2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)最新文献_第5页

Sequential diagonal linear discriminant analysis (SeqDLDA) for microarray classification and gene identification 序列对角线性判别分析(SeqDLDA)用于微阵列分类和基因鉴定

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.124

R. Pique-Regi, Antonio Ortega, S. Asgharzadeh

{"title":"Sequential diagonal linear discriminant analysis (SeqDLDA) for microarray classification and gene identification","authors":"R. Pique-Regi, Antonio Ortega, S. Asgharzadeh","doi":"10.1109/CSBW.2005.124","DOIUrl":"https://doi.org/10.1109/CSBW.2005.124","url":null,"abstract":"In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA), since reliable estimates of the covariance matrix cannot be obtained. Alternative techniques based on Diagonal LDA (DLDA) combined with an independent gene selection (filtering) have been proposed. In this paper we propose a novel sequential DLDA (SeqDLDA) technique that combines gene selection and classification. At each iteration, one gene is sequentially added and the linear discriminant (LD) recomputed using the DLDA model (i.e., a diagonal co-variance matrix). Classical DLDA will add the gene with highest t-test score without checking the resulting model. In contrast, SeqDLDA will find the one gene that better improves class separation after recomputing the model measured using a robustified t-test score. We evaluate the new method in several 2-class datasets (Neuroblastoma, Prostate, Leukemia, Colon) using 10-fold cross-validation. For example, for the Neuroblastoma data set, the average misclassification rate of DLDA (16.91%) is significantly reduced to 13.87% using SeqDLDA.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133513092","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: 21

An approach to distributed interactive simulation and visualization of complex systems using cluster computing 基于集群计算的复杂系统分布式交互仿真与可视化方法

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.20

D. Gračanin

{"title":"An approach to distributed interactive simulation and visualization of complex systems using cluster computing","authors":"D. Gračanin","doi":"10.1109/CSBW.2005.20","DOIUrl":"https://doi.org/10.1109/CSBW.2005.20","url":null,"abstract":"When dealing with complex systems, interactive, realtime simulations require significant computational capabilities that can be provided by cluster computing. Current cluster computing based techniques are mostly focused on batch jobs. However, it is possible to use clusters so that an application can run and directly communicate with the remote client(s). Direct communication enables, without loss of accuracy or frame rate, real time visualization of and interaction with much larger models compared to a single machine implementation. The degree of coupling between the dependent variables in the model determines the degree of parallelization that can be achieved by evaluating the solution for each dependent variable in parallel. A distributed mass-spring simulation system was developed to serve as an open platform that can be used to improve the scalability of the simulation computation. Several techniques are used to improve scalability, both in terms of the problem size and number of clients. The developed system provides support for large scale mass-spring simulations to leverage available cluster computing and visualization resources. It can be applied to a wide range of problems related to de-formable solids including many biologically related like human organ modeling and medical animation where realtime feedback is required.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131772891","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

A new clustering strategy with stochastic merging and removing based on kernel functions 一种基于核函数的随机合并和去除聚类策略

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.10

Huimin Geng, H. Ali

{"title":"A new clustering strategy with stochastic merging and removing based on kernel functions","authors":"Huimin Geng, H. Ali","doi":"10.1109/CSBW.2005.10","DOIUrl":"https://doi.org/10.1109/CSBW.2005.10","url":null,"abstract":"With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they cannot subsequently be separated. Also, when a top-down algorithm separates two elements, they can't be rejoined. Such greedy property may lead to premature convergence and consequently lead to a clustering that is far from optimal. To overcome this problem, we propose a new Stochastic Message Passing Clustering (SMPC) method based on the Message Passing Clustering (MPC) algorithm introduced in our earlier work. SMPC, as a generalized version of MPC, extends the clustering algorithm from a deterministic process to a stochastic process, adding two major advantages. First, in deciding the merging cluster pair, the influences of all clusters are quantified by probabilities, estimated by kernel functions based on their relative distances. Secondly, clustering can be undone to improve the clustering performance when the algorithm detects elements which don't have good probabilities inside the cluster and moves them outside. The test results on colon cancer gene-expression data show that SMPC performs better than the deterministic MPC or hierarchical clustering method.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128998365","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

PLATCOM: a platform for computational comparative genomics on the Web PLATCOM:一个网络计算比较基因组学平台

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.107

Kwangmin Choi, Jeong-Hyeon Choi, A. Saple, Zhiping Wang, Jason Lee, Sun Kim

引用次数: 0

Incorporating life sciences applications in the architectural optimizations of next-generation petaflop-system 将生命科学应用纳入下一代千万亿次浮点运算系统的架构优化

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.77

David A. Bader, Vipin Sachdeva

引用次数: 3

Functional modularity in a large-scale mammalian molecular interaction network 大型哺乳动物分子相互作用网络的功能模块化

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.67

Andreas Krämer, D. Richards, James O. Bowlby, R. Felciano

引用次数: 1

Massive multiple sequence alignment of 16S bacterial ribosomal RNAs using ClustalW-Message Passing Interface (MPI) Based on Beowulf Linux system 基于Beowulf Linux系统的ClustalW-Message Passing Interface (MPI)对16S细菌核糖体rna的大量多序列比对

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.88

Hyon Chang Kim, Yong Beom Seo, Ji Hwan Song, D. Choi, C. Min, Han Jip Kim

引用次数: 1

Consensus methods using phylogenetic databases 使用系统发育数据库的共识方法

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.43

M. Kulkarni, Bernard M. E. Moret

{"title":"Consensus methods using phylogenetic databases","authors":"M. Kulkarni, Bernard M. E. Moret","doi":"10.1109/CSBW.2005.43","DOIUrl":"https://doi.org/10.1109/CSBW.2005.43","url":null,"abstract":"With the increasing use and size of phytogenies, the output of reconstruction programs must be stored for future reference, in which case post-tree analyses such as consensus must be run from a database. We set out to determine whether such analyses can be run at a reasonable cost; we chose consensus (which summarizes the information from many trees into a single tree) because of its general applicability and because it creates a severe demand on the database by requiring examination of every edge of every tree. We preprocess the data (trees) to create tables that support consensus computations, using our own extensions to the PhyloDB schema of Nakhleh et al. For each of the three consensus methods (strict, majority, and greedy), we compare the database computation with the memory-resident computation using the Phylip consensus programs. We use a large selection of datasets of varying sizes (up to 1,000 trees of up to 1,500 taxa each) and of varying degrees of commonality. The computations from the database are very practical: they often run faster, and never run more than 5 times slower, than the computations in main memory using Phylip. The additional storage costs are easily handled by any database system, while the preprocessing costs remain reasonable. Thus suitable preprocessing of phylogenetic data allows post-tree analyses to be run directly from the database at much the same cost as current memory-resident analyses.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124391869","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

Maximum sequence alignment fails to predict off-targeted gene regulation by RNAi 最大序列比对不能预测RNAi对脱靶基因的调控

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.90

A. Birmingham, E. Anderson, W. Marshall, A. Khvorova

引用次数: 0

Lossless compression of DNA microarray images DNA微阵列图像的无损压缩

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.85

Yong Zhang, Rahul Parthe, D. Adjeroh

引用次数: 26