The performance of a network server is directly influenced by its network I/O management architecture, i.e., its network I/O multiplexing mechanism. Existing benchmark tools focus on the evaluation of high-level service performance of network servers that implement specific application-layer protocols or the evaluation of low-level communication performance of network paths. However, such tools are not suitable for performance evaluation of server architectures. In this study, we developed a benchmark tool for network I/O management architectures. We implemented five representative network I/O management mechanisms as modules: multi-process, multi-thread, select, poll, and epoll. This modularised implementation enabled quantitative and fair comparisons among them. Our experimental results on Linux 2.6 revealed that the select-based and poll-based servers had no performance advantage over the others and the multi-process and multi-thread servers achieved a high performance almost equal to that of the epoll-based server.
{"title":"A Benchmark Tool for Network I/O Management Architectures","authors":"Eiji Kawai, S. Yamaguchi","doi":"10.2197/IPSJDC.4.138","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.138","url":null,"abstract":"The performance of a network server is directly influenced by its network I/O management architecture, i.e., its network I/O multiplexing mechanism. Existing benchmark tools focus on the evaluation of high-level service performance of network servers that implement specific application-layer protocols or the evaluation of low-level communication performance of network paths. However, such tools are not suitable for performance evaluation of server architectures. In this study, we developed a benchmark tool for network I/O management architectures. We implemented five representative network I/O management mechanisms as modules: multi-process, multi-thread, select, poll, and epoll. This modularised implementation enabled quantitative and fair comparisons among them. Our experimental results on Linux 2.6 revealed that the select-based and poll-based servers had no performance advantage over the others and the multi-process and multi-thread servers achieved a high performance almost equal to that of the epoll-based server.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128479150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peer-to-Peer multimedia streaming is expected to grow rapidly in the near future. Packet losses during transmission are a serious problem for streaming media as they result in degradation of the quality of service (QoS). Forward Error Correction (FEC) is a promising technique to recover the lost packets and improve the QoS of streaming media. However, FEC may degrade the QoS of all streaming due to the increased congestion caused by the FEC overhead when streaming sessions increase. Although streaming media can be categorized into live and on-demand streaming contents, conventional FEC methods apply the same FEC scheme for both contents without distinguishing them. In this paper, we clarify the effective ranges where each conventional FEC and Retransmission scheme works well. Then, we propose a novel FEC method that distinguishes two types of streaming media and is applied for on-demand streaming contents. It can overcome the adverse effect of the FEC overhead in on-demand streaming contents during media streaming and therefore reduce the packet loss due to the FEC overhead. As a result, the packet loss ratios of both live and on-demand streaming contents are improved. Moreover, it provides the QoS according to the requirements and environments of users by using layered coding of FEC. Thus, packet losses are recovered at each end host and do not affect the next-hop streaming. The numerical analyses show that our proposed method highly improves the packet loss ratio compared to the conventional method.
{"title":"Peer-to-Peer Multimedia Streaming with Guaranteed QoS for Future Real-time Applications","authors":"M. Hayasaka, T. Miki","doi":"10.2197/IPSJDC.4.128","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.128","url":null,"abstract":"Peer-to-Peer multimedia streaming is expected to grow rapidly in the near future. Packet losses during transmission are a serious problem for streaming media as they result in degradation of the quality of service (QoS). Forward Error Correction (FEC) is a promising technique to recover the lost packets and improve the QoS of streaming media. However, FEC may degrade the QoS of all streaming due to the increased congestion caused by the FEC overhead when streaming sessions increase. Although streaming media can be categorized into live and on-demand streaming contents, conventional FEC methods apply the same FEC scheme for both contents without distinguishing them. In this paper, we clarify the effective ranges where each conventional FEC and Retransmission scheme works well. Then, we propose a novel FEC method that distinguishes two types of streaming media and is applied for on-demand streaming contents. It can overcome the adverse effect of the FEC overhead in on-demand streaming contents during media streaming and therefore reduce the packet loss due to the FEC overhead. As a result, the packet loss ratios of both live and on-demand streaming contents are improved. Moreover, it provides the QoS according to the requirements and environments of users by using layered coding of FEC. Thus, packet losses are recovered at each end host and do not affect the next-hop streaming. The numerical analyses show that our proposed method highly improves the packet loss ratio compared to the conventional method.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127823713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Skeletal parallel programming makes both parallel programs development and parallelization easier. The idea is to abstract generic and recurring patterns within parallel programs as skeletons and provide them as a library whose parallel implementations are transparent to the programmer. SkeTo is a parallel skeleton library that enables programmers to write parallel programs in C++ in a sequential style. However, SkeTo's matrix skeletons assume that a matrix is dense, so they are incapable of efficiently dealing with a sparse matrix, which has many zeros, because of duplicated computations and commutations of identical values. This problem is solved by re-formalizing the matrix data type to cope with sparse matrices and by implementing a new C++ class of SkeTo with efficient sparse matrix skeletons based on this new formalization. Experimental results show that the new skeletons for sparse matrices perform well compared to existing skeletons for dense matrices.
