2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)最新文献_第4页

A parametric Bayesian method to test the association of rare variants 一个参数贝叶斯方法来检验罕见变异的关联

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112366

Yufeng Shen, Y. Cheung, Shuang Wang, I. Pe’er

引用次数: 2

Liver targeting effect of vinegar-baked Radix Bupleuri on oxymatrine in mice 醋烤柴胡对小鼠氧化苦参碱的肝脏靶向作用

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112462

Ruizhi Zhao, You-jun Chen, Jian Cai

引用次数: 7

Employing Machine Learning Techniques for Data Enrichment: Increasing the Number of Samples for Effective Gene Expression Data Analysis 利用机器学习技术进行数据丰富:增加有效基因表达数据分析的样本数量

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBM.2011.105

U. Erdogdu, Mehmet Tan, R. Alhajj, Faruk Polat, D. Demetrick, J. Rokne

{"title":"Employing Machine Learning Techniques for Data Enrichment: Increasing the Number of Samples for Effective Gene Expression Data Analysis","authors":"U. Erdogdu, Mehmet Tan, R. Alhajj, Faruk Polat, D. Demetrick, J. Rokne","doi":"10.1109/BIBM.2011.105","DOIUrl":"https://doi.org/10.1109/BIBM.2011.105","url":null,"abstract":"For certain domains, e.g. bioinformatics, producing more real samples is costly, error prone and time consuming. Therefore, there is a need for an intelligent automated process capable of substituting the real samples by artificial samples that carry the same characteristics as the real samples and hence could be used for running comprehensive testing of new methodologies. Motivated by this need, we describe a novel approach that integrates Probabilistic Boolean Network and genetic algorithm based techniques into a framework that uses some existing real samples as input and successfully produces new samples as output. The new samples will inspire the characteristics of the existing samples without duplicating them. This leads to diversity in the samples and hence a more rich set of samples to be used in testing. The developed framework incorporates two models (perspectives) for sample generation. We illustrate its applicability for producing new gene expression data samples, a high demanding area that has not received attention. The two perspectives employed in the process are based on models that are not closely related, the independence eliminates the bias of having the produced approach covering only certain characteristics of the domain and leading to samples skewed towards one direction. The produced results are very promising in showing the effectiveness, usefulness and applicability of the proposed multi-model framework.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"9 1","pages":"238-242"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88615678","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: 5

Mining fetal magnetocardiogram data for high-risk fetuses 挖掘胎儿心脏磁图数据的高危胎儿

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112563

D. Snider, Xiaowei Xu

引用次数: 0

Fracture detection and quantitative measure of displacement in pelvic CT images 骨盆CT图像的骨折检测与位移定量测量

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112437

Jie Wu, Pavani Davuluri, Ashwin Belle, Charles Cockrell, Yang Tang, Kevin Ward, R. Hobson, K. Najarian

{"title":"Fracture detection and quantitative measure of displacement in pelvic CT images","authors":"Jie Wu, Pavani Davuluri, Ashwin Belle, Charles Cockrell, Yang Tang, Kevin Ward, R. Hobson, K. Najarian","doi":"10.1109/BIBMW.2011.6112437","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112437","url":null,"abstract":"Traumatic pelvic injury is a severe and common injury in the United States. The automatic detection of fractures in pelvic CT images is a significant contribution for assisting physicians in making faster and more accurate patient diagnostic decisions and treatment planning. However, due to the low resolution and quality of the original images, the complexity of pelvic structures, and the difference in visual characteristics of fracture by their location, it is difficult to detect and accurately locate the pelvic fractures and determine the severity of the injury. In this paper, an automatic hierarchical algorithm for detecting pelvic bone fractures in CT scans is proposed. The algorithm utilizes symmetric comparison, adaptive windowing, boundary tracing, wavelet transform. Also, the quantitative measure of fracture severity in pelvic CT scans is defined. The results are promising, demonstrating that the proposed method is capable of automatically detecting both major and minor fractures accurately, shows potential for clinical application. Statistical results also indicate the superiority of the proposed method.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"14 1","pages":"600-606"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86702180","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

