Protein structure Quality Assessment（QA） is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure ...Protein structure Quality Assessment（QA） is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA.In this work, we developed a new Hidden Markov Model（HMM） to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities：（1） encoding local structure of each position by jointly considering sequence and structure information, and（2）assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP,and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets.展开更多
Pipeline processing is applied to mutiple flow tables(MFT)in the switch of software-defined network(SDN)to increase the throughput of the flows.However,the processing time of each flow increases as the size or number ...Pipeline processing is applied to mutiple flow tables(MFT)in the switch of software-defined network(SDN)to increase the throughput of the flows.However,the processing time of each flow increases as the size or number of flow tables gets larger.In this paper we propose a novel approach called PopFlow where a table keeping popular flow entries is located up front in the pipeline,and an express path is provided for the flow matching the table.A Markov model is employed for the selection of popular entries considering the match latency and match frequency,and Queuing theory is used to model the flow processing time of the existing MFT-based schemes and the proposed scheme.Computer simulation reveals that the proposed scheme substantially reduces the flow processing time compared to the existing schemes,and the diference gets more significant as the flow arrival rate increases.展开更多
基金supported by National Institutes of Health grants R21/R33-GM078601 and R01-GM100701
文摘Protein structure Quality Assessment（QA） is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA.In this work, we developed a new Hidden Markov Model（HMM） to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities：（1） encoding local structure of each position by jointly considering sequence and structure information, and（2）assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP,and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets.
基金supported by Institute for In-fornation&communications Technology Promotion(ITP)grant funded by the Korea government(MSIT)(2016-0-00133,Research on Edge computing via collctive intelligence of hyperconnection IoT nodes)Korea,under the National Program for Excellence in Sw supervised by the ITP(Institute for Information&communications Technology Promotion)(2015-0-00914)Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(2016R1A6A3A11931385,Research of key technologies based on software defined wireless sensor network for realtime public safety service,2017R1A2B2009095,Research on SDN-based WSN Supporting Real-time Stream Data Processing and Multi-connectivity,2019R1I1A1A01058780,Eficient Management of SDN-based Wireless Sensor Network Using Machine Learning Technique),the second Brain Korea 21 PLUS project.
文摘Pipeline processing is applied to mutiple flow tables(MFT)in the switch of software-defined network(SDN)to increase the throughput of the flows.However,the processing time of each flow increases as the size or number of flow tables gets larger.In this paper we propose a novel approach called PopFlow where a table keeping popular flow entries is located up front in the pipeline,and an express path is provided for the flow matching the table.A Markov model is employed for the selection of popular entries considering the match latency and match frequency,and Queuing theory is used to model the flow processing time of the existing MFT-based schemes and the proposed scheme.Computer simulation reveals that the proposed scheme substantially reduces the flow processing time compared to the existing schemes,and the diference gets more significant as the flow arrival rate increases.