{"title":"Parallel Skeletons for Sparse Matrices in SkeTo Skeleton Library","authors":"Yuki Karasawa, H. Iwasaki","doi":"10.2197/IPSJDC.4.167","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.167","url":null,"abstract":"Skeletal parallel programming makes both parallel programs development and parallelization easier. The idea is to abstract generic and recurring patterns within parallel programs as skeletons and provide them as a library whose parallel implementations are transparent to the programmer. SkeTo is a parallel skeleton library that enables programmers to write parallel programs in C++ in a sequential style. However, SkeTo's matrix skeletons assume that a matrix is dense, so they are incapable of efficiently dealing with a sparse matrix, which has many zeros, because of duplicated computations and commutations of identical values. This problem is solved by re-formalizing the matrix data type to cope with sparse matrices and by implementing a new C++ class of SkeTo with efficient sparse matrix skeletons based on this new formalization. Experimental results show that the new skeletons for sparse matrices perform well compared to existing skeletons for dense matrices.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128681928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the control operators “control” and “prompt” which manage part of continuations, that is, delimited continuations. They are similar to the well-known control operators“shift” and “reset”, but differ in that the former is dynamic, while the latter is static. In this paper, we introduce a static type system for “control”and “prompt” which does not use recursive types. We design our type system based on the dynamic CPS transformation recently proposed by Biernacki, Danvy and Millikin. We also introduce let-polymorphism into our type system, and show that our type system satisfies several important properties such as strong type soundness.
{"title":"A Type System for Dynamic Delimited Continuations","authors":"T. Yonezawa, Yukiyoshi Kameyama","doi":"10.2197/IPSJDC.4.182","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.182","url":null,"abstract":"We study the control operators “control” and “prompt” which manage part of continuations, that is, delimited continuations. They are similar to the well-known control operators“shift” and “reset”, but differ in that the former is dynamic, while the latter is static. In this paper, we introduce a static type system for “control”and “prompt” which does not use recursive types. We design our type system based on the dynamic CPS transformation recently proposed by Biernacki, Danvy and Millikin. We also introduce let-polymorphism into our type system, and show that our type system satisfies several important properties such as strong type soundness.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125260205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Comparative analysis of organisms with metabolic pathways gives important information about functions within organisms. In this paper, we propose a new method for comparing the metabolic pathways with reaction structures that include important enzymes. In this method, subgraphs from pathways that include ‘choke point’ or ‘load point’ are extracted as important “reaction structures,” and a “reaction structure profile,” which represents whether extracted reaction structures are observed in the metabolic pathway of other organisms, is created. Distance regarding function within organisms between species is defined using the “reaction structure profile.” By applying the proposed method to the metabolic networks of 64 representative organisms selected from Archaea, Eubacteria and Eukaryote in the KEGG database, we succeed in reconstructing a phylogenetic tree, and confirm the effectiveness of the method.
{"title":"Reaction Structure Profile : A Comparative Analysis of Metabolic Pathways Based on Important Substructures","authors":"Y. Ashida, Tomonobu Ozaki, T. Ohkawa","doi":"10.2197/IPSJDC.4.228","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.228","url":null,"abstract":"Comparative analysis of organisms with metabolic pathways gives important information about functions within organisms. In this paper, we propose a new method for comparing the metabolic pathways with reaction structures that include important enzymes. In this method, subgraphs from pathways that include ‘choke point’ or ‘load point’ are extracted as important “reaction structures,” and a “reaction structure profile,” which represents whether extracted reaction structures are observed in the metabolic pathway of other organisms, is created. Distance regarding function within organisms between species is defined using the “reaction structure profile.” By applying the proposed method to the metabolic networks of 64 representative organisms selected from Archaea, Eubacteria and Eukaryote in the KEGG database, we succeed in reconstructing a phylogenetic tree, and confirm the effectiveness of the method.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130460552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chemical and biological activities of compounds provide valuable information for discovering new drugs. The compound fingerprint that is represented by structural information of the activities is used for candidates for investigating similarity. However, there are several problems with predicting accuracy from the requirement in the compound structural similarity. Although the amount of compound data is growing rapidly, the number of well-annotated compounds, e.g., those in the MDL Drug Data Report (MDDR)database, has not increased quickly. Since the compounds that are known to have some activities of a biological class of the target are rare in the drug discovery process, the accuracy of the prediction should be increased as the activity decreases or the false positive rate should be maintained in databases that have a large number of un-annotated compounds and a small number of annotated compounds of the biological activity. In this paper, we propose a new similarity scoring method composed of a combination of the Tanimoto coefficient and the proximity measure of random forest. The score contains two properties that are derived from unsupervised and supervised methods of partial dependence for compounds. Thus, the proposed method is expected to indicate compounds that have accurate activities. By evaluating the performance of the prediction compared with the two scores of the Tanimoto coefficient and the proximity measure, we demonstrate that the prediction result of the proposed scoring method is better than those of the two methods by using the Linear Discriminant Analysis (LDA) method. We estimate the prediction accuracy of compound datasets extracted from MDDR using the proposed method. It is also shown that the proposed method can identify active compounds in datasets including several un-annotated compounds.
