in Plasmodium transcriptional regulation and suggest that AP2 transcription factors may play a limited regulatory role, perhaps operating in conjunction with epigenetic factors.
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Registered trials
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