肿瘤新抗原数据库平台。

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yan Shao, Yang Gao, Ling-Yu Wu, Shu-Guang Ge, Peng-Bo Wen
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引用次数: 0

摘要

随着肿瘤免疫治疗的不断进步,以新抗原为基础的治疗已显示出显著的临床疗效。然而,准确预测新抗原的免疫原性仍然是一个重大挑战。这主要是由于两个核心因素:缺乏高质量的新抗原数据集和现有免疫原性预测工具的预测精度有限。本研究通过几个关键步骤解决了这些问题。首先,从公开的文献和新抗原数据库中收集和整理免疫原性新抗原肽数据。其次,对数据进行分析,确定影响新抗原免疫原性预测的关键特征。最后,结合现有的预测工具,构建肿瘤新抗原综合数据库TumorAgDB1.0。TumorAgDB1.0提供了一个用户友好的平台。用户可以使用氨基酸序列和肽长度等参数有效地搜索新抗原数据。该平台还提供了新抗原特征的详细信息和预测肿瘤新抗原免疫原性的工具。此外,该数据库还包括数据下载功能,允许研究人员轻松访问高质量数据,以支持新抗原免疫原性预测工具的开发和改进。综上所述,TumorAgDB1.0是肿瘤免疫治疗中新抗原筛选和验证的有力工具。它为研究人员提供了强有力的支持。数据库地址:https://tumoragdb.com.cn。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TumorAgDB1.0: tumor neoantigen database platform.

With the continuous advancements in cancer immunotherapy, neoantigen-based therapies have demonstrated remarkable clinical efficacy. However, accurately predicting the immunogenicity of neoantigens remains a significant challenge. This is mainly due to two core factors: the scarcity of high-quality neoantigen datasets and the limited prediction accuracy of existing immunogenicity prediction tools. This study addressed these issues through several key steps. First, it collected and organized immunogenic neoantigen peptide data from publicly available literature and neoantigen databases. Second, it analyzed the data to identify key features influencing neoantigen immunogenicity prediction. Finally, it integrated existing prediction tools to create TumorAgDB1.0, a comprehensive tumor neoantigen database. TumorAgDB1.0 offers a user-friendly platform. Users can efficiently search for neoantigen data using parameters like amino acid sequence and peptide length. The platform also offers detailed information on the characteristics of neoantigens and tools for predicting tumor neoantigen immunogenicity. Additionally, the database includes a data download function, allowing researchers to easily access high-quality data to support the development and improvement of neoantigen immunogenicity prediction tools. In summary, TumorAgDB1.0 is a powerful tool for neoantigen screening and validation in tumor immunotherapy. It offers strong support to researchers. Database URL: https://tumoragdb.com.cn.

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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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