{"title":"A Combination Method of the Tanimoto Coefficient and Proximity Measure of Random Forest for Compound Activity Prediction","authors":"G. Kawamura, S. Seno, Y. Takenaka, H. Matsuda","doi":"10.2197/IPSJDC.4.238","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.238","url":null,"abstract":"Chemical and biological activities of compounds provide valuable information for discovering new drugs. The compound fingerprint that is represented by structural information of the activities is used for candidates for investigating similarity. However, there are several problems with predicting accuracy from the requirement in the compound structural similarity. Although the amount of compound data is growing rapidly, the number of well-annotated compounds, e.g., those in the MDL Drug Data Report (MDDR)database, has not increased quickly. Since the compounds that are known to have some activities of a biological class of the target are rare in the drug discovery process, the accuracy of the prediction should be increased as the activity decreases or the false positive rate should be maintained in databases that have a large number of un-annotated compounds and a small number of annotated compounds of the biological activity. In this paper, we propose a new similarity scoring method composed of a combination of the Tanimoto coefficient and the proximity measure of random forest. The score contains two properties that are derived from unsupervised and supervised methods of partial dependence for compounds. Thus, the proposed method is expected to indicate compounds that have accurate activities. By evaluating the performance of the prediction compared with the two scores of the Tanimoto coefficient and the proximity measure, we demonstrate that the prediction result of the proposed scoring method is better than those of the two methods by using the Linear Discriminant Analysis (LDA) method. We estimate the prediction accuracy of compound datasets extracted from MDDR using the proposed method. It is also shown that the proposed method can identify active compounds in datasets including several un-annotated compounds.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125269014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a novel clustering method based on graph theory for analysis of biological networks. In this method, each biological network is treated as an undirected graph and edges are weighted based on similarities of nodes. Then, maximal components, which are defined based on edge connectivity, are computed and the nodes are partitioned into clusters by selecting disjoint maximal components. The proposed method was applied to clustering of protein sequences and was compared with conventional clustering methods. The obtained clusters were evaluated using P-values for GO(GeneOntology) terms. The average P-values for the proposed method were better than those for other methods.
{"title":"A Clustering Method for Analysis of Sequence Similarity Networks of Proteins Using Maximal Components of Graphs","authors":"M. Hayashida, T. Akutsu, H. Nagamochi","doi":"10.2197/IPSJDC.4.207","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.207","url":null,"abstract":"This paper proposes a novel clustering method based on graph theory for analysis of biological networks. In this method, each biological network is treated as an undirected graph and edges are weighted based on similarities of nodes. Then, maximal components, which are defined based on edge connectivity, are computed and the nodes are partitioned into clusters by selecting disjoint maximal components. The proposed method was applied to clustering of protein sequences and was compared with conventional clustering methods. The obtained clusters were evaluated using P-values for GO(GeneOntology) terms. The average P-values for the proposed method were better than those for other methods.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131899217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We accelerate the time-consuming iterations for projective reconstruction, a key component of self-calibration for computing 3-D shapes from feature point tracking over a video sequence. We first summarize the algorithms of the primal and dual methods for projective reconstruction. Then, we replace the eigenvalue computation in each step by the power method. We also accelerate the power method itself. Furthermore, we introduce the SOR method for accelerating the subspace fitting involved in the iterations. Using simulated and real video images, we demonstrate that the computation sometimes becomes several thousand times faster.
