Identifying common transcriptome signatures of cancer by interpreting deep learning models

[1] Haigis KM(2019)Tissue-specificity in cancer: the rule, not the exception Science 363 1150-1

[2] Cichowski K(2018)Oncogenic signaling pathways in the cancer genome atlas Cell 173 321-37

[3] Elledge SJ(2021)A modular master regulator landscape controls cancer transcriptional identity Cell 184 334-35120

[4] Sanchez-Vega F(2004)Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells N Engl J Med 351 2159-69

[5] Mina M(2010)A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients Cancer Res 70 10202-12

[6] Armenia J(2014)RNA-seq accurately identifies cancer biomarker signatures to distinguish tissue of origin Neoplasia 16 918-27

[7] Chatila WK(2019)Application of a neural network whole transcriptome–based pan-cancer method for diagnosis of primary and metastatic cancers JAMA Netw Open 2 192597-30

[8] Luna A(2019)Pan-cancer RNA-seq data stratifies tumours by some hallmarks of cancer J Cell Mol Med 24 418-71

[9] La KC(1997)Selection of relevant features and examples in machine learning Artif Intell 97 245-82

[10] Dimitriadoy S(2003)An introduction to variable and feature selection J Mach Learn Res 3 1157-9

[1] Haigis KM(2019)Tissue-specificity in cancer: the rule, not the exception Science 363 1150-1

[2] Cichowski K(2018)Oncogenic signaling pathways in the cancer genome atlas Cell 173 321-37

[3] Elledge SJ(2021)A modular master regulator landscape controls cancer transcriptional identity Cell 184 334-35120

[4] Sanchez-Vega F(2004)Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells N Engl J Med 351 2159-69

[5] Mina M(2010)A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients Cancer Res 70 10202-12

[6] Armenia J(2014)RNA-seq accurately identifies cancer biomarker signatures to distinguish tissue of origin Neoplasia 16 918-27

[7] Chatila WK(2019)Application of a neural network whole transcriptome–based pan-cancer method for diagnosis of primary and metastatic cancers JAMA Netw Open 2 192597-30

[8] Luna A(2019)Pan-cancer RNA-seq data stratifies tumours by some hallmarks of cancer J Cell Mol Med 24 418-71

[9] La KC(1997)Selection of relevant features and examples in machine learning Artif Intell 97 245-82

[10] Dimitriadoy S(2003)An introduction to variable and feature selection J Mach Learn Res 3 1157-9