Combining multiomics to develop new bioinformatics approaches for personalized medicine

识别导致人类疾病的基因和遗传变异并解释它们在生物网络中的功能是走向个性化医学和发现新的生物标记物的关键一步。来自各个研究小组的DNA测序项目和英国基因组学的100K基因组计划正在提供史无前例的DNA测序数据，需要对其进行分析，以获得具有生物学意义的信息。这项任务不能人工完成，需要计算资源。最近在使用AlphaFold进行3D蛋白质建模领域的重大进展，以及关于人类和模型生物中基因表达的空前丰富的信息，使得多重组学被广泛用于开发新的预测算法，这些算法将识别可能扰乱蛋白质功能/结构和生物途径的基因和遗传变异。在这个项目中，您将利用可用的信息，关于基因表达，蛋白质相互作用，以及由内部Phyre2同源建模软件和/或深度学习算法AlphaFold实验确定或建模的三维蛋白质结构数据。你将把这些与多组学数据结合起来，开发出新的强大的生物信息学算法，用于预测基因变异的影响，并识别人类疾病的新候选基因。你将把这些新的生物信息学方法应用于基因组和临床数据，以解释它们的生物相关性。你将有机会开发有效的可视化网络工具，使这些新算法可供生物医学界使用。您将与临床医生密切合作，设计定制的方法，以确保这些新的生物信息资源在临床上的有效利用。

The identification of genes and genetic variants responsible for human disease and the interpretation of their function within a biological network is a crucial step towards personalized medicine and the discovery of novel biomarkers. DNA sequencing projects from individual research groups and the 100K Genomes Project at Genomics England are providing an unprecedented amount of DNA sequencing data that need to be analysed, to derive biologically meaningful information. This task cannot be performed manually and requires computational resources.Recent major developments in the field of 3D protein modeling withAlphaFold, and the unprecedent wealth of information now available on gene expression in human and model organisms, are allowing an expandeduse of multiomics for developing new prediction algorithms that will identify genes and genetic variants, which may disrupt protein function/structureand biological pathways.In this project you will exploit available information on gene expression,protein-protein interaction, and three-dimensional protein structure dataexperimentally determined or modelled by the in-house Phyre2 homologymodeling software and/or the deep learning algorithm AlphaFold. You willintegrate these with multi omics data to develop new robust bioinformaticsalgorithms for predicting the effect of genetic variants and identifying newcandidate genes for human disease. You will apply these new bioinformaticsapproaches to genomic and clinical data to interpret their biologicalrelevance. You will have the opportunity to develop effective visualisationweb tools to make these new algorithms available to the biomedicalcommunity. You will work closely with clinicians to design bespokeapproaches to ensure the effective clinical utilization of these newbioinformatic resources.