{"title":"Fast Projective Reconstruction: Toward Ultimate Efficiency","authors":"H. Ackermann, K. Kanatani","doi":"10.2197/IPSJDC.4.257","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.257","url":null,"abstract":"We accelerate the time-consuming iterations for projective reconstruction, a key component of self-calibration for computing 3-D shapes from feature point tracking over a video sequence. We first summarize the algorithms of the primal and dual methods for projective reconstruction. Then, we replace the eigenvalue computation in each step by the power method. We also accelerate the power method itself. Furthermore, we introduce the SOR method for accelerating the subspace fitting involved in the iterations. Using simulated and real video images, we demonstrate that the computation sometimes becomes several thousand times faster.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134275386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As increasing clock frequency approaches its physical limits, a good approach to enhance performance is to increase parallelism by integrating more cores as coprocessors to general-purpose processors in order to handle the different workloads in scientific, engineering, and signal processing applications. In this paper, we propose a many-core matrix processor model consisting of a scalar unit augmented with b × b simple cores tightly connected in a 2D torus matrix unit to accelerate matrix-based kernels. Data load/store is overlapped with computing using a decoupled data access unit that moves b × b blocks of data between memory and the two scalar and matrix processing units. The operation of the matrix unit is mainly processing fine-grained b × b matrix multiply-add (MMA) operations. We formulate the data alignment operations including matrix transposition and skewing as MMA operations in order to overlap them with data load/store. Two fundamental linear algebra algorithms are designed and an- alytically evaluated on the proposed matrix processor: the Level-3 BLAS kernel, GEMM, and the LU factorization with partial pivoting, the main step in solving linear systems of equa- tions. For the GEMM kernel, the maximum speed of computing measured in FLOPs/cycle is approached for different matrix sizes, n , and block sizes, b. The speed of the LU factorization for relatively large values of n ranges from around 50–90% of the maximum speed depending on the model parameters. Overall, the analytical results show the merits of using the matrix unit for accelerating the matrix-based applications.
{"title":"Level-3 BLAS and LU Factorization on a Matrix Processor","authors":"A. Zekri, S. Sedukhin","doi":"10.2197/IPSJDC.4.151","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.151","url":null,"abstract":"As increasing clock frequency approaches its physical limits, a good approach to enhance performance is to increase parallelism by integrating more cores as coprocessors to general-purpose processors in order to handle the different workloads in scientific, engineering, and signal processing applications. In this paper, we propose a many-core matrix processor model consisting of a scalar unit augmented with b × b simple cores tightly connected in a 2D torus matrix unit to accelerate matrix-based kernels. Data load/store is overlapped with computing using a decoupled data access unit that moves b × b blocks of data between memory and the two scalar and matrix processing units. The operation of the matrix unit is mainly processing fine-grained b × b matrix multiply-add (MMA) operations. We formulate the data alignment operations including matrix transposition and skewing as MMA operations in order to overlap them with data load/store. Two fundamental linear algebra algorithms are designed and an- alytically evaluated on the proposed matrix processor: the Level-3 BLAS kernel, GEMM, and the LU factorization with partial pivoting, the main step in solving linear systems of equa- tions. For the GEMM kernel, the maximum speed of computing measured in FLOPs/cycle is approached for different matrix sizes, n , and block sizes, b. The speed of the LU factorization for relatively large values of n ranges from around 50–90% of the maximum speed depending on the model parameters. Overall, the analytical results show the merits of using the matrix unit for accelerating the matrix-based applications.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134060281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Protein-protein interactions play an important role in a number of biological activities. We developed two methods of predictingprotein-protein interaction site residues. One method uses only sequence information and the other method uses both sequence and structural information. We used support vector machine (SVM) with a position specific scoring matrix (PSSM) as sequence information and accessible surface area(ASA) of polar and non-polar atoms as structural information. SVM is used in two stages. In the first stage, an interaction residue is predicted by taking PSSMs of sequentially neighboring residues or taking PSSMs and ASAs of spatially neighboring residues as features. The second stage acts as a filter to refine the prediction results. The recall and precision of the predictor using both sequence and structural information are 73.6% and 50.5%, respectively. We found that using PSSM instead of frequency of amino acid appearance was the main factor of improvement of our methods.
{"title":"Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information","authors":"Masanori Kakuta, Shugo Nakamura, K. Shimizu","doi":"10.2197/IPSJDC.4.217","DOIUrl":"https://doi.org/10.2197/IPSJDC.4.217","url":null,"abstract":"Protein-protein interactions play an important role in a number of biological activities. We developed two methods of predictingprotein-protein interaction site residues. One method uses only sequence information and the other method uses both sequence and structural information. We used support vector machine (SVM) with a position specific scoring matrix (PSSM) as sequence information and accessible surface area(ASA) of polar and non-polar atoms as structural information. SVM is used in two stages. In the first stage, an interaction residue is predicted by taking PSSMs of sequentially neighboring residues or taking PSSMs and ASAs of spatially neighboring residues as features. The second stage acts as a filter to refine the prediction results. The recall and precision of the predictor using both sequence and structural information are 73.6% and 50.5%, respectively. We found that using PSSM instead of frequency of amino acid appearance was the main factor of improvement of our methods.","PeriodicalId":432390,"journal":{"name":"Ipsj Digital Courier","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130968023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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