A5100624532- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Consumer Retail Behavior Studies
- Advanced Radiotherapy Techniques
- Face and Expression Recognition
- Circular RNAs in diseases
- Remote-Sensing Image Classification
- Evolution and Genetic Dynamics
- Remote Sensing and Land Use
- Advanced Image Fusion Techniques
- Medical Imaging Techniques and Applications
- Customer churn and segmentation
- Molecular Biology Techniques and Applications
- Cancer Genomics and Diagnostics
- Advanced X-ray and CT Imaging
- Customer Service Quality and Loyalty
- Gene Regulatory Network Analysis
United Imaging Healthcare (China)
2023
Hunan University
2014-2020
Beijing University of Technology
2016
China Earthquake Administration
2014
Chongqing University of Education
2010
With the advance of high-throughput sequencing technologies, a great amount somatic mutation data in cancer have been produced, allowing deep analyzing tumor pathogenesis. However, majority these are cross-sectional rather than temporal, and it is difficulty to infer temporal order gene mutations from them. In this paper, we first show probabilistic graphical model (PGM) constrains selectivity relation among driver genes which presented by directed acyclic graph. We then apply an exponential...
High dimensional and unbalanced datasets are the main problems which prevent from achieving ideally churn prediction performance. Features selection is necessary to be adopted enhance model A new predicting framework proposed in this paper uses complementary fusion of multilayer features. Several subsets features were acquired according feature factorization construction respectively. The effective selected by contribution In way, imbalance defects class distributions can fixed, accuracy...
The association between microRNAs (miRNAs) and diseases is significant to understand the development progression of many human diseases. Given cost complexity biological experiments, computational method for predicting potential miRNAs disease will be an effective complement. In this article, we have developed a model (microRNA based on Bayesian probabilistic matrix factorization, MDBPMF) fully treatment factorization find associations by using HMDDv2.0 database, which contains proven...
Tumor gene expression data has the characteristic of high dimensionality and small sample size, which pose a rigorous challenge for tumor classification. Since not all genes are associated with phenotypes, irrelevant features seriously reduce learning performance. It is necessary to select relevant from original data. In this paper, we propose new filter feature selection method based on graph embedding framework manifold learning, named as LLRFC score. The relationship between classes...
The purpose of this study was to accurately predict or classify the beam GPR with an ensemble model by using machine learning for SBRT(VMAT) plans.
From the perspective of data science, we propose a cancer diagnosis method combining miRNA-lncRNA interaction pairs and class weight competition. First, is introduced into joint expression profiles, complex mechanism development demonstrated in depth through reappearance key association information. This an information ensemble three carcinogenic mechanisms at dataset construction level: classical genetics, epigenetics, effect between miRNAs lncRNAs. Then, put forward hybrid feature...
After the devastating earthquake, change detection with pre-earthquake images and post-earthquake can find seriously damaged area quickly, which provides important information for rescue. Shen et al. (2011) researched influence of image registration error on high resolution RS images[1]. Rathje (2005), Zhang (2013) made an intense research method to acquire earthquake damage[2][3]. In this paper, we identify damage by means regional optimizing correlation coefficient processed ratio image,...
MicroRNAs (miRNAs) play a key role in gene expression and regulation various organisms. They control wide range of biological processes are involved several types cancers by causing mRNA degradation or translational inhibition. However, the functions most miRNAs their precise regulatory mechanisms remain elusive. With accumulation data mRNAs, many computational methods have been proposed to predict miRNA–mRNA relationship. existing require number modules predefined that may be difficult...