Computational systems bioinformatics. Computational Systems Bioinformatics Conference最新文献_第8页

Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination. 基于位点定向蛋白质重组的蛋白质工程中断点位置选择优化算法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Wei Zheng, Xiaoduan Ye, Alan M Friedman, Chris Bailey-Kellogg

{"title":"Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination.","authors":"Wei Zheng, Xiaoduan Ye, Alan M Friedman, Chris Bailey-Kellogg","doi":"","DOIUrl":"","url":null,"abstract":"Protein engineering by site-directed recombination seeks to develop proteins with new or improved function, by accumulating multiple mutations from a set of homologous parent proteins. A library of hybrid proteins is created by recombining the parent proteins at specified breakpoint locations; subsequent screening/selection identifies hybrids with desirable functional characteristics. In order to improve the frequency of generating novel hybrids, this paper develops the first approach to explicitly plan for diversity in site-directed recombination, including metrics for characterizing the diversity of a planned hybrid library and efficient algorithms for optimizing experiments accordingly. The goal is to choose breakpoint locations to sample sequence space as uniformly as possible (which we argue maximizes diversity), under the constraints imposed by the recombination process and the given set of parents. A dynamic programming approach selects optimal breakpoint locations in polynomial time. Application of our method to optimizing breakpoints for an example biosynthetic enzyme, purE, demonstrates the significance of diversity optimization and the effectiveness of our algorithms.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":" ","pages":"31-40"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27061851","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

Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination. 基于位点定向蛋白质重组的蛋白质工程中断点位置选择优化算法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0008

Wei Zheng, Xiaoduan Ye, A. Friedman, C. Bailey-Kellogg

{"title":"Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination.","authors":"Wei Zheng, Xiaoduan Ye, A. Friedman, C. Bailey-Kellogg","doi":"10.1142/9781860948732_0008","DOIUrl":"https://doi.org/10.1142/9781860948732_0008","url":null,"abstract":"Protein engineering by site-directed recombination seeks to develop proteins with new or improved function, by accumulating multiple mutations from a set of homologous parent proteins. A library of hybrid proteins is created by recombining the parent proteins at specified breakpoint locations; subsequent screening/selection identifies hybrids with desirable functional characteristics. In order to improve the frequency of generating novel hybrids, this paper develops the first approach to explicitly plan for diversity in site-directed recombination, including metrics for characterizing the diversity of a planned hybrid library and efficient algorithms for optimizing experiments accordingly. The goal is to choose breakpoint locations to sample sequence space as uniformly as possible (which we argue maximizes diversity), under the constraints imposed by the recombination process and the given set of parents. A dynamic programming approach selects optimal breakpoint locations in polynomial time. Application of our method to optimizing breakpoints for an example biosynthetic enzyme, purE, demonstrates the significance of diversity optimization and the effectiveness of our algorithms.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"31-40"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007062","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

Supercomputing with toys: harnessing the power of NVIDIA 8800GTX and playstation 3 for bioinformatics problem. 超级计算与玩具:利用NVIDIA 8800GTX和playstation 3的力量来解决生物信息学问题。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0039

Justin Wilson, Manhong Dai, Elvis Jakupovic, S. Watson, F. Meng

引用次数: 13

Cancer molecular pattern discovery by subspace consensus kernel classification. 子空间共识核分类发现癌症分子模式。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Xiaoxu Han

{"title":"Cancer molecular pattern discovery by subspace consensus kernel classification.","authors":"Xiaoxu Han","doi":"","DOIUrl":"","url":null,"abstract":"Cancer molecular pattern efficient discovery is essential in the molecular diagnostics. The characteristics of the gene/protein expression data are challenging traditional unsupervised classification algorithms. In this work, we describe a subspace consensus kernel clustering algorithm based on the projected gradient nonnegative matrix factorization (PG-NMF). The algorithm is a consensus kernel hierarchical clustering (CKHC) method in the subspace generated by the PG-NMF. It integrates convergence-soundness parts-based learning, subspace and kernel space clustering in the microarray and proteomics data classification. We first integrated subspace methods and kernel methods by following our framework of the input space, subspace and kernel space clustering. We demonstrate more effective classification results from our algorithm by comparison with those of the classic NMF, sparse-NMF classifications and supervised classifications (KNN and SVM) for the four benchmark cancer datasets. Our algorithm can generate a family of classification algorithms in machine learning by selecting different transforms to generate subspaces and different kernel clustering algorithms to cluster data.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":" ","pages":"55-65"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27060666","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

