E Pluribus Unum: Understanding and Influencing Pluripotency & Reprogramming by Integrative Bioinformatics

继SPP资助开始以来的过去20个月中完成的工作，我们打算完成多能性机器学习，现在专注于数据挖掘和集成，基于我们的PluriNetWork和相关的ExprEssence软件，通过比较高通量数据集来建议多能性涉及的机制。我们将扩展小鼠多能基因/蛋白的PluriNetWork，并建立用于人类(和其他物种)的PluriNetWork，重点是转录调节、信号和表观遗传学。理解多能性和重新编程的基础是将不同的高通量数据集整合到我们的网络中，并识别可能的机制，比较a)不同的物种，b)不同的数据类型(蛋白质、rna、表观遗传学、…)。，和c)不同的干预措施和时间序列，多能性的不同状态(ICM、外胚层、iPS、…)&不同的重新编程方法(iPS、SCNT、Fusion)。我们在所有维度的分析中剖析多能性和重新编程，使用网络整合数据，并提出干预方案(整合小分子)。ExprEssence的差异分析是为了应对这些新任务而进一步发展的，包括。用于生成电影的组件，突出显示网络中沿所有维度的机制的启动和关闭。ExprEssence突出显示将因此确定要接受详细建模(TEIS)的子网络集合，它将支持Boiani、Greber、Meisternst、Hiirai、Schroeder、Tanaka、Besser、F.-J.Müler、A.Müler和Zenke，它也是SPP生物信息学帮助台未来的核心。

Following up on work accomplished in the past 20 months since SPP funding commenced, we intend to complete machine learning of pluripotency, now focusing on data mining & integration, based on our PluriNetWork, and associated ExprEssence software that suggests mechanisms involved in pluripotency, by comparing high-throughput datasets. We will expand the PluriNetWork of pluripotency genes/proteins in mouse, and establish it for human (& other species), focusing on transcriptional regulation, signaling & epigenetics. Understanding pluripotency & reprogramming is then based on integrating differential highthroughput datasets into our networks and identifying putative mechanisms, comparing a) different species, b) different data types (protein, RNA, epigenetics, …), and c) different interventions & time series, different states of pluripotency (ICM, Epiblast, iPS, …) & different reprogramming approaches (iPS, SCNT, fusion). We dissect pluripotency & reprogramming in an analysis across all dimensions, using the networks to integrate the data, and to propose intervention schemes (integrating small molecules). The differential analyses by ExprEssence are developed further to cope with these new tasks, incl. components for generating movies, highlighting the startup & shutdown of mechanisms in a network along all dimensions. ExprEssence highlighting will thus identify ensembles of subnetworks to be subjected to detailed modeling (Theis), it will support Boiani, Greber, Meisterernst, Hiiragi, Schroeder, Tanaka, Besser, F.-J. Müller, A. Müller & Zenke, and it is also the future core of the Bioinformatics Helpdesk for the SPP.