​​​​​​In the era of precision medicine, how can the power of AI be utilised to turn biological studies into the best possible targets? How can AI be applied to systems biology to bring the most effective targets to light? And how can we use these insights in the drug discovery process? In the webinar, 4 different experts will discuss the areas in which AI is bringing biological insights to the forefront, and Aaron Sato, Twist's CSO, will explain how Twist is enabling  the key players to write the Future of Biologics with Synthetic DNA and Machine Learning. 演讲者：Gary An, Prof. & Vice Chair of Surgical Research, University of Vermont Aaron K. Sato, CSO, Twist Bioscience Enkelejda Miho, Prof. of Digital Life Sciences, The FHNW University of Applied Sciences and Arts Northwestern Switzerland Philip Kim, Prof., The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto

In the future, it is expected that the DNA methylation information of each individual will be used for early prevention of diseases and as a surrogate marker to improve lifestyle. However, the capture sequencing method is expensive and requires a large amount of DNA, which has been a challenge. At this time, with the cooperation of Twist Bioscience, they created a capture probe set to measure CpG at approximately 1,000 locations and evaluated it, especially for the amount of DNA required. As a result, it was confirmed that capture sequencing was possible with less than 200 ng of DNA compared to other reagents. In this talk, Dr. Shimizu presents their epigenome research at IMM, their recently published work on epigenetic age, and the results of the use of the Twist Bioscience Methylation detection system.    

Twist 的新型 RNA 外显子组组合用新型外显子感知设计策略来靶向已知的蛋白质编码亚型，并能够发现新的融合基因。我们评估了组合性能，显示相对转录本丰度在杂交捕获后得以保留。我们还展示了测序效率的提高，并展示了捕获新结构变异的能力，例如癌症中常见的 RNA 融合。我们讨论了评估 RNA 捕获性能的生物信息学方法以及 RNA-seq 实验分析中的挑战。