Transcriptional profiling of definitive endoderm derived from human embryonic stem cells. 人胚胎干细胞最终内胚层的转录谱分析。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Huiqing Liu, Stephen Dalton, Ying Xu

引用次数: 0

Enhanced partial order curve comparison over multiple protein folding trajectories. 在多个蛋白质折叠轨迹上增强的偏序曲线比较。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Hong Sun, Hakan Ferhatosmanoglu, Motonori Ota, Yusu Wang

引用次数: 0

Improvement in protein sequence-structure alignment using insertion/deletion frequency arrays. 利用插入/删除频率阵列改进蛋白质序列结构比对。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Kyle Ellrott, Jun-tao Guo, Victor Olman, Ying Xu

引用次数: 0

Supercomputing with toys: harnessing the power of NVIDIA 8800GTX and playstation 3 for bioinformatics problem. 超级计算与玩具:利用NVIDIA 8800GTX和playstation 3的力量来解决生物信息学问题。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Justin Wilson, Manhong Dai, Elvis Jakupovic, Stanley Watson, Fan Meng

引用次数: 0

Deconvoluting the BAC-gene relationships using a physical map. 使用物理图谱解卷积bac -基因关系。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0023

Yonghui Wu, Lan Liu, T. Close, S. Lonardi

{"title":"Deconvoluting the BAC-gene relationships using a physical map.","authors":"Yonghui Wu, Lan Liu, T. Close, S. Lonardi","doi":"10.1142/9781860948732_0023","DOIUrl":"https://doi.org/10.1142/9781860948732_0023","url":null,"abstract":"MOTIVATION The deconvolution of the relationships between BAC clones and genes is a crucial step in the selective sequencing of the regions of interest in a genome. It usually requires combinatorial pooling of unique probes obtained from the genes (unigenes), and the screening of the BAC library using the pools in a hybridization experiment. Since several probes can hybridize to the same BAC, in order for the deconvolution to be achievable the pooling design has to be able to handle a large number of positives. As a consequence, smaller pools need to be designed which in turn increases the number of hybridization experiments possibly making the entire protocol unfeasible. RESULTS We propose a new algorithm that is capable of producing high accuracy deconvolution even in the presence of a weak pooling design, i.e., when pools are rather large. The algorithm compensates for the decrease of information in the hybridization data by taking advantage of a physical map of the BAC clones. We show that the right combination of combinatorial pooling and our algorithm not only dramatically reduces the number of pools required, but also successfully deconvolutes the BAC-gene relationships with almost perfect accuracy.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"203-14"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007363","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

Using indirect protein-protein interactions for protein complex predication. 利用间接蛋白质-蛋白质相互作用预测蛋白质复合物。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0014

H. Chua, K. Ning, W. Sung, H. Leong, L. Wong

{"title":"Using indirect protein-protein interactions for protein complex predication.","authors":"H. Chua, K. Ning, W. Sung, H. Leong, L. Wong","doi":"10.1142/9781860948732_0014","DOIUrl":"https://doi.org/10.1142/9781860948732_0014","url":null,"abstract":"Protein complexes are fundamental for understanding principles of cellular organizations. Accurate and fast protein complex prediction from the PPI networks of increasing sizes can serve as a guide for biological experiments to discover novel protein complexes. However, protein complex prediction from PPI networks is a hard problem, especially in situations where the PPI network is noisy. We know from previous work that proteins that do not interact, but share interaction partners (level-2 neighbors) often share biological functions. The strength of functional association can be estimated using a topological weight, FS-Weight. Here we study the use of indirect interactions between level-2 neighbors (level-2 interactions) for protein complex prediction. All direct and indirect interactions are first weighted using topological weight (FS-Weight). Interactions with low weight are removed from the network, while level-2 interactions with high weight are introduced into the interaction network. Existing clustering algorithms can then be applied on this modified network. We also propose a novel algorithm that searches for cliques in the modified network, and merge cliques to form clusters using a \"partial clique merging\" method. In this paper, we show that 1) the use of indirect interactions and topological weight to augment protein-protein interactions can be used to improve the precision of clusters predicted by various existing clustering algorithms; 2) our complex finding algorithm performs very well on interaction networks modified in this way. Since no any other information except the original PPI network is used, our approach would be very useful for protein complex prediction, especially for prediction of novel protein complexes.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"97-109"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1142/9781860948732_0014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007409","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: 35