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Search Results: 1 - 10 of 78099 matches for " Junfei Chen "
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PFP-RFSM: Protein fold prediction by using random forests and sequence motifs  [PDF]
Junfei Li, Jigang Wu, Ke Chen
Journal of Biomedical Science and Engineering (JBiSE) , 2013, DOI: 10.4236/jbise.2013.612145
Abstract:

Protein tertiary structure is indispensible in revealing the biological functions of proteins. De novo perdition of protein tertiary structure is dependent on protein fold recognition. This study proposes a novel method for prediction of protein fold types which takes primary sequence as input. The proposed method, PFP-RFSM, employs a random forest classifier and a comprehensive feature representation, including both sequence and predicted structure descriptors. Particularly, we propose a method for generation of features based on sequence motifs and those features are firstly employed in protein fold prediction. PFP-RFSM and ten representative protein fold predictors are validated in a benchmark dataset consisting of 27 fold types. Experiments demonstrate that PFP-RFSM outperforms all existing protein fold predictors and improves the success rates by 2%-14%. The results suggest sequence motifs are effective in classification and analysis of protein sequences.

 

SPI-based Regional Drought Prediction Using Weighted Markov Chain Model
Junfei Chen,Yang Yang
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: Drought is one of the most serious natural disasters in China. Drought disasters occur frequently and caused huge economic loss in recently. In this paper, a drought prediction model based on weighted Markov Chain is put forward. An application is demonstrated by Anhui province of Huaihe River in China. Based on the precipitation data during 1958-2006 at monthly scale, the different time scales Standardized Precipitation Index (SPI) is computed and the occurrence frequency of extreme drought, severe drought, moderate drought, slight drought and non-drought is obtained. The prediction of SPI is conducted by weighted Markov Chain model and the prediction accuracy is computed for the SPI of different time scales. The results show that weighted Markov Chain model is an effective tool for drought prediction and can provide decision-making for regional drought management.
Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast
Junfei Chen,Ming Li,Weiguang Wang
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/915053
Abstract: Drought is part of natural climate variability and ranks the first natural disaster in the world. Drought forecasting plays an important role in mitigating impacts on agriculture and water resources. In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI). We demonstrate model application by four stations in the Haihe river basin, China. The random-forest- (RF-) based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting. The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events.
Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin
Junfei Chen,Qiongji Jin,Jing Chao
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/235929
Abstract: With the global climate change, drought disasters occur frequently. Drought prediction is an important content for drought disaster management, planning and management of water resource systems of a river basin. In this study, a short-term drought prediction model based on deep belief networks (DBNs) is proposed to predict the time series of different time-scale standardized precipitation index (SPI). The DBN model is applied to predict the drought time series in the Huaihe River Basin, China. Compared with BP neural network, the DBN-based drought prediction model has shown better predictive skills than the BP neural network for the different time-scale SPI. This research can improve drought prediction technology and be helpful for water resources managers and decision makers in managing drought disasters.
Pricing for Catastrophe Bonds Based on Expected-value Model
Junfei Chen,Lu Zhang,Lingyan Xu
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: As the catastrophes cannot be avoided and result in huge economic losses, therefore the compensation issue for catastrophe losses become an important research topic. Catastrophe bonds can effectively disperse the catastrophe risks which mainly undertaken by the government and the insurance companies currently and focus on capital more effectively in broad capital market, therefore to be an ideal catastrophe securities product. This study adopts Expectancy Theory to supplement and improve the pricing of catastrophe bonds based on Value Theory. A model of expected utility is established to determine the conditions of the expected revenue R of catastrophe bonds. The pricing model of the value function is used to get the psychological value of R,U (R-R ̄), for catastrophe bonds. Finally, the psychological value is improved by the value according to expected utility and this can more accurately evaluate catastrophe bonds at a reasonable price. This research can provide decision-making for the pricing of catastrophe bonds.
Effects of cyclosporin-a on rat skeletal biomechanical properties
Yixin Chen, Xin Zheng, Rui Zou, Junfei Wang
BMC Musculoskeletal Disorders , 2011, DOI: 10.1186/1471-2474-12-240
Abstract: Fifty-six male 3-month-old Wistar rats were divided into five groups. Eight rats were randomly chosen as the basal group, while the others were randomly distributed into four groups of 12 animals each. One group was used as controls and received daily subcutaneous injection of 1 ml of saline solution; another three experimental groups were injected subcutaneously with CsA in a daily dose of 1.5, 7.5, and 15 mg/kg body weight respectively for 60 days. The bone biomechanical proprieties, the bone mineral density, as well as the trabecular bone architecture were measured at different anatomic sites, i.e. the lumbar vertebra, the middle femur shaft, and the proximal femur.CsA therapy at 7.5 and 1.5 mg/kg can significantly reduce the ultimate force, the ultimate stress and the energy absorption per unit of bone volume of the lumbar vertebra, with no effect on the middle femur. CsA therapy at 7.5 mg/kg can significantly reduce the ultimate force, the ultimate stress and the Young's modulus of the femoral neck, but not CsA at 1.5 mg/kg. Furthermore, CsA therapy at 7.5 and 1.5 mg/kg can significantly reduce the bone mineral density of the lumber vertebra and the proximal femur, but have no effect on the middle femur. CsA therapy at 7.5 and 1.5 mg/kg can also significantly reduce the bone volume fraction of the proximal tibia and the lumber vertebra, but has no effect on the cortical thickness of the middle femoral shaft. In the 15 mg/kg CsA group only one rat survived, and the kidney and liver histology of the survived rat showed extensive tissue necrosis.Long-term use of CsA can weaken the biomechanical properties and thus increase the fracture rate of the lumbar vertebra and the proximal femur. However, CsA therapy has less effect on the middle femur shaft. The effects of CsA on skeleton are site-specific.Cyclosporin A (CsA) has been widely used clinically to prevent organ rejection in post-transplantation and to ameliorate the autoimmune disorders. However, since the pat
