Kang Seokjun, Lee Daehwan, Hwang Gyeongjo, Lee Kiwon, Kang Mingeun
Spidercore Inc., 1662, Yuseong-daero, Yuseong-gu, Daejeon 34054, South Korea.
Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea.
Nucleic Acids Res. 2025 Jul 7;53(W1):W39-W44. doi: 10.1093/nar/gkaf392.
Antisense oligonucleotides (ASOs) are a promising class of gene therapies that can modulate the gene expression. However, designing ASOs manually is resource-intensive and time-consuming. To address this, we introduce a user-friendly web server for ASOptimizer, a deep learning-based computational framework for optimizing ASO sequences and chemical modifications. Given a user-provided ASO sequence, the web server systematically explores modification sites within the nucleic acid and returns a ranked list of promising modification patterns. With an intuitive interface requiring no expertise in deep learning tools, the platform makes ASOptimizer easily accessible to the broader research community. The web server is freely available at https://asoptimizer.s-core.ai/.
反义寡核苷酸（ASO）是一类很有前景的基因疗法，可调节基因表达。然而，手动设计ASO既耗费资源又耗时。为解决这一问题，我们推出了一个用户友好的网络服务器ASOptimizer，这是一个基于深度学习的计算框架，用于优化ASO序列和化学修饰。给定用户提供的ASO序列，该网络服务器会系统地探索核酸内的修饰位点，并返回一份有前景的修饰模式排名列表。该平台拥有直观的界面，无需深度学习工具方面的专业知识，使广大研究群体能够轻松使用ASOptimizer。该网络服务器可在https://asoptimizer.s-core.ai/免费获取。
Zotero 插件
