A5001837630- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Cancer-related molecular mechanisms research
- Alzheimer's disease research and treatments
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
- Spectroscopy and Chemometric Analyses
- MicroRNA in disease regulation
- Endometrial and Cervical Cancer Treatments
- Computational Drug Discovery Methods
- Machine Learning in Bioinformatics
- Ferroptosis and cancer prognosis
- RNA modifications and cancer
- Financial Literacy, Pension, Retirement Analysis
- Genetic Associations and Epidemiology
- Ovarian cancer diagnosis and treatment
- Fractal and DNA sequence analysis
- Sarcoma Diagnosis and Treatment
- Neuroinflammation and Neurodegeneration Mechanisms
- Cervical Cancer and HPV Research
- Brain Tumor Detection and Classification
- Dementia and Cognitive Impairment Research
- Gene Regulatory Network Analysis
- Adversarial Robustness in Machine Learning
- Speech and Audio Processing
Shanghai Maritime University
2016-2025
Beijing University of Chemical Technology
2024
China Railway Construction Corporation (China)
2024
Affiliated Hospital of Taishan Medical University
2024
Shandong First Medical University
2024
The Affiliated Yongchuan Hospital of Chongqing Medical University
2021-2023
Shanghai University of International Business and Economics
2019-2023
Chongqing Medical University
2021-2023
Academy of Military Medical Sciences
2023
Xi'an University of Technology
2010-2022
The microbiota living in the human body has critical impacts on our health and disease, but a systems understanding of its relationships with disease remains limited. Here, we use large-scale text mining-based manually curated microbe–disease association data set to construct microbe-based network investigate between microbes genes, symptoms, chemical fragments drugs. We reveal that loops are significantly coherent. Microbe-based connections have strong overlaps those constructed by...
Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds thousands genes. However, because data in colossal amounts generated by DNA are usually complex, noisy, high-dimensional, and often hindered low statistical power, their exploitation difficult. To overcome these problems, two kinds unsupervised analysis methods for data: principal component (PCA) independent (ICA) have been developed...
Alzheimer’s disease, an irreversible neurodegenerative disorder, manifests through the progressive deterioration of memory and cognitive functions. While magnetic resonance imaging has become indispensable neuroimaging modality for disease diagnosis monitoring, current diagnostic paradigms predominantly rely on single-time-point data analysis, neglecting inherent longitudinal nature applications. Therefore, in this paper, we propose a multi-task feature selection algorithm classification...
Abstract Recent theoretical and experimental studies indicate that long‐chain noncoding RNAs (lncRNAs) are essential for the growth differentiation of cells occurrence development tumors in epigenetics, but regulation lncRNA on gene expression, transcriptional activation, interference diseases is still unclear. There an urgent need effective methods to discover significant lncRNAs with their functions regulatory mechanisms. For this purpose, a new method extracting based pathway crosstalk...
The wide use of high-throughput DNA microarray technology provide an increasingly detailed view human transcriptome from hundreds to thousands genes. Although biomedical researchers typically design experiments explore specific biological contexts, the relationships between genes are hard identified because they complex and noisy high-dimensional data often hindered by low statistical power. main challenge now is extract valuable information colossal amount gain insight into processes...
MicroRNAs (miRNAs) have great potential serving as tumor biomarkers and therapeutic targets. As the rapid development of high-throughput experimental technology, gene expression experiments become more specialized diversified. The complex data structure has brought challenge for identification biomarkers. In meantime, current statistical machine learning methods detecting problem low reliability biased criteria. This study aims to select combinatorial miRNA biomarkers, which higher...
Lymph node metastasis (LNM) is a critical unfavorable prognostic factor in endometrial cancer (EC). At present, models involving molecular indicators that accurately predict LNM are still uncommon. We addressed this gap by developing nomograms to individualize the risk of EC and identify low-risk group for LNM.In all, 776 patients who underwent comprehensive surgical staging with pelvic lymphadenectomy at First Affiliated Hospital Chongqing Medical University were divided into training...
The study of pathogenic mechanism at the genetic level by imaging genetics methods enables to effectively reveal association histopathology and genetics. However, there is a lack effective accurate tools establish models from macroscopic microscopic.The multi-constrained joint non-negative matrix factorization (MCJNMF) was developed for simultaneous integration genomic data image identify common modules related disease. Two types matrices were projected onto feature space, in which...
Melasma is an acquired pigmentation disease that mainly involves the development of symmetrical yellow-brown facial patches. The incidence rate increasing yearly. Therefore, actively studying exposure factors induce melasma could contribute to prevention and treatment this disease. In present review, possible were summarized.
Alzheimer’s disease (AD) is a progressively and fatally neurodegenerative disorder leads to irreversibly cognitive memorial damage in different brain regions. The identification analysis of the dysregulated pathways subnetworks among affected regions will provide deep insights for pathogenetic mechanism AD. In this paper, commonly specifically significant were identified from six AD Protein-protein interaction (PPI) data integrated add molecular biological information construct functional...
MRNA and lncRNA serve as a type of endogenous RNA in cell, which can competitively bind to the same miRNA through response elements (MREs), thereby regulating their respective expression levels, playing an important role post-transcriptional regulation, progress tumors.The proposed competing (ceRNA) hypothesis provides novel clues for occurrence development tumors, but integrative analysis methods diverse data are significantly limited.In order find out relationship among miRNA, mRNA lncRNA,...
Microenvironment-driven tumor heterogeneity causes the limitation of immunotherapy sarcomas. Nonetheless, systematical studies various molecular levels can enhance understanding microenvironment (TME) related to prognosis and provide novel insights precision immunotherapy. Three prognostic-related TME phenotypes were identified by consensus clustering relative infiltration 22 immune cells from 869 samples Additionally, integrative immunogenomic analysis is applied explore characteristics...