| Year |
Citation |
Score |
| 2022 |
Tao Y, Ma X, Palmer D, Schwartz R, Lu X, Osmanbeyoglu HU. Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers. Nucleic Acids Research. PMID 36243974 DOI: 10.1093/nar/gkac881 |
0.508 |
|
| 2022 |
Lei H, Guo XA, Tao Y, Ding K, Fu X, Oesterreich S, Lee AV, Schwartz R. Semi-deconvolution of bulk and single-cell RNA-seq data with application to metastatic progression in breast cancer. Bioinformatics (Oxford, England). 38: i386-i394. PMID 35758822 DOI: 10.1093/bioinformatics/btac262 |
0.551 |
|
| 2022 |
Fu X, Lei H, Tao Y, Schwartz R. Reconstructing tumor clonal lineage trees incorporating single-nucleotide variants, copy number alterations and structural variations. Bioinformatics (Oxford, England). 38: i125-i133. PMID 35758777 DOI: 10.1093/bioinformatics/btac253 |
0.552 |
|
| 2022 |
Ren S, Tao Y, Yu K, Xue Y, Schwartz R, Lu X. De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 27: 278-289. PMID 34890156 |
0.45 |
|
| 2021 |
Fu X, Lei H, Tao Y, Heselmeyer-Haddad K, Torres I, Dean M, Ried T, Schwartz R. Joint Clustering of Single-Cell Sequencing and Fluorescence In Situ Hybridization Data for Reconstructing Clonal Heterogeneity in Cancers. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. PMID 34612714 DOI: 10.1089/cmb.2021.0255 |
0.565 |
|
| 2021 |
Lei H, Gertz EM, Schäffer AA, Fu X, Tao Y, Heselmeyer-Haddad K, Torres I, Li G, Xu L, Hou Y, Wu K, Shi X, Dean M, Ried T, Schwartz R. Tumor heterogeneity assessed by sequencing and fluorescence in situ hybridization (FISH) data. Bioinformatics (Oxford, England). PMID 34289030 DOI: 10.1093/bioinformatics/btab504 |
0.586 |
|
| 2021 |
Tao Y, Rajaraman A, Cui X, Cui Z, Chen H, Zhao Y, Eaton J, Kim H, Ma J, Schwartz R. Assessing the contribution of tumor mutational phenotypes to cancer progression risk. Plos Computational Biology. 17: e1008777. PMID 33711014 DOI: 10.1371/journal.pcbi.1008777 |
0.552 |
|
| 2020 |
Tao Y, Lei H, Lee AV, Ma J, Schwartz R. Neural Network Deconvolution Method for Resolving Pathway-Level Progression of Tumor Clonal Expression Programs With Application to Breast Cancer Brain Metastases. Frontiers in Physiology. 11: 1055. PMID 33013452 DOI: 10.3389/Fphys.2020.01055 |
0.606 |
|
| 2020 |
Tao Y, Lei H, Fu X, Lee AV, Ma J, Schwartz R. Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis. Bioinformatics (Oxford, England). 36: i407-i416. PMID 32657393 DOI: 10.1093/Bioinformatics/Btaa396 |
0.624 |
|
| 2020 |
Tao Y, Cai C, Cohen WW, Lu X. From genome to phenome: Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 25: 79-90. PMID 31797588 |
0.503 |
|
| 2016 |
Tao Y, Lin F, Li R, Shen J, Wang Z. Prolyl Hydroxylase-2 Inhibits Liver Tumor Cell Proliferation and Cyclin D1 Expression in a Hydroxylase-dependent Manner. The International Journal of Biochemistry & Cell Biology. PMID 27307407 DOI: 10.1016/j.biocel.2016.05.022 |
0.38 |
|
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