Promoting Effect of Layered Titanium Phosphate on the Electrochemical and Photovoltaic Performance of Dye-Sensitized Solar Cells
Cheng Ping,Chen Ruihao,Wang Junfei,Yu Jianong
Nanoscale Research Letters , 2010,
Abstract: We reported a composite electrolyte prepared by incorporating layered α-titanium phosphate (α-TiP) into an iodide-based electrolyte using 1-ethyl-3-methylimidazolium tetrafluoroborate(EmimBF4) ionic liquid as solvent. The obtained composite electrolyte exhibited excellent electrochemical and photovoltaic properties compared to pure ionic liquid electrolyte. Both the diffusion coefficient of triiodide (I3 ) in the electrolyte and the charge-transfer reaction at the electrode/electrolyte interface were improved markedly. The mechanism for the enhanced electrochemical properties of the composite electrolyte was discussed. The highest conversion efficiency of dye-sensitized solar cell (DSSC) was obtained for the composite electrolyte containing 1wt% α-TiP, with an improvement of 58% in the conversion efficiency than the blank one, which offered a broad prospect for the fabrication of stable DSSCs with a high conversion efficiency.
Risk Assessment on Drought Disaster in China Based on Integrative Cloud Model
Junfei Chen,Shufang Zhao,Quanxi Shao,Huimin Wang
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: This study promotes cloud model for risk assessment of drought disaster. Cloud model is an effective tool in uncertain transforming between qualitative concepts and their quantitative expressions. Cloud is expressed by a concept with three quantitative characteristics of expectation, entropy and hyper entropy and the mapping between qualitative and quantitative is realized. In this study, considering the fuzziness and uncertainty of drought disaster, we established the comprehensive cloudy model based on entropy weight method for evaluating the risk of drought disaster. The disaster-affected rate and disaster-damaged rate are selected as the evaluation indices of drought degree. The model is applied to assess the drought disaster risk in China. The BP neural network, hard division method and integrative cloud model are compared, and the integrative cloud model is shown better for evaluating drought risk. This study shows that risk assessment of drought disaster based on cloud model is feasible and effective and can provide decision-making for the risk assessment of drought disaster.
Modeling and Simulation on Co-evolution of Emergency Agents for Unconventional Emergency Water Disaster
Junfei Chen,Guiyun Liu,Huimin Wang,Gaofeng Liu
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: The Unconventional Emergency Water Disaster (UEWD) is a water disaster that the society has not experienced or experienced few times and lacks the knowledge of its evolution and the experience to deal with it. The emergency system for UEWD is a complex adaptive system with different kinds of agents. In this study, we study the co-evolution mechanism of UEWD agents system. A dynamical model based on improved Logistic model and co-evolution theory is proposed. The impact factors of the emergency ability which mainly include the initial emergency capacity, the growth rate of the emergency ability, the maximun of the emergency ability, the quantity of the emergency agents and the coefficients of the competition and cooperation, is simulated and analyzed. The results show that the emergency ability under the co-stable state has nothing to do with the initial emergency capacity and the growth rate of the emergency ability. However, the time which reaches the co-stable state is positively related to the two factors. The maximun of the emergency ability and the quantity of the emergency agents have impacts on the emergency ability. The degree for the competition and cooperation among the agents is the key factor that affects the co-stable state of UEWD agents. At the end, some conclusions and suggestions are given to improve the emergency ability based on the characters of UEWD and the simulation results.
Polymorphisms on 8q24 Are Associated with Lung Cancer Risk and Survival in Han Chinese
Xuelin Zhang, Qun Chen, Chunya He, Weihua Mao, Ling Zhang, Xiaowen Xu, Junfei Zhu, Baofu Chen
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0041930
Abstract: Chromosome 8q24 is commonly amplified in many types of cancer, particularly lung cancer. Polymorphisms in this region are associated with risk of different cancers. To investigate the relationship between three single nucleotide polymorphisms (SNPs) (rs1447295, rs16901979 and rs6983267) on 8q24 and lung cancer risk, we conducted an association study in two Han Chinese populations: one population was from Zhejiang Province (576 case patients and 576 control subjects), whereas the other was from Fujian Province (576 case patients and 576 control subjects). We found that rs6983267 was significantly associated with an increased risk of lung cancer in both populations. Compared with the TT genotype, the GG genotype was associated with a significant 1.555-fold increased risk of lung cancer [95% confidence interval (CI) 1.218–1.986, P = 4.0×10?4]. This effect was more pronounced in never-smokers [odds ratio (OR) = 2.366, 95% CI 1.605–3.488, P = 1.4×10?5]. Analyses stratified by histology revealed that rs6983267 GG genotype was most associated with patients with other histological types (OR = 3.012, 95% CI 1.675–5.417, P = 2.3×10?4). The AA genotype of rs1447295 was associated with increased risk for adenocarcinoma compared with the CC genotype (OR = 2.260, 95% CI 1.174–4.353, P = 0.015). Furthermore, the GG genotype of rs6983267 was associated with worse survival in the Zhejiang population (hazard ratio (HR) = 1.646, 95% CI 1.099–2.464, P = 0.016). No association was observed for rs16901979. These results suggest that genetic variations on 8q24 may play significant roles in the development and progression of lung cancer.
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