Identification of circulating miRNA as early diagnostic molecular markers in malignant glioblastoma base on decision tree joint scoring algorithm., Fei Su, Yueyang Liu, Yonghua Zong, Ziyu Gao, Guiqin Zhou, Chao Deng, Yuyu Liu, Yue Zeng, Xiaoyan Ma, Yongxia Wang, Yinwei Wu3, Fusheng Xu, Lili Guan, Baoquan Liu., 2023
Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer., Fei Su, Ziyu Gao, Yueyang Liu, Guiqin Zhou, Wei Gao, Chao Deng, Yuyu Liu, Yihao Zhang, Xiaoyan Ma, Yongxia Wang, Lili Guan, Yafang Zhang, Baoquan Liu., 2022
Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications., Fei Su, Ziyu Gao, Yueyang Liu, Guiqin Zhou, Ying Cui, Chao Deng, Yuyu Liu, Yihao Zhang, Xiaoyan Ma, Yongxia Wang, Lili Guan, Yafang Zhang, Baoquan Liu., 2022
Serum microRNA-21 predicted treatment outcome and survival in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy combined with trastuzumab., B Liu, F Su, X Lv, W Zhang, X Shang, Y Zhang., 2019
Cofunctional Subpathways Were Regulated by Transcription Factor with Common Motif, Common Family, or Common., Su F, Shang D, Xu Y, Feng L, Yang H, Liu B, Su S, Chen L, Li X., 2015
SCARA5 plays a critical role in the progression and metastasis of breast cancer by inactivating the ERK1/2, STAT3, and AKT signaling pathways., You K, Su F, Liu L, Lv X, Zhang J, Zhang Y, Liu B., 2017
Serum miR-21 and miR-125b as markers predicting neoadjuvant chemotherapy response and prognosis in stage II/III breast cancer., Liu B, Su F, Chen M, Li Y, Qi X, Xiao J, Li X, Liu X, Liang W, Zhang Y, Zhang J., 2017
Changes of serum miR34a expression during neoadjuvant chemotherapy predict the treatment response and prognosis in stage II/III breast cancer., Liu B, Su F, Li Y, Qi X, Liu X, Liang W, You K, Zhang Y, Zhang J., 2017
Expression of VEGF-D, SMAD, and SMAD7 and Their Relationship with Lymphangiogenesis and Prognosis in Colon Cancer., Su F, Li X, You K, Chen M, Xiao J, Zhang Y, Ma J, Liu B., 2016
Association between VEGF-A, C and D expression and lymph node involvement in breast cancer: a meta-analysis., Su F, Liu B, Chen M, Xiao J, Li X, Lv X, Ma J, You K, Zhang J, Zhang Y., 2016
Inference of patient-specific subpathway activities reveals a functional signature associated with the prognosis of patients with breast cancer., Han J, Liu S, Jiang Y, Xu C, Zheng B, Jiang M, Yang H, Su F, Li C, Zhang Y., 2018
The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs and Diseases., Haixiu Yang, Desi Shang, Yanjun Xu, Chunlong Zhang, Li Feng, Zeguo Sun, Xinrui Shi, Yunpeng Zhang, Junwei Han, Fei Su, Chunquan Li, Xia Li., 2017
BioM2MetDisease: a manually curated database for associations between microRNAs, metabolites, small molecules and metabolic diseases., Yanjun Xu, Haixiu Yang, Tan Wu, Qun Dong, Zeguo Sun, Desi Shang, Feng Li, Yingqi Xu, Fei Su, Siyao Liu, Yunpeng Zhang, Xia Li., 2017
Identification of novel prognostic indicators for triple-negative breast cancer patients through integrative analysis of cancer genomics data and protein interactome data., Fan Zhang, Chunyan Ren, Hengqiang Zhao, Lei Yang, Fei Su, Ming-Ming Zhou, Junwei Han, Eric A. Sobie, Martin J. Walsh., 2016
LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method., Han J, Liu S, Sun Z, Zhang Y, Zhang F, Zhang C, Shang D, Yang H, Su F, Xu Y, Li C, Ren H, Li X., 2017
Identification of a lncRNA involved functional module for esophageal cancer subtypes., Li S, Xu Y, Sun Z, Feng L, Shang D, Zhang C, Shi X, Han J, Su F, Yang H, Zhao J, Song C, Zhang Y, Li C, Li X., 2016
Subpathway-LNCE: Identify dysfunctional subpathways competitively regulated by lncRNAs through integrating lncRNA-mRNA expression profile and pathway topologies., Shi Xinrui, Xu Yanjun, Zhang Chunlong, Feng Li, Sun Zeguo, Hang Junwei, Su Fei, Zhang Yunpeng, Li., 2016
A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways., Han J, Li C, Yang H, Xu Y, Zhang C, Ma J, Shi X, Liu W, Shang D, Yao Q, Zhang Y, Su F, Feng L, Li X., 2015
ESEA Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis., Han J, Shi X, Zhang Y, Xu Y, Jiang Y, Zhang C, Feng L, Yang H, Shang D, Sun Z, Su Fei, Li Chun quan, Li Xia., 2015
Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network., Qianlan Yao, Yanjun Xu, Haixiu Yang, Desi Shang, Chunlong Zhang, Yunpeng Zhang, Zeguo Sun, Xinrui Shi, Li Feng, Junwei Han, Fei Su, Chunquan Li, Xia Li., 2015
Identification of Subtype Specific miRNA-mRNA Functional Regulatory Modules in Matched miRNA-mRNA Expression Data Multiple Myeloma as a Case., Zhang Y, Liu W, Xu Y, Li C, Wang Y, Yang H, Zhang C, Su F, Li Y, Li X., 2015
Subpathway-GMir Identifying miRNA-mediated metabolic subpathways by integrating condition-specific genes, microRNAs, and pathway topologies., Feng L, Xu Y, Zhang Y, Sun Z, Han J, Zhang C, Yang H, Shang D, Su F, Shi X, Li S, Li C, Li X., 2015
A global view of network of lncRNAs and their binding proteins., Shang D, Yang H, Xu Y, Yao Q, Zhou W, Shi X, Han J, Su F, Su B, Zhang C, Li C, Li X., 2014
MPINet Metabolite Pathway Identification via Coupling of Global Metabolite Network Structure and Metabolomic Profile., Li F, Xu Y, Shang D, Yang H, Liu W, Han J, Sun Z, Yao Q, Zhang C, Ma J, Su F, Feng L, Shi X, Zhang Y, Li J, Gu Q, Li X, Li C., 2014
Prioritizing Candidate Disease Metabolites Based on Global Functional Relationships between Metabolites in the Context of Metabolic Pathways., Shang D, Li C, Yao Q, Yang H, Xu Y, Han J, Li J, Su F, Zhang Y, Zhang C, Li D, Li X., 2014
The detection of risk pathways, regulated by miRNAs, via the integration of sample-matched miRNA-mRNA profiles and pathway structure., Li J, Li C, Han J, Zhang C, Shang D, Yao Q, Zhang Y, Zhang C, Li D, Li X., 2014
Allele-Specific Behavior of Molecular Networks: Understanding Small-Molecule Drug Response in Yeast., Zhang F, Gao B, Xu L, Li C, Hao D, Zhang S, Zhou M, Su F, Chen X, Zhi H, Li X., 2013
Topologically inferring risk-active pathways toward precise cancer classification by directed random walk., Liu W, Li C, Xu Y, Yang H, Yao Q, Han J, Shang D, Zhang C, Su F, Li X, Xiao Y, Zhang F, Dai M, Li X., 2013
Area of Focus
Biomedical | Big Data | Cancer | Personalized Treatment | Medication | Bioinformatics | Mathematics | Research | Oncology | Data Analysis
