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Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework

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Title: Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework
Authors: Huang, Shuqiang a, 1, Tan, Cuiyu a, 1, Chen, Wanru b, 1, Zhang, Tongtong a, Xu, Liying a, Li, Zhihong a, Chen, Miaoqi a, Yuan, Xiaojun a, Chen, Cairong a, c, ⁎, Yan, Qiuxia a, c, ⁎
Source: In Genomics January 2025 117(1)
Database: ScienceDirect
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  – Url: https://www.doi.org/10.1016/j.ygeno.2024.110977?
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  Data: Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework
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  Data: In <searchLink fieldCode="JN" term="%22Genomics%22">Genomics</searchLink> January 2025 117(1)
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        Value: 10.1016/j.ygeno.2024.110977
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        Text: English
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      – TitleFull: Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework
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              Text: January 2025
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              Y: 2025
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