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生物信息学方法在CTL表位预测中的应用 被引量:4

Prediction of CTL epitopes using the bioinformatics tools
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摘要 细胞毒性T淋巴细胞(CytotoxicTlymphocyte ,CTL)在机体抗感染免疫和肿瘤免疫中发挥重要作用。引起有效CTL免疫应答的,并非完整的蛋白质抗原分子,而是抗原来源的特异性CTL表位。因此,对CTL表位作出高效、准确地预测,进而通过实验方法鉴定,是基于表位的疫苗设计以及发展特异性CTL免疫应答检测技术的关键。近年来,随着生物信息学的迅猛发展,一系列该领域的新成果被应用于CTL表位预测。通过建立新的算法和编写相应程序,大大提高了CTL表位鉴定的效率,加快了基于表位的新药研发进程。 Cytotoxic T lymphocytes (CTL) are the key mediators of specific immune responses against infectious diseases and cancer. The minimal essential units of information, T-cell epitopes that are derived from self and nonself proteins, can provoke the cellular immune responses when presented to T cell. Thereby, the precision prediction of T cell epitopes, followed by confirmatory studies in vitro, remains a critical step in the development of epitope-driven vaccines and the methods of monitoring T cell responses. With the development of bioinformatics, a series of new technologies in this field have been used for epitope mapping. Identification of CTL epitopes by establishing new computer algorithms can achieve high-throughput epitopes screen in silico and reduce the time and effort involved in drug design significantly.
出处 《免疫学杂志》 CAS CSCD 北大核心 2005年第2期155-159,共5页 Immunological Journal
关键词 CTL 表位 生物信息学 基序 人工神经网络 Cytotoxic T lymphocytes Epitope Bioinformatics Motif Artificial neural network
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