2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology最新文献_第2页

Principal components analysis filters functionally significant peroxidase motions 主成分分析过滤功能显著过氧化物酶运动

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510723

M. Laberge, Istvan Kovesi

引用次数: 0

Missing value imputation methods for gene-sample-time microarray data analysis 基因-样品-时间微阵列数据分析的缺失值输入方法

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510349

Yifeng Li, A. Ngom, L. Rueda

引用次数: 13

Super-resolution of mammograms 乳房x线照片的超分辨率

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510384

Jun Zheng, O. Fuentes, M. Leung

引用次数: 9

Modeling treatment and drug effects at the molecular level using hybrid system theory 利用混合系统理论在分子水平上模拟治疗和药物效应

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510440

Xiangfang Li, Lijun Qian, E. Dougherty

{"title":"Modeling treatment and drug effects at the molecular level using hybrid system theory","authors":"Xiangfang Li, Lijun Qian, E. Dougherty","doi":"10.1109/CIBCB.2010.5510440","DOIUrl":"https://doi.org/10.1109/CIBCB.2010.5510440","url":null,"abstract":"In this paper, we propose to study the treatment and drug effects at the molecular level using a hybrid system model. Specifically, we propose a generic piecewise linear model to analyze drug effects on the state of the genes in a genetic regulatory network. We intend to answer the following question: given an initial state, would a treatment or drug (control input) drive the target gene to a new desired state that are not reachable without the treatment or drug? assuming that the concentration level of the drug remains constant. In other words, we try to identify whether there is a chance that the treatment or drug will be effective for changing gene expressions at all. We provide detailed analysis for two cases. In the first case, there is only one target gene; while in the second case, there is also another gene interacting with the target gene. The relationships between various parameters (of the genetic regulatory network and the design of the drug) and the convergence and the steady state of the controlled genes are derived analytically and discussed in detail. Simulations are performed using MATLAB/SIMULINK and the results confirmed our analytical findings.","PeriodicalId":340637,"journal":{"name":"2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125600033","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: 3

Speeding up subcellular localization by extracting informative regions of protein sequences for profile alignment 通过提取蛋白质序列的信息区域，加快亚细胞定位

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510320

Wei Wang, M. Mak, S. Kung

{"title":"Speeding up subcellular localization by extracting informative regions of protein sequences for profile alignment","authors":"Wei Wang, M. Mak, S. Kung","doi":"10.1109/CIBCB.2010.5510320","DOIUrl":"https://doi.org/10.1109/CIBCB.2010.5510320","url":null,"abstract":"The functions of proteins are closely related to their subcellular locations. In the post-proteomics era, the amount of gene and protein data grows exponentially, which necessitates the prediction of subcellular localization by computational means. This paper proposes mitigating the computation burden of alignment-based approaches to subcellular localization prediction by using the information provided by the N-terminal sorting signals. To this end, a cascaded fusion of cleavage site prediction and profile alignment is proposed. Specifically, the informative segments of protein sequences are identified by a cleavage site predictor. Then, only the informative segments are applied to a homology-based classifier for predicting the subcellular locations. Experimental results on a newly constructed dataset show that the method can make use of the best property of both approaches and can attain an accuracy higher than using the full-length sequences. Moreover, the method can reduce the computation time by 20 folds. We advocate that the method will be important for biologists to conduct large-scale protein annotation or for bioinformaticians to perform preliminary investigations on new algorithms that involve pairwise alignments.","PeriodicalId":340637,"journal":{"name":"2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127023168","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

Support vectors based correlation coefficient for gene and sample selection in cancer classification 基于支持向量的癌症分类中基因和样本选择的相关系数

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510689

P. Mundra, Jagath Rajapakse

引用次数: 3

A regression tree-based Gibbs sampler to learn the regulation programs in a transcription regulatory module network 一个基于回归树的吉布斯采样器来学习转录调控模块网络中的调控程序

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510433

Jianlong Qi, T. Michoel, G. Butler

{"title":"A regression tree-based Gibbs sampler to learn the regulation programs in a transcription regulatory module network","authors":"Jianlong Qi, T. Michoel, G. Butler","doi":"10.1109/CIBCB.2010.5510433","DOIUrl":"https://doi.org/10.1109/CIBCB.2010.5510433","url":null,"abstract":"Many algorithms have been proposed to learn transcription regulatory networks from gene expression data. Bayesian networks have obtained promising results, in particular, the module network method. The genes in a module share a regulation program (regression tree), consisting of a set of parents and conditional probability distributions. Hence, the method significantly decreases the search space of models and consequently avoids overfitting. The regulation program of a module is normally learned by a deterministic search algorithm, which performs a series of greedy operations to maximize the Bayesian score. The major shortcoming of the deterministic search algorithm is that its result may only represent one of several possible regulation programs. In order to account for the model uncertainty, we propose a regression tree-based Gibbs sampling algorithm for learning regulation programs in module networks. The novelty of this work is that a set of tree operations is defined for generating new regression trees from a given tree and we show that the set of tree operations is sufficient to generate a well mixing Gibbs sampler even in large data sets. The effectiveness of our algorithm is demonstrated by the experiments in synthetic data and real biological data.","PeriodicalId":340637,"journal":{"name":"2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133804093","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: 11

Functional data classification for temporal gene expression data with kernel-induced random forests 核诱导随机森林对时间基因表达数据的功能数据分类

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510482

Guangzhe Fan, Jiguo Cao, Jiheng Wang

引用次数: 11

A Discrete Fourier Transform method for alignment of visual evoked potentials 视觉诱发电位排列的离散傅立叶变换方法

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510704

Ismet Sahin, N. Yilmazer

{"title":"A Discrete Fourier Transform method for alignment of visual evoked potentials","authors":"Ismet Sahin, N. Yilmazer","doi":"10.1109/CIBCB.2010.5510704","DOIUrl":"https://doi.org/10.1109/CIBCB.2010.5510704","url":null,"abstract":"In this paper, we consider alignment of visual evoked potentials (EP) in the Discrete Fourier Transform (DFT) domain. Visual EPs have important clues for diagnosing medical problems such as multiple sclerosis and optic neuritis. The amplitude of visual EPs are usually smaller than the amplitude of spontaneous EPs which causes difficulties in reliably finding the latencies and amplitudes of important positive and negative peaks in the evoked responses. Therefore, noise cancellation becomes important for determining the features of interest in these waveforms. A well-known noise cancellation method is averaging multiple evoked potentials. Averaging after alignment of EP waveforms can improve the waveform quality substantially since usually evoked potentials have different characteristics and therefore have different latencies and amplitudes in response to the same visual stimulus. In this paper, we use a time alignment method which simultaneously reduces the spectral differences between all waveforms by minimizing the linearly phase shifted forms of the DFTs of these waveforms. We demonstrate that this method successfully aligns multiple visual EPs and achieves a smooth averaged waveform with reduced noise.","PeriodicalId":340637,"journal":{"name":"2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116164497","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: 2

Identifying essential features for the classification of real and pseudo microRNAs precursors using fuzzy decision trees 利用模糊决策树识别真实和伪microrna前体分类的基本特征

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2010-05-02 DOI: 10.1109/CIBCB.2010.5510430

Na'el Abu-halaweh, R. Harrison

{"title":"Identifying essential features for the classification of real and pseudo microRNAs precursors using fuzzy decision trees","authors":"Na'el Abu-halaweh, R. Harrison","doi":"10.1109/CIBCB.2010.5510430","DOIUrl":"https://doi.org/10.1109/CIBCB.2010.5510430","url":null,"abstract":"MicroRNAs play an important role in post-transcriptional gene regulation. Experimental approaches to identify microRNAs are expensive and time-consuming. Computational approaches have proven to be useful for identifying microRNA candidates. Most approaches rely on features extracted from miroRNA precursors (pre-microRNA) and their secondary structure. Selecting the appropriate set of features plays a critical role in improving the prediction accuracy of pre-microRNA candidates. This work aims to investigate the triplet elements encoding scheme and to identify essential features needed for the correct classification of pre-microRNAs. To achieve these goals, an extension of the triplet elements encoding scheme is introduced. Features extracted using the extended scheme were combined with global features introduced in the literature, and fuzzy decision tree (FDT) is used as a classification and a feature selection tool. Unlike previous machine-learning-based approaches, FDT produces a human comprehensible classification model. The interpretability of the classification model provides a means to identify the essential features needed to recognize microRNA candidates and offers a better understanding of this problem. Our results indicate that the triplet elements scheme is not superior to any of its proposed extensions. Further analysis revealed that including the features extracted using triplet elements scheme does not add any value to this classification problem but rather introduces some noisy features, and comparable classification results can be achieved by using only the six global features identified by FDT.","PeriodicalId":340637,"journal":{"name":"2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125963395","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: 7