发育生物学,单细胞转录组测序,人工智能," /> 发育生物学,单细胞转录组测序,人工智能,"/> <span style="line-height:2;font-size:14px;">单细胞转录组测序与人工智能在发育</span><span style="line-height:2;font-size:14px;">生物学中的应用</span>
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发育医学电子杂志  2020, Vol. 8 Issue (1): 1-7    DOI: 10.3969/j.issn.2095-5340.2020.01.001
  发育基础   专题笔谈 |
单细胞转录组测序与人工智能在发育生物学中的应用
张苇 辛子娟 张昭军 方向东
1. 中国科学院北京基因组研究所 基因组科学与信息重点实验室,北京 100101; 2. 中国科学院大学 生命科学学院,北京 100049;3. 中国科学院大学 中丹学院,北京 100190;3. 中国科学院 干细胞与再生医学创新研究院,北京 100101
Application of single-cell RNA sequencing and artificial intelligence in the developmental biology
ZHANG Wei, XIN Zi-juan, ZHANG Zhao-jun, et al
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摘要 发育生物学(developmental biology)的研究范畴涵盖了一个生物从出现到消失的全部过程,包括配子发生、受精、胚胎发育、个体生长、衰老和死亡。研究人员借助生物学实验和计算分析手段对多细胞样本进行研究,以阐明发育生物学中存在的问题。随着单细胞测序技术的出现和发展,对生物发育调控与差异性的相关研究得以提高至单个细胞层面,并借助人工智能(artificial intelligence,AI)算法提高单细胞测序数据分析的准确性,进一步加深对个体发育和疾病发生的突破性了解。本文将从单细胞测序在胚胎发育、器官形成和肿瘤发生研究中的应用进行综述,为深入利用单细胞测序进行发育生物学研究提供参考。
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关键词:  发育生物学')" href="#">发育生物学  单细胞转录组测序  人工智能    
收稿日期:  2019-10-20                出版日期:  2020-01-30      发布日期:  2020-01-21      期的出版日期:  2020-01-30
基金资助: 中国科学院战略性先导科技专项(XDA16010602);国家重点研发计划(2016YFC0901700,2016YFC0901603 ,2017YFC0907400,2018YFC0910700,2017YFC0907403,2018YFC0910402);国家自然科学基金(81670109,81870097,81700097,81700116)
通讯作者:  方向东https://baike.baidu.com/item/%E6%96%B9%E5%90%91%E4%B8%9C/4812857?fr=aladdin    E-mail:  fangxd@big.ac.cn
引用本文:    
张苇 辛子娟 张昭军 方向东. 单细胞转录组测序与人工智能在发育生物学中的应用[J]. 发育医学电子杂志, 2020, 8(1): 1-7.
ZHANG Wei, XIN Zi-juan, ZHANG Zhao-jun, et al. Application of single-cell RNA sequencing and artificial intelligence in the developmental biology. Journal of Developmental Medicine(Electronic Version), 2020, 8(1): 1-7.
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