Bioinformatics Studies of Human Viruses

人类病毒的生物信息学研究

• 批准号: 10471119
• 负责人: John Spouge
• 金额: $ 16.98万
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10471119
• 关键词: 2019-nCoV; Back; Bioinformatics; Biological; COVID-19; COVID-19 pandemic; Cancer Patient; Computational algorithm; Country; Epidemic; Experimental Designs; Growth; HIV; HIV Infections; Herpesviridae; Human; Infection; Mathematics; Methods; MicroRNAs; Mutation; Pattern; Population; Population Growth; Recording of previous events; Reporting; Reproduction; SARS-CoV-2 variant; Sampling; Social Distance; Statistical Methods; Sum; Viral; Viremia; Virus; algorithmic methodologies; circular RNA; interest; reconstruction; simulation; virology

We developed a statistical method summarizing the mutational patterns in HIV sequences from early infection. We showed that the summary agreed with simulation results for an HIV population during early infection in a single host. We have also showed that to useful accuracies in feasible experimental designs, we can reconstruct features of the early population growth of an HIV infection in a single host. With an NCI collaborator, Dr Ziegelbauer, we previously reported on a statistical method that we developed for inferring whether herpesvirus miRNA motifs were overrepresented on human circular RNAs. We have refined and generalized the computer algorithm for the method to other biological situations where one wants to infer that one of the terms of a sum is "too large", e.g., whether a human circular RNA has "too many" instances of a herpesvirus miRNA motif relative to other circular RNAs, whether a particular column of a domain alignments from cancer patients contains "too many" mutations, etc. We have automated the calculation of the Malthusian parameter controlling the initial exponential growths of the COVID-19 epidemic in many countries. A basic formula from Wallinga & Lipsitch relates the basic reproduction number R0 of the COVID-19 to the Malthusian parameter.

我们开发了一种统计方法，总结了早期感染的HIV序列中的突变模式。我们表明，总结同意模拟结果的HIV人口在早期感染的单一主机。我们还表明，在可行的实验设计中，我们可以重建单个宿主中HIV感染的早期人口增长的特征。 与NCI的合作者Ziegelbauer博士一起，我们先前报道了一种统计方法，该方法用于推断疱疹病毒miRNA基序是否在人类环状RNA上过度表达。我们已经将该方法的计算机算法改进和推广到其他生物学情况，其中人们想要推断总和的一项“太大”，例如，人类环状RNA相对于其他环状RNA是否具有“太多”疱疹病毒miRNA基序的实例，来自癌症患者的结构域比对的特定列是否包含“太多”突变等。 我们已自动计算马尔萨斯参数，控制COVID-19疫情在许多国家的初始指数增长。Wallinga & Lipsitch的一个基本公式将COVID-19的基本繁殖数R 0与马尔萨斯参数联系起来。