KiNext:一种便携和可扩展的工作流程,用于蛋白质激酶的识别和分类
Elisabeth Hellec1,2,3, Flavia Nunes2, Charlotte Corporeau3
1Ifremer, IRSI-SeBiMER, Plouzané, France.
BMC bioinformatics
|October 25, 2024
概括
KiNext是一个符合FAIR原则的管道,可以有效地识别和分类蛋白质基因酶. 该工具通过发现新酶和分类以前未被分配的酶来改进现有方法.
科学领域:
- 生物化学 生化学
- 生物信息学是一种生物信息学.
- 基因组学就是基因组学.
背景情况:
- 蛋白激酶对于细胞信号传递和生物体生理学至关重要.
- 蛋白质激酶的失调与癌症等疾病有关.
- 鉴定基因组有助于理解生物体的能力和适应性.
研究的目的:
- 提出一个符合FAIR原则的管道,用于识别和分类蛋白激酶.
- 为了从预测的蛋白质组中实现高效和可复制的基因组分析.
主要方法:
- 使用Nextflow和现有的生物信息工具.
- 采用隐藏的马尔科夫模型 (HMM) 来识别常规的真核蛋白激酶 (ePK) 和非典型的蛋白激酶 (aPK).
- 使用专用HMM将ePK分为八个组.
主要成果:
- KiNext成功地在太平洋和绿藻中识别和分类蛋白激酶.
- 该管道通过发现新的激酶和分类未分配的激酶,超越了以前的方法.
- 证明了改进的激酶识别和分类,具有可追溯性和可重现性.
结论:
- KiNext提供了一种高效且可复制的方法,用于从蛋白质组中识别基因组.
- 管道的设计是为了方便使用,自动化,便携性和可扩展性.
- 适用于分析超出真核生物以外的多种类型的基因组.
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