Detalhe da pesquisa
1.
Identification of the HNSC88 Molecular Signature for Predicting Subtypes of Head and Neck Cancer.
Int J Mol Sci
; 24(17)2023 Aug 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-37685875
2.
Densest subgraph-based methods for protein-protein interaction hot spot prediction.
BMC Bioinformatics
; 23(1): 451, 2022 Oct 31.
Artigo
em Inglês
| MEDLINE | ID: mdl-36316653
3.
CoMI: consensus mutual information for tissue-specific gene signatures.
BMC Bioinformatics
; 22(Suppl 10): 624, 2022 Apr 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-35439942
4.
Whole-Blood 3-Gene Signature as a Decision Aid for Rifapentine-based Tuberculosis Preventive Therapy.
Clin Infect Dis
; 75(5): 743-752, 2022 09 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-34989801
5.
Reply to Chang and Huang.
Clin Infect Dis
; 75(10): 1867, 2022 Nov 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-35833899
6.
Methotrexate inhibition of SARS-CoV-2 entry, infection and inflammation revealed by bioinformatics approach and a hamster model.
Front Immunol
; 13: 1080897, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36618412
7.
Convolutional neural network for human cancer types prediction by integrating protein interaction networks and omics data.
Sci Rep
; 11(1): 20691, 2021 10 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-34667236
8.
An Integrated Genomic Strategy to Identify CHRNB4 as a Diagnostic/Prognostic Biomarker for Targeted Therapy in Head and Neck Cancer.
Cancers (Basel)
; 12(5)2020 May 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-32455963
9.
Identification of the PCA29 gene signature as a predictor in prostate cancer.
J Bioinform Comput Biol
; 17(3): 1940006, 2019 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-31288639
10.
Membrane protein-regulated networks across human cancers.
Nat Commun
; 10(1): 3131, 2019 07 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-31311925
11.
Nicotinic Acetylcholine Receptor Subtype Alpha-9 Mediates Triple-Negative Breast Cancers Based on a Spontaneous Pulmonary Metastasis Mouse Model.
Front Cell Neurosci
; 11: 336, 2017.
Artigo
em Inglês
| MEDLINE | ID: mdl-29163048