Sharan R. and Shamir R. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Biology, To appear. Home/Search Document Details and Download
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Graph-Modeled Data Clustering: Fixed-Parameter.. - Gramm, Guo.. (2003) (3 citations) (Correct)
....tractability, exact algorithms. 1 Introduction Motivation and problem definition. There is a huge variety of clustering algorithms with applications in numerous fields (cf. e.g. 8, 9] Here, we focus on problems closely related to algorithms for clustering gene expression data (cf. [19] for a very recent survey) More precisely, Shamir et al. 17] recently studied two NP complete problems called Cluster Editing and Cluster Deletion . These are based on the notion of a similarity graph whose vertices correspond to elements and in which there is an edge between two vertices i# ....
R. Sharan and R. Shamir. Algorithmic approaches to clustering gene expression data. In T. Jiang et al. (eds): Current Topics in Computational Molecular Biology , pages 269--300, The MIT Press. 2002.
DNA microarray data and contextual analysis of correlation.. - Rougemont, Hingamp (2003) (1 citation) (Correct)
....of gene expression levels by microarray experiments create a high throughput of data, the interpretation of which increasingly requires novel and efficient dimensionality reduction strategies. Many clustering methods have been proposed (see for example [1 5] and the more comprehensive reviews [6,7]) and are widely used. These algorithms group genes and or samples into clusters of similar expression profiles, in order to suggest possible functional relationships between them. The importance of graphical representations and of automatic cluster annotations stands out from many recent ....
Shamir R and Sharan R Algorithmic approaches to clustering gene expression data In Current Topics In Computational Molecular Biology (Edited by: Jiang T, Xu Y, Smith T) 2002, 269-300
Approximation Schemes for Clustering Problems (Extended .. - Vega, Karpinski.. (2003) (Correct)
....motivation. The problem of partitioning a data set into a small number of clusters of related items has a crucial role in many information retrieval and data analysis applications, such