Establishment of Active Chromatin Domains

研究总结： 了解驱动协调基因激活的机制将提供关键的 对发育和疾病的生物学见解。本附录旨在启用AI/ML 方法集成不同的数据集，以帮助实现这一目标。具体来说，我们计划 用计算机模拟果蝇基因的时空调控 ChIP-Seq、Hi-C/Micro-C和mRNA-Seq数据集。此外，我们还将获得并建模 早期胚胎发育的单细胞测量(scRNA-Seq和scATAC-Seq) 协调基因激活区域建立的阶段。因此，我们提出三点建议 为社区生成AI/ML就绪数据集的任务。(1)稳健发展 用于轻松访问和输入到基于图的神经网络以进行集成的预处理管道 数据集。(2)子图选择方法在信息交互抽取中的应用 由染色质捕获技术生成的大而有噪音的图形。(3)集成单元格 并为数据建模和分析目的提供这些组合。这个 提出的方法将有助于实现准确捕捉潜在生物的目标 使用各种机器学习方法时的信息。此外，我们还将提供 向社区提供经过处理的数据集和脚本，以实现方法创新。Dr。 Larschan将与机器学习专家Singh博士合作，我们已经在 与学生和出版物联合开展了几个基于拟议主题的项目。这 补充将是使我们能够继续协作并产生新的 方法和数据集，将提供对协调基因激活的关键洞察。

RESEARCH SUMMARY: Understanding the mechanisms which drive coordinate gene activation will provide critical biological insights into development and disease. This supplement aims to enable AI/ML methods to integrate diverse datasets to help achieve that goal. Specifically, we plan to computationally model the spatiotemporal regulation of genes in Drosophila by combining ChIP-Seq, Hi-C/ Micro-C, and mRNA-Seq datasets. Moreover, we will obtaining and model single-cell measurements (scRNA-Seq and scATAC-Seq) across early embryonic developmental stages when domains of coordinate gene activation are established. Therefore, we propose three tasks to produce AI/ML-ready datasets for the community. (1) Development of robust preprocessing pipelines for easy access and input to graph-based neural networks for integrating datasets. (2) Application of sub-graph selection methods to extract informative interactions from large and noisy graphs generated from chromatin capture technologies. (3) Integrating single-cell measurements and providing these combinations for data modeling and analysis purposes. The proposed methods will assist the goals of accurately capturing the underlying biological information when using various machine learning approaches. Furthermore, we will provide processed datasets and scripts to the community to enable methodological innovations. Dr. Larschan will collaborate with machine learning expert Dr. Singh and we have collaborated on several projects based on the proposed topic with joint students and publications. This supplement will be essential to allowing us to continue collaborating and generating new methods and data sets which will provide key insight into coordinate gene activation.