JP2024538478A - ギャップ付き及び非ギャップタンパク質サンプルを使用した変異体病原性予測器の複合学習及び転移学習 - Google Patents
ギャップ付き及び非ギャップタンパク質サンプルを使用した変異体病原性予測器の複合学習及び転移学習 Download PDFInfo
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- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
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Applications Claiming Priority (13)
| Application Number | Priority Date | Filing Date | Title |
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| US202163253122P | 2021-10-06 | 2021-10-06 | |
| US63/253,122 | 2021-10-06 | ||
| US202163281592P | 2021-11-19 | 2021-11-19 | |
| US202163281579P | 2021-11-19 | 2021-11-19 | |
| US63/281,579 | 2021-11-19 | ||
| US63/281,592 | 2021-11-19 | ||
| US17/533,091 | 2021-11-22 | ||
| US17/533,091 US11538555B1 (en) | 2021-10-06 | 2021-11-22 | Protein structure-based protein language models |
| US17/953,286 | 2022-09-26 | ||
| US17/953,293 | 2022-09-26 | ||
| US17/953,293 US20230108368A1 (en) | 2021-10-06 | 2022-09-26 | Combined and transfer learning of a variant pathogenicity predictor using gapped and non-gapped protein samples |
| US17/953,286 US20230108241A1 (en) | 2021-10-06 | 2022-09-26 | Predicting variant pathogenicity from evolutionary conservation using three-dimensional (3d) protein structure voxels |
| PCT/US2022/045823 WO2023059750A1 (en) | 2021-10-06 | 2022-10-05 | Combined and transfer learning of a variant pathogenicity predictor using gapped and non-gapped protein samples |
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| JP2023580572A Pending JP2024538477A (ja) | 2021-10-06 | 2022-10-05 | タンパク質構造に基づくタンパク質言語モデル |
| JP2023579826A Pending JP2024538475A (ja) | 2021-10-06 | 2022-10-05 | 三次元（３ｄ）タンパク質構造ボクセルを用いた進化的保存からの変異体病原性の予測 |
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| JP2023579826A Pending JP2024538475A (ja) | 2021-10-06 | 2022-10-05 | 三次元（３ｄ）タンパク質構造ボクセルを用いた進化的保存からの変異体病原性の予測 |
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| CN117178327A (zh) * | 2021-04-15 | 2023-12-05 | 因美纳有限公司 | 使用深度卷积神经网络来预测变体致病性的多通道蛋白质体素化 |
| CN118629516B (zh) * | 2024-05-17 | 2025-09-16 | 安徽农业大学 | 一种基于多模态特征和孪生网络的神经肽预测方法及系统 |
| CN119560009B (zh) * | 2025-01-22 | 2025-06-24 | 浙江工业大学 | 一种蛋白质翻译后修饰与疾病关联预测系统及方法 |
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| CN117642824A (zh) | 2024-03-01 |
| KR20240088641A (ko) | 2024-06-20 |
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