siRNAEfficacyDB: An experimentally supported small interfering RNA efficacy database.

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Yang Zhang, Ting Yang, Yu Yang, Dongsheng Xu, Yucheng Hu, Shuo Zhang, Nanchao Luo, Lin Ning, Liping Ren
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引用次数: 0

Abstract

Small interfering RNA (siRNA) has revolutionised biomedical research and drug development through precise post-transcriptional gene silencing technology. Despite its immense potential, siRNA therapy still faces technical challenges, such as delivery efficiency, targeting specificity, and molecular stability. To address these challenges and facilitate siRNA drug development, we have developed siRNAEfficacyDB, a comprehensive database that integrates experimentally validated siRNA efficacy data. This database contains 3544 siRNA records, covering 42 target genes and 5 cell lines. It provides detailed information on siRNA sequences, target genes, inhibition efficiencies, experimental techniques, cell lines, siRNA concentrations, and incubation times. siRNAEfficacyDB offers a user-friendly web interface that makes it easy to query, browse and analyse data, enabling efficient access to siRNA-related information. In summary, siRNAEfficacyDB provides a useful data foundation for siRNA drug design and optimisation, serving as a valuable resource for advancing computer-aided siRNA design research and nucleic acid drug development. siRNAEfficacyDB is freely available at https://cellknowledge.com.cn/siRNAEfficacy for non-commercial use.

siRNAEfficacyDB: 经实验支持的小干扰 RNA 药效数据库。
通过精确的转录后基因沉默技术,小干扰 RNA(siRNA)为生物医学研究和药物开发带来了革命性的变化。尽管 siRNA 潜力巨大,但其治疗仍面临着技术挑战,如传递效率、靶向特异性和分子稳定性。为了应对这些挑战,促进 siRNA 药物开发,我们开发了 siRNAEfficacyDB,这是一个整合了经实验验证的 siRNA 疗效数据的综合数据库。该数据库包含 3544 条 siRNA 记录,涵盖 42 个靶基因和 5 个细胞系。siRNAEfficacyDB 提供用户友好的网络界面,便于查询、浏览和分析数据,使人们能够高效地获取 siRNA 相关信息。总之,siRNAEfficacyDB 为 siRNA 药物设计和优化提供了有用的数据基础,是推进计算机辅助 siRNA 设计研究和核酸药物开发的宝贵资源。siRNAEfficacyDB 可在 https://cellknowledge.com.cn/siRNAEfficacy 免费获取,但不得用于商业用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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