Malaria is a mosquito-borne disease caused by single-celled blood parasites of the genus Plasmodium. The most severe cases of this disease are caused by the Plasmodium species, Falciparum. Once infected, a human host experiences symptoms of recurrent and intermittent fevers occurring over a time-frame of 48 hours, attributed to the synchronized developmental cycle of the parasite during the blood stage. To understand the regulated periodicity of Plasmodium falciparum transcription, this paper forecast and predict the P. falciparum gene transcription during its blood stage life cycle implementing a well-tuned recurrent neural network with gated recurrent units. Additionally, we also employ a spiking neural network to predict the expression levels of the P. falciparum gene. We provide results of this prediction on multiple genes including potential genes that express possible drug target enzymes. Our results show a high level of accuracy in being able to predict and forecast the expression levels of the different genes.

疟疾是一种由蚊子传播的疾病，由该属的单细胞血液寄生虫引起 疟原虫. 这种疾病最严重的病例是由疟原虫 物种， 恶性疟原虫. 一旦被感染，人类宿主会在 48 小时内出现反复和间歇性发烧的症状，这归因于寄生虫在血液阶段的同步发育周期。了解调节周期恶性疟原虫 转录，本文预测和预测 恶性疟原虫在其血液阶段生命周期中的基因转录实现了一个带有门控循环单元的经过良好调整的循环神经网络。此外，我们还使用尖峰神经网络来预测恶性疟原虫基因。我们提供了对多个基因的预测结果，包括表达可能的药物靶标酶的潜在基因。我们的结果表明，能够预测和预测不同基因的表达水平具有高度的准确性。