• Title/Summary/Keyword: prediction structure

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Reviving GOR method in protein secondary structure prediction: Effective usage of evolutionary information

  • Lee, Byung-Chul;Lee, Chang-Jun;Kim, Dong-Sup
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2003.10a
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    • pp.133-138
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    • 2003
  • The prediction of protein secondary structure has been an important bioinformatics tool that is an essential component of the template-based protein tertiary structure prediction process. It has been known that the predicted secondary structure information improves both the fold recognition performance and the alignment accuracy. In this paper, we describe several novel ideas that may improve the prediction accuracy. The main idea is motivated by an observation that the protein's structural information, especially when it is combined with the evolutionary information, significantly improves the accuracy of the predicted tertiary structure. From the non-redundant set of protein structures, we derive the 'potential' parameters for the protein secondary structure prediction that contains the structural information of proteins, by following the procedure similar to the way to derive the directional information table of GOR method. Those potential parameters are combined with the frequency matrices obtained by running PSI-BLAST to construct the feature vectors that are used to train the support vector machines (SVM) to build the secondary structure classifiers. Moreover, the problem of huge model file size, which is one of the known shortcomings of SVM, is partially overcome by reducing the size of training data by filtering out the redundancy not only at the protein level but also at the feature vector level. A preliminary result measured by the average three-state prediction accuracy is encouraging.

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Temporal Prediction Structure and Motion Estimation Method based on the Characteristic of the Motion Vectors (시간적 예측 구조와 움직임 벡터의 특성을 이용한 움직임 추정 기법)

  • Yoon, Hyo Sun;Kim, Mi Young
    • Journal of Korea Multimedia Society
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    • v.18 no.10
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    • pp.1205-1215
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    • 2015
  • Efficient multi-view coding techniques are needed to reduce the complexity of multi-view video which increases in proportion to the number of cameras. To reduce the complexity and maintain image quality and bit-rates, an motion estimation method and temporal prediction structure are proposed in this paper. The proposed motion estimation method exploits the characteristic of motion vector distribution and the motion direction and motion size of the block to place search points and decide the search patten adaptively. And the proposed prediction structure divides every GOP to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experiment results show that the complexity reduction of the proposed temporal prediction structure and motion estimation method over hierarchical B pictures prediction structure and TZ search method which are used in JMVC(Joint Multi-view Video Coding) reference model can be up to 45∼70% while maintaining similar video quality and bit rates.

Temporal Prediction Structure for Multi-view Video Coding (다시점 비디오 부호화를 위한 시간적 예측 구조)

  • Yoon, Hyo-Sun;Kim, Mi-Young
    • Journal of Korea Multimedia Society
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    • v.15 no.9
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    • pp.1093-1101
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    • 2012
  • Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding exploits inter-view correlations among pictures of neighboring views and temporal correlations among pictures of the same view. Multi-view video coding which uses many cameras requires a method to reduce the computational complexity. In this paper, we proposed an efficient prediction structure to improve performance of multi-view video coding. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several small groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experimental results show that the proposed prediction structure shows good performance in image quality and bit-rates. When compared to the performance of hierarchical B pictures of Fraunhofer-HHI, the proposed prediction structure achieved 0.07~0.13 (dB) of PSNR gain and was down by 6.5(Kbps) in bitrate.

Prediction of Stand Structure Dynamics for Unthinned Slash Pine Plantations

  • Lee, Young-Jin;Cho, Hyun-Je;Hong, Sung-Cheon
    • The Korean Journal of Ecology
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    • v.23 no.6
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    • pp.435-438
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    • 2000
  • Diameter distributions describe forest stand structure information. Prediction equations for percentiles of diameter distribution and parameter recovery procedures for the Weibull distribution function based on four percentile equations were applied to develop prediction system of even-aged slash pine stand structure development in terms of the number of stems per diameter class changes. Four percentiles of the cumulative diameter distribution were predicted as a function of stand characteristics. The predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level. Statistically, no significant differences were detected based on the data from 236 evaluation data sets. This stand level diameter distribution prediction system will be useful in slash pine stand structure modeling and in updating forest inventories for the long-term forest management planning.

