Unsupervised clustering reveals new prostate cancer subtypes
摘要 背景：前列腺癌是男性中第二常見的癌症。發展基於基因的分類方法是迫切的要求。我們的目標是建立基因分型。 方法：我們使用了四個前列腺癌數據集。癌症基因組圖譜（TCGA）RNA-Seq數據用於訓練分類器。基於分類器的三個亞型被測試是否具有臨牀數據存在顯着差異。其他三組按分類器分類並驗證。 結果：分類器有183個基因。前列腺癌亞型1（PCS1）的特徵是高 GSTP1的表達，Gleason評分較低（P
相關文章
- 1. 論文筆記《Adversarial Networks for Prostate Cancer Detection》
- 2. Clustering - Unsupervised learning introduction
- 3. Machine learning(7): Unsupervised learning-------CLUSTERING
- 4. Unsupervised Deep Embedding for Clustering Analysis(DEC)
- 5. False Positive Reduction Using Multiscale Contextual Features for Prostate Cancer Detection..論文筆記
- 6. 論文筆記（四）《Adversarial Networks for the Detection of Aggressive Prostate Cancer》
- 7. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 8. Deep Unsupervised Clustering Using Mixture of Autoencoders(2017)
- 9. Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder
- 10. Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
- 更多相關文章...
- • Thymeleaf表單 - Thymeleaf 教程
- • C# 交錯數組 - C#教程
- • 爲了進字節跳動，我精選了29道Java經典算法題，帶詳細講解
- • IntelliJ IDEA代碼格式化設置
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 論文筆記《Adversarial Networks for Prostate Cancer Detection》
- 2. Clustering - Unsupervised learning introduction
- 3. Machine learning(7): Unsupervised learning-------CLUSTERING
- 4. Unsupervised Deep Embedding for Clustering Analysis(DEC)
- 5. False Positive Reduction Using Multiscale Contextual Features for Prostate Cancer Detection..論文筆記
- 6. 論文筆記（四）《Adversarial Networks for the Detection of Aggressive Prostate Cancer》
- 7. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 8. Deep Unsupervised Clustering Using Mixture of Autoencoders(2017)
- 9. Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder
- 10. Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering