2010 IEEE International Conference on BioInformatics and BioEngineering最新文献

An Elastic Video Interpolation Methodology for Wireless Capsule Endoscopy Videos 一种用于无线胶囊内窥镜视频的弹性视频插值方法

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.16

A. Karargyris, N. Bourbakis

引用次数: 4

Quantification and Analysis of Combination Drug Synergy in High-Throughput Transcriptome Studies 高通量转录组研究中联合药物协同作用的定量分析

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.46

Z. Gümüş, F. Siso-Nadal, Ada Gjrezi, P. McDonagh, I. Khalil, P. Giannakakou, H. Weinstein

引用次数: 0

Using the Semantically Interoperable Biospecimen Repository Application, caTissue: End User Deployment Lessons Learned 使用语义上可互操作的生物标本库应用程序，caTissue:最终用户部署经验教训

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.71

J. London, Devjani Chatterjee

引用次数: 9

Identifying Hidden Confounders in Gene Networks by Bayesian Networks 利用贝叶斯网络识别基因网络中隐藏的混杂因素

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.35

Tomoya Higashigaki, Kaname Kojima, R. Yamaguchi, Masato Inoue, S. Imoto, S. Miyano

{"title":"Identifying Hidden Confounders in Gene Networks by Bayesian Networks","authors":"Tomoya Higashigaki, Kaname Kojima, R. Yamaguchi, Masato Inoue, S. Imoto, S. Miyano","doi":"10.1109/BIBE.2010.35","DOIUrl":"https://doi.org/10.1109/BIBE.2010.35","url":null,"abstract":"In the estimation of gene networks from microarray gene expression data, we propose a statistical method for quantification of the hidden confounders in gene networks, which were possibly removed from the set of genes on the gene networks or are novel biological elements that are not measured by microarrays. Due to high computational cost of the structural learning of Bayesian networks and the limited source of the microarray data, it is usual to perform gene selection prior to the estimation of gene networks. Therefore, there exist missing genes that decrease accuracy and interpretability of the estimated gene networks. The proposed method can identify hidden confounders based on the conflicts of the estimated local Bayesian network structures and estimate their ideal profiles based on the proposed Bayesian networks with hidden variables with an EM algorithm. From the estimated ideal profiles, we can identify genes which are missing in the network or suggest the existence of the novel biological elements if the ideal profiles are not significantly correlated with any expression profiles of genes. To the best of our knowledge, this research is the first study to theoretically characterize missing genes in gene networks and practically utilize this information to refine network estimation.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127720800","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

Fast Phased Small RNA Cycle Counting Algorithms 快速分阶段小RNA循环计数算法

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.30

F. S. Bao, Zhixin Xie, Yuanlin Zhang

{"title":"Fast Phased Small RNA Cycle Counting Algorithms","authors":"F. S. Bao, Zhixin Xie, Yuanlin Zhang","doi":"10.1109/BIBE.2010.30","DOIUrl":"https://doi.org/10.1109/BIBE.2010.30","url":null,"abstract":"Counting phased small RNA cycles (PSRC) from mapped small RNA positions is a repeatedly invoked subproblem in the computation of identifying TRANS-ACTING siRNA (TAS) loci and loci of other small RNAs forming through mechanisms similar to that of trans-acting small interfering RNAs (ta-siRNAs). The efficiency of counting PSRC has a clear impact on the efficiency of the algorithms predicting these loci. There are two closely related variants on counting PSRC in real applications: WPSRC, which counts the number of distinct small RNAs falling onto the phased positions in a sliding window, and MPSRC, which counts the maximum consecutive PSRC from mapped small RNA positions. In this paper, we develop fast algorithms for both WPSRC and MPSRC. Our algorithms have O(max(S)) time complexity, while the existing algorithm and its variant have O(|S|·max(S)) and O(|S|·L) time complexity for MPSRC and WPSRC respectively, where S is a set of mapped small RNA positions and L the length of sliding window for WPSRC. Experimental results on two real-life datasets show that our algorithms are significantly faster than the existing algorithm and its variant. The proposed algorithms are applicable to TAS-like clusters with any PSRC length including 21-nt.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133528233","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

Estimating the Expression of Transcript Isoforms from mRNA-Seq via Nonnegative Least Squares 利用非负最小二乘法估计mRNA-Seq转录异构体的表达

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.61

Hyunsoo Kim, Y. Bi, R. Davuluri

引用次数: 5

An Accurate Prediction Method for Protein Structural Class from Signal Patterns of NMR Spectra in the Absence of Chemical Shift Assignments 在没有化学移位赋值的情况下，利用核磁共振光谱信号模式准确预测蛋白质结构类别的方法

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.15

Hiromi Arai, N. Tochio, Tsuyoshi Kato, T. Kigawa, M. Yamamura

引用次数: 3

Use of Hilbert Huang Transform in Uterine Contraction Analysis 黄氏变换在子宫收缩分析中的应用

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.70

Kemal Aydın, R. M. Demirer, Coskun Bayrak

引用次数: 0

A Comparison between Transmembrane Helices and Reentrant Loops 跨膜螺旋和重入环的比较

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.54

Changhui Yan, Jingru Luo

引用次数: 1

Dynamic Complexity of the Temporal Transcriptional Regulation Program in Human Endotoxemia 人类内毒素血症中时间转录调控程序的动态复杂性

2010 IEEE International Conference on BioInformatics and BioEngineering Pub Date : 2010-05-31 DOI: 10.1109/BIBE.2010.27

Tung T. Nguyen, P. T. Foteinou, I. Androulakis, S. Calvano, S. Lowry

{"title":"Dynamic Complexity of the Temporal Transcriptional Regulation Program in Human Endotoxemia","authors":"Tung T. Nguyen, P. T. Foteinou, I. Androulakis, S. Calvano, S. Lowry","doi":"10.1109/BIBE.2010.27","DOIUrl":"https://doi.org/10.1109/BIBE.2010.27","url":null,"abstract":"Human endotoxemia is a well-accepted surrogate model for studying the acute inflammatory responses. In order to discover the complex underlying dynamics, identifying biologically relevant transcriptional regulators as well as their putative regulatory interactions with target genes is an essential step. However, prediction of relevant transcriptional regulators in higher eukaryotes remains a challenge both in silico and in vivo. In this study, we analyzed gene expression data from human blood leukocytes to extract four significant patterns of highly coexpressed genes that capture the essence of inflammatory phases. Upon identification of these patterns, a number of inflammation-specific pathways are selected by evaluating the enrichment of the corresponding subsets. Subsequently, statistically significant cis-regulatory modules (CRMs) are selected and decomposed into a list of relevant transcription factors (34 TFs) which are further validated from prior experiments and computational studies in literature. Additionally, our analysis also allows for the construction of a putative dynamic representation of the transcriptional regulatory program, making it become a critical enabler for unraveling regulatory interactions which is an essential step towards a quantification of dynamic transcriptional regulatory networks.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130029229","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: 0