Balance-bagging-PRFS algorithm for feature optimization on insomnia data intervened by traditional Chinese Medicine 中药干预失眠数据特征优化的Balance-bagging-PRFS算法

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112485

Xiao-bo Yang, Shixing Yan, Zheng-yang Zhou, Guozheng Li, Yan Li, Xin-feng Guo

{"title":"Balance-bagging-PRFS algorithm for feature optimization on insomnia data intervened by traditional Chinese Medicine","authors":"Xiao-bo Yang, Shixing Yan, Zheng-yang Zhou, Guozheng Li, Yan Li, Xin-feng Guo","doi":"10.1109/BIBMW.2011.6112485","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112485","url":null,"abstract":"Goal: Traditional Chinese Medicine (TCM) focuses on individual diagnosis. Besides the analysis methods on group level, clinical experimental data could also be researched with Information Technology to optimize the feature for individual healing effect; Method: we propose and apply a new method of feature optimization — Balance-Bagging-PRFS — to optimize the feature of insomnia intervened by TCM, aiming at solving problems typically in TCM data, such as mixing of discrete and continuous features and data imbalance; Result: from the view of all data, it is found that different levels of \"ISI baseline score\" and \"Insomnia severity\" have important influence on the curative effect. In treat group, different values of \"environment\" and \"social field baseline\" make remarkable difference on curative effect; while in control group, in which patients are treated with the placebo, \"social field baseline\", \"survival quality baseline\", and \"classification of constitution\" make sense; Conclusion: the method of Balance-Bagging-PRFS achieves good results in feature optimization for data from insomnia interfered by TCM, and it provides a basis for TCM individual diagnosis and for further optimization of symptom.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"28 1","pages":"854-857"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82017161","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

A New Measurement for Evaluating Clusters in Protein Interaction Networks 一种评价蛋白质相互作用网络簇的新方法

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBM.2011.47

Min Li, Xuehong Wu, Jianxin Wang, Yi Pan

{"title":"A New Measurement for Evaluating Clusters in Protein Interaction Networks","authors":"Min Li, Xuehong Wu, Jianxin Wang, Yi Pan","doi":"10.1109/BIBM.2011.47","DOIUrl":"https://doi.org/10.1109/BIBM.2011.47","url":null,"abstract":"Clustering of protein-protein interaction networks is one of the most prevalent methods for identifying protein complexes and functional modules, which is crucial to understanding the principles of cellular organization and prediction of protein functions. In the past few years, many computational methods have been proposed. However, it is always a challenging task to evaluate how well the clusters are identified. Even for the most popular measurements, F-measure and Pvalue, bias exists for evaluating the identified clusters. In this paper, we propose a new measurement, named hF-measure, to evaluate clusters more finely and distinctly. First, we defined the hierarchical consistency and the hierarchical similarity. Then, we propose a new hierarchical measurement of hF-measure by taking into account the hierarchical organization of functional annotations and the functional similarities among proteins. The new measurement hF-measure can discriminate between different types of errors which cannot be distinguished by F-measure. The experimental results based on Gene Ontology (GO) and yeast functional modules show that hF-measure evaluates clusters more accurately when compared to F-measure.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"8 1","pages":"63-68"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83621992","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

iQuant: A fast yet accurate GUI tool for transcript quantification iQuant:一个快速而准确的GUI工具，用于转录量化

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBMW.2011.6112556

Tin Chi Nguyen, N. Deng, Guorong Xu, Z. Duan, D. Zhu

引用次数: 5

Efficient and Fast Analysis for Detecting High Order Gene-by-Gene Interactions in a Genome-Wide Association Study 在全基因组关联研究中检测高阶基因间相互作用的高效快速分析

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBM.2011.103

Sohee Oh, Jaehoon Lee, Min-Seok Kwon, Kyunga Kim, T. Park

引用次数: 1

A Computational Pipeline for LC-MS/MS Based Metabolite Identification 基于LC-MS/MS的代谢物鉴定计算管道

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) Pub Date : 2011-11-12 DOI: 10.1109/BIBM.2011.89

Bin Zhou, J. Xiao, H. Ressom

引用次数: 3