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Improving Hit Ratio and Hybrid Branch Prediction Performance with Victim BTB (Victim BTB를 활용한 히트율 개선과 효율적인 통합 분기 예측)

  • Joo, Young-Sang;Cho, Kyung-San
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.10
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    • pp.2676-2685
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    • 1998
  • In order to improve the branch prediction accuracy and to reduce the BTB miss rate, this paper proposes a two-level BTB structure that adds small-sized victim BTB to the convetional BTB. With small cost, two-level BTB can reduce the BTB miss rate as well as improve the prediction accuracy of the hybrid branch prediction strategy which combines dynamic prediction and static prediction. Through the trace-driven simulation of four bechmark programs, the performance improvement by the proposed two-level BTB structure is analysed and validated. Our proposed BTB structure can improve the BTB miss rate by 26.5% and the misprediction rate by 26.75%

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BJRNAFold: Prediction of RNA Secondary Structure Base on Constraint Parameters

  • Li, Wuju;Ying, Xiaomin
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.287-293
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    • 2005
  • Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

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Protein Tertiary Structure Prediction Method based on Fragment Assembly

  • Lee, Julian;Kim, Seung-Yeon;Joo, Kee-Hyoung;Kim, Il-Soo;Lee, Joo-Young
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2004.11a
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    • pp.250-261
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    • 2004
  • A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is introduced. This method utilizes secondary structure prediction information and fragment assembly. The secondary structure prediction of proteins is performed with the PREDICT method which uses PSI-BLAST to generate profiles and a distance measure in the pattern space. In order to predict the tertiary structure of a protein sequence, we assemble fragments in the fragment library constructed as a byproduct of PREDICT. The tertiary structure is obtained by minimizing the potential energy using the conformational space annealing method which enables one to sample diverse low lying minima of the energy function. We apply PROFESY for prediction of some proteins with known structures, which shows good performances. We also participated in CASP5 and applied PROFESY to new fold targets for blind predictions. The results were quite promising, despite the fact that PROFESY was in its early stage of development. In particular, the PROFESY result is the best for the hardest target T0161.

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Genome Scale Protein Secondary Structure Prediction Using a Data Distribution on a Grid Computing

  • Cho, Min-Kyu;Lee, Soojin;Jung, Jin-Won;Kim, Jai-Hoon;Lee, Weontae
    • Proceedings of the Korean Biophysical Society Conference
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    • 2003.06a
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    • pp.65-65
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    • 2003
  • After many genome projects, algorithms and software to process explosively growing biological information have been developed. To process huge amount of biological information, high performance computing equipments are essential. If we use the remote resources such as computing power, storages etc., through a Grid to share the resources in the Internet environment, we will be able to obtain great efficiency to process data at a low cost. Here we present the performance improvement of the protein secondary structure prediction (PSIPred) by using the Grid platform, distributing protein sequence data on the Grid where each computer node analyzes its own part of protein sequence data to speed up the structure prediction. On the Grid, genome scale secondary structure prediction for Mycoplasma genitalium, Escherichia coli, Helicobacter pylori, Saccharomyces cerevisiae and Caenorhabditis slogans were performed and analyzed by a statistical way to show the protein structural deviation and comparison between the genomes. Experimental results show that the Grid is a viable platform to speed up the protein structure prediction and from the predicted structures.

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Prediction of Radiated Sound on Structure-acoustic Coupled Plate by the Efficient Configuration of Structural Sensors (구조센서의 효율적인 구성을 통한 구조 음향연성 평판의 방사음 예측)

  • Lee, Ok-Dong;Oh, Jae-Eung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.9
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    • pp.695-705
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    • 2014
  • In this paper, two types of techniques for the prediction of radiated sound pressure due to vibration of a structure are investigated. The prediction performance using wave-number sensing technique is compared to that of conventional prediction method, such as Rayleigh's integral method, for the prediction of far-field radiated sound pressure. For a coupled plate, wave-number components are predicted by the vibration response of plate and the prediction performance of far-field sound is verified. In addition, the applicability of distributed sensors that are not allowable to Rayleigh's integral method is considered and these can replace point sensors. Experimental implementation verified the prediction accuracy of far-field sound radiation by the wave-number sensing technique. Prediction results from the technique are as good as those of Rayleigh's integral method and with distributed sensors, more reduced computation time is expected. To predict the radiated sound by the efficient configuration of structural sensors, composed(synthesized) mode considering sound power contribution is determined and from this size and location of sensors are chosen. Four types of sensor configuration are suggested, simulated and compared.

USING AN ABSTRACTION OF AMINO ACID TYPES TO IMPROVE THE QUALITY OF STATISTICAL POTENTIALS FOR PROTEIN STRUCTURE PREDICTION

  • Lee, Jin-Woo
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.15 no.3
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    • pp.191-199
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    • 2011
  • In this paper, we adopt a position specific scoring matrix as an abstraction of amino acid type to derive two new statistical potentials for protein structure prediction, and investigated its effect on the quality of the potentials compared to that derived using residue specific amino acid identity. For stringent test of the potential quality, we carried out folding simulations of 91 residue A chain of protein 2gpi, and found unexpectedly that the abstract amino acid type improved the quality of the one-body type statistical potential, but not for the two-body type statistical potential which describes long range interactions. This observation could be effectively used when one develops more accurate potentials for structure prediction, which are usually involved in merging various one-body and many-body potentials.