Gene Regulatory Networks (GRN) produce powerful insights into transcriptional regulation in cells. The power of GRNs has been underutilized in malaria research. The Arboreto library was incorporated into a user-friendly web-based application for malaria researchers ( http://malboost.bi.up.ac.za ). This application will assist researchers with gaining an in depth understanding of transcriptomic datasets. The web application for MALBoost was built in Python-Flask with Redis and Celery workers for queue submission handling, which execute the Arboreto suite algorithms. A submission of 5–50 regulators and total expression set of 5200 genes is permitted. The program runs in a point-and-click web user interface built using Bootstrap4 templates. Post-analysis submission, users are redirected to a status page with run time estimates and ultimately a download button upon completion. Result updates or failure updates will be emailed to the users. A web-based application with an easy-to-use interface is presented with a use case validation of AP2-G and AP2-I. The validation set incorporates cross-referencing with ChIP-seq and transcriptome datasets. For AP2-G, 5 ChIP-seq targets were significantly enriched with seven more targets presenting with strong evidence of validated targets. The MALBoost application provides the first tool for easy interfacing and efficiently allows gene regulatory network construction for Plasmodium. Additionally, access is provided to a pre-compiled network for use as reference framework. Validation for sexually committed ring-stage parasite targets of AP2-G, suggests the algorithm was effective in resolving “traditionally” low-level signatures even in bulk RNA datasets.

中文翻译：

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MALBoost：恶性疟原虫基因调控网络分析的基于网络的应用程序

基因调控网络 (GRN) 对细胞中的转录调控产生了强大的洞察力。GRN 的力量在疟疾研究中没有得到充分利用。Arboreto 库被整合到一个用户友好的基于 Web 的应用程序中，供疟疾研究人员使用 (http://malboost.bi.up.ac.za)。此应用程序将帮助研究人员深入了解转录组数据集。MALBoost 的 Web 应用程序是在 Python-Flask 中构建的，Redis 和 Celery 工作者用于队列提交处理，它们执行 Arboreto 套件算法。允许提交 5-50 个调节子和 5200 个基因的总表达集。该程序在使用 Bootstrap4 模板构建的点击式 Web 用户界面中运行。分析后提交，用户被重定向到带有运行时间估计的状态页面，并在完成后最终出现一个下载按钮。结果更新或失败更新将通过电子邮件发送给用户。一个基于 Web 的应用程序具有易于使用的界面，并带有 AP2-G 和 AP2-I 的用例验证。验证集结合了 ChIP-seq 和转录组数据集的交叉引用。对于 AP2-G，5 个 ChIP-seq 目标显着丰富，另外 7 个目标提供了验证目标的有力证据。MALBoost 应用程序提供了第一个易于连接的工具，并有效地实现了疟原虫基因调控网络的构建。此外，还提供对预编译网络的访问以用作参考框架。验证 AP2-G 的性犯罪环状阶段寄生虫目标，