“第四十八章 开发癌症疫苗”版本间的差异

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==教学资料==
 
==教学资料==
  
* [[教学参考-47|教学参考]]
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* [[教学参考-48|教学参考]]
* [http://aigraph.cslt.org/courses/47/course-47.pptx 课件]
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* [http://aigraph.cslt.org/courses/48/course-48.pptx 课件]
* 小清爱提问:人工智能如何预测新冠病毒传染性 ? [https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247487279&idx=1&sn=d6c7bc8ea1a45a6dfdcfae3ad2c6dc15&chksm=c30805edf47f8cfbac027694f266151284f08efc784718ad225ab33be85067ef37d62e93fec9&scene=178#rd]
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* 小清爱提问:人工智能如何助力开发癌症疫苗? [https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247486775&idx=1&sn=f5115c5ed723303b683a25c35a93f901&chksm=c30807f5f47f8ee35cc32c7611fd1ac4cc271623eaa20e5e074e55c7c99104cd322a9ec65aeb&scene=178#rd]
* 小清爱提问:人工智能如何预测新冠疫情?  [https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247485425&idx=1&sn=f4e19de5736a475584063a7abedb1a8f&chksm=c3080d33f47f8425da5b03161bac48aeea4eccd4bb9b6b4d74e13a31e7b9f02bc7fd9557d233&scene=178#rd]
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==扩展阅读==
 
  
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==扩展阅读==
  
* WHO: 苗如何发挥作用? {https://www.who.int/zh/news-room/feature-stories/detail/how-do-vaccines-work}
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* WHO: 苗如何发挥作用? [https://www.who.int/zh/news-room/feature-stories/detail/how-do-vaccines-work]
 
* 维基百科:免疫系统 [http://aigraph.cslt.org/courses/48/免疫系统.pdf]
 
* 维基百科:免疫系统 [http://aigraph.cslt.org/courses/48/免疫系统.pdf]
* 维基百科:2019冠状病毒 [http://aigraph.cslt.org/courses/48/2019冠状病毒病.pdf]
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* 维基百科:免疫疗法 [http://aigraph.cslt.org/courses/48/免疫治疗.pdf]
  
  
 
==视频展示==
 
==视频展示==
  
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* 疫苗的历史:人类与病毒之间的史诗级战役,最终谁赢了? [https://www.bilibili.com/video/BV1J64y1b7Mf?spm_id_from=333.337.search-card.all.click]
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* 细胞免疫 [https://www.bilibili.com/video/BV1cZ4y1k7Zq/?spm_id_from=333.788.recommend_more_video.-1]
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* CAR-T细胞免疫疗法 [https://www.bilibili.com/video/BV1Zg4y1B7Us?spm_id_from=333.337.search-card.all.click]
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* 一分半解读CAR-T疗法 [https://www.bilibili.com/video/BV16W41157MX/?spm_id_from=333.788.recommend_more_video.-1]
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* 肿瘤免疫疗法之免疫检查点抑制剂 [https://www.bilibili.com/video/BV1MZ4y1c7Ff?spm_id_from=333.337.search-card.all.click]
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* 体免疫的“刹车”系统:新免疫疗法为癌症患者带来福音 [https://www.bilibili.com/video/BV1Db411A7Un/?spm_id_from=333.788.recommend_more_video.2]
  
  
 
==演示链接==
 
==演示链接==
 
  
  
 
==开发者资源==
 
==开发者资源==
  
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* Source Code for DeepNovo[https://www.nature.com/articles/s42256-020-00260-4#MOESM2] [https://github.com/nh2tran/DeepNovoAA]
  
 
==高级读者==
 
==高级读者==
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* Hu Z, Ott P A, Wu C J. Towards personalized, tumour-specific, therapeutic vaccines for cancer[J]. Nature Reviews Immunology, 2018, 18(3): 168-182. [https://www.nature.com/articles/nri.2017.131]
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* Andreatta, M. & Nielsen, M. Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics 32, 511–517 (2016).  [https://academic.oup.com/bioinformatics/article/32/4/511/1744469] 
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* Calling cancer’s bluff with neoantigen vaccines, [https://www.nature.com/articles/d41586-017-08706-3]
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* Ngoc Hieu Tran, Rui Qiao, Lei Xin, Xin Chen, Baozhen Shan,Ming Li, Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines, Nature Machine Intelligence, 2, pages764–771(2020) [https://www.nature.com/articles/s42256-020-00260-4#MOESM2]
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* Ball P. First quantum computer to pack 100 qubits enters crowded race[J]. Nature, 2021, 599(7886): 542-542. [https://www.nature.com/articles/d41586-021-03476-5]

2022年8月26日 (五) 04:55的最后版本

教学资料


扩展阅读

  • WHO: 苗如何发挥作用? [2]
  • 维基百科:免疫系统 [3]
  • 维基百科:免疫疗法 [4]


视频展示

  • 疫苗的历史:人类与病毒之间的史诗级战役,最终谁赢了? [5]
  • 细胞免疫 [6]
  • CAR-T细胞免疫疗法 [7]
  • 一分半解读CAR-T疗法 [8]
  • 肿瘤免疫疗法之免疫检查点抑制剂 [9]
  • 体免疫的“刹车”系统:新免疫疗法为癌症患者带来福音 [10]


演示链接

开发者资源

高级读者

  • Hu Z, Ott P A, Wu C J. Towards personalized, tumour-specific, therapeutic vaccines for cancer[J]. Nature Reviews Immunology, 2018, 18(3): 168-182. [13]
  • Andreatta, M. & Nielsen, M. Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics 32, 511–517 (2016). [14]
  • Calling cancer’s bluff with neoantigen vaccines, [15]
  • Ngoc Hieu Tran, Rui Qiao, Lei Xin, Xin Chen, Baozhen Shan,Ming Li, Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines, Nature Machine Intelligence, 2, pages764–771(2020) [16]
  • Ball P. First quantum computer to pack 100 qubits enters crowded race[J]. Nature, 2021, 599(7886): 542-542. [17]