2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology最新文献_第2页

A Simple Algorithm for (l, d) Motif Search1 (l, d) Motif搜索的一种简单算法

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925721

Dolly Sharma, S. Rajasekaran

引用次数: 8

An automatic gene ontology software tool for bicluster and cluster comparisons 用于双聚类和聚类比较的自动基因本体软件工具

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925723

Fadhl M. Al-Akwaa, Y. Kadah

引用次数: 12

A method for improving protein localization prediction from datasets with outliers 一种基于异常值数据集的蛋白质定位预测改进方法

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925714

Jiang Tian, Hong Gu, Wenqi Liu

{"title":"A method for improving protein localization prediction from datasets with outliers","authors":"Jiang Tian, Hong Gu, Wenqi Liu","doi":"10.1109/CIBCB.2009.4925714","DOIUrl":"https://doi.org/10.1109/CIBCB.2009.4925714","url":null,"abstract":"Large-scale genome analysis and drug discovery require an automated prediction method for protein subcellular localization, and Support Vector Machines (SVMs) effectively solve this problem in a supervised manner. However, the protein subcellular localization datasets obtained from experiments always contain outliers, which can lead to poor generalization ability and classification accuracy. To address this issue, we first analyzed the influence of Principal Component Analysis (PCA) on classification performance, and then proposed a hybrid method for prediction of protein subcellular localization based on Weighted Supported Vector Machine (WSVM) and PCA. Different weights were assigned to different data points, so the training algorithm could learn the decision boundary according to the relative importance of the data points. After performing dimension reduction operations on the datasets, kernel-based possibilistic c-means (KPCM) was chosen to generate weights for this algorithm, as it generates relative high values for important data points but low values for outliers. Experimental results on a benchmark dataset show promising results, which confirms the effectiveness of the proposed method in terms of prediction accuracy.","PeriodicalId":162052,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128492740","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}

引用次数: 1

An approach for RNA secondary structure prediction based on Bayesian network 基于贝叶斯网络的RNA二级结构预测方法

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925703

Tianhua Wu, Zhidong Deng, Dandan Song

引用次数: 1

Steady-state analysis of genetic regulatory networks modeled by nonlinear ordinary differential equations 非线性常微分方程遗传调控网络的稳态分析

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925726

Haixin Wang, Lijun Qian, E. Dougherty

引用次数: 7

DDPIn - Distance and density based protein indexing DDPIn -基于距离和密度的蛋白质索引

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925737

D. Hoksza

引用次数: 4

Knee MR image segmentation combining contextual constrained neural network and level set evolution 结合上下文约束神经网络和水平集进化的膝关节MR图像分割

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925738

Haw-Chang Lan, Tsai-Rong Chang, Wen-Ching Liao, Yi-Nung Chung, P. Chung

{"title":"Knee MR image segmentation combining contextual constrained neural network and level set evolution","authors":"Haw-Chang Lan, Tsai-Rong Chang, Wen-Ching Liao, Yi-Nung Chung, P. Chung","doi":"10.1109/CIBCB.2009.4925738","DOIUrl":"https://doi.org/10.1109/CIBCB.2009.4925738","url":null,"abstract":"Tracking the patella movement trajectory during the bending process of the knee is one essential step to knee pain diagnosis. In order for tracking patella, correct segmentation of the femur and patella from the axial knee MR image is indispensable. But the strong adhesion of the soft tissue around femur and patella, the gray-level similarities of adjacent organs, and the non-uniform gray intensity due to the degradation of the magnetic propagation make the MR image segmentation challenging. In this paper, we proposed a mechanism combining contextual constraint neural network (CCNN) and level set evolution to segment the femur and patella. The segmentation can be divided into two phases. In the first phase SOM and CCNN are applied to extract initial contours of the femur and patella. Consequently in the second phase, modified level set evolution is performed, with the extracted contours as the initial zero level set contour, to accomplish the segmentation of the femur and patella. Our experimental results show that the femur and patella can be correctly segmented for tracking patella movement.","PeriodicalId":162052,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122486316","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}

引用次数: 4

A novel LDA and PCA-based hierarchical scheme for metagenomic fragment binning 一种新的基于LDA和pca的宏基因组片段分割分层方案

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925707

Hao Zheng, Hongwei Wu

引用次数: 7

Simulation of the impact of retroviruses on genome organization of an artificial organism 逆转录病毒对人工生物基因组组织影响的模拟

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925720

D. Ashlock, W. Ashlock

引用次数: 3

Bioinformatics: Implementation of a proposed upgraded Smith-Waterman algorithm for local alignment 生物信息学:提出的局部比对升级Smith-Waterman算法的实现

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI: 10.1109/CIBCB.2009.4925712

Md. Shihabuddin Sadi, Abu Z. Mohammad Sami, I. Ahmed, A. B. M. Ruhunnabi, Nirmalendu Das

引用次数: 4