2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)最新文献

Revision of the variational Bayesian method for uncovering genes regulatory network 基因调控网络的变分贝叶斯方法的改进

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169481

M. Sánchez-Castillo, I. M. Tienda-Luna, D. Blanco-Navarro, M. Perez

引用次数: 1

Targeting myocardial infarction-specific protein interaction network using computational analyses 利用计算分析靶向心肌梗死特异性蛋白相互作用网络

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169479

Nguyen T. Nguyen, Xiaolin Zhang, Yunji Wang, Hai-Chao Han, Yufang Jin, Galen Schmidt, R. Lange, R. Chilton, M. Lindsey

{"title":"Targeting myocardial infarction-specific protein interaction network using computational analyses","authors":"Nguyen T. Nguyen, Xiaolin Zhang, Yunji Wang, Hai-Chao Han, Yufang Jin, Galen Schmidt, R. Lange, R. Chilton, M. Lindsey","doi":"10.1109/GENSiPS.2011.6169479","DOIUrl":"https://doi.org/10.1109/GENSiPS.2011.6169479","url":null,"abstract":"Myocardial infarction (MI) is a leading cause of deaths in the United States. Currently, the high mortality rate in MI is partially due to the lacking of diagnostic and prognostic biomarkers. Therefore, the purpose of this study was to develop a framework to understand MI-specific protein interaction network and identify MI-specific biomarkers with public databases and literatures. We established an MI-specific protein interaction network, examined the statistical significance of the MI-specific network compared to random networks, and evaluated the importance of the MI-specified proteins with its network properties and research intensity. The established MI-specific protein interaction network had less sub-networks and more links in addition to higher measurements on closeness centrality, clustering coefficient and degree centrality, suggesting a strong connectivity of hub proteins, which confirmed the determination of key proteins based on structural evaluation. In summary, this study established a framework to integrate published data in literatures and provided a promising way to identify biomarkers post-myocardial infarction.","PeriodicalId":181666,"journal":{"name":"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122216703","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: 8

Feature set enhancement via hierarchical clustering for microarray classification 基于微阵列分类的分层聚类特征集增强

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169486

Mattia Bosio, Pau Bellot, P. Salembier, Albert Oliveras-Vergés

引用次数: 8

Joint corresponding feature identification and alignment for multiple LC/MS replicates 联合相应的特征鉴定和比对多个LC/MS重复

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169456

Jian Cui, Xuepo Ma, Jianqiu Zhang

{"title":"Joint corresponding feature identification and alignment for multiple LC/MS replicates","authors":"Jian Cui, Xuepo Ma, Jianqiu Zhang","doi":"10.1109/GENSiPS.2011.6169456","DOIUrl":"https://doi.org/10.1109/GENSiPS.2011.6169456","url":null,"abstract":"In Liquid Chromatography/Mass Spectrometry (LC-MS), identifying corresponding peptide features (LC peaks) in multiple replicate datasets plays a crucial role in the differential analysis of complex peptide or protein samples for biomarker discovery. Given a peptide sequence, we aim at identifying its LC peak intervals in all datasets simultaneously. Generally, features are first identified in each replicate dataset, and then the features are aligned using warping functions. In such a procedure, the error in feature identification will propagate to alignment. Instead, we consider the problem of joint feature identification and alignment in multiple datasets. Since accurate feature identification improves the accuracy of corresponding feature alignment and vice versa, joint processing provides better performance than separate processing. We propose an algorithm which combines peak identification quality scores, time shifts and the similarity of LC peak shapes between candidate corresponding features for accurate alignment. In addition, we also incorporate the approximate elution time interval of a peptide stored in an Accurate Time and Mass (ATM) database when available. We test our algorithm on publicly available datasets, and we compare its with that of separate feature identification and alignment. Results show that the number of accurately identified corresponding features is improved significantly by using the proposed method.","PeriodicalId":181666,"journal":{"name":"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131427417","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

ECF sigma factor-associated regulatory networks in Streptomyces colicolor A3(2) 大色链霉菌A3中ECF sigma因子相关调控网络的研究(2)

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169475

Zhan Zhou, Qi Li, Julie Tudyk, Yong-Quan Li, Yufeng Wang

引用次数: 0

Gene network inference via sparse structural equation modeling with genetic perturbations 基于遗传扰动的稀疏结构方程模型的基因网络推断

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169445

Xiaodong Cai, J. Bazerque, G. Giannakis

引用次数: 13

The effect of certain Boolean functions in stability of networks with varying topology 某些布尔函数对拓扑结构变化网络稳定性的影响

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169431

V. H. Louzada, Fabricio M. Lopes, R. F. Hashimoto

{"title":"The effect of certain Boolean functions in stability of networks with varying topology","authors":"V. H. Louzada, Fabricio M. Lopes, R. F. Hashimoto","doi":"10.1109/GENSiPS.2011.6169431","DOIUrl":"https://doi.org/10.1109/GENSiPS.2011.6169431","url":null,"abstract":"The stability of biological organisms is a major feature which contributes to their survival in the environment. However, the study of the stability in vivo is a very hard challenge. An objective way for the stability analysis is to adopt the Boolean network model, which can qualitatively describe the behavior of biological networks as well as allows the analysis of the results in a comprehensive and global way. Besides, certain Boolean function classes play an important role in Boolean network stability. In addition to this relationship, it is expected that many classes of network topology assigns greater or lesser resistance to damage. In this work, we define “local stability” as the stability resulted from the presence of a certain Boolean function class, such as the canalyzing Boolean functions, and “global stability” as the result of a certain network topology, such as the scale-free topology. Next, we investigate the interaction between these two factors using the size of the largest basin of attraction and generalized Derrida curves as measures for network stability. Our results show that there is a “topology order” for certain Boolean function classes, and that these two factors should be jointly addressed in future analysis of network stability.","PeriodicalId":181666,"journal":{"name":"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129410430","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

Inference of a genetic regulatory network model from limited time series data 从有限时间序列数据推断遗传调控网络模型

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169470

Saad Haider, R. Pal

引用次数: 3

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data 生存分析方法在LC-MS蛋白质组学数据定量分析中的应用

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169453

Carmen D. Tekwe, Alan R. Dabney, Raymond J. Carroll

引用次数: 19

Geometrical modification of wavelet SVM kernels and its application in microarray analysis 小波支持向量机核的几何修正及其在微阵列分析中的应用

2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) Pub Date : 2011-12-01 DOI: 10.1109/GENSiPS.2011.6169467

Hong Cai, Yufeng Wang

引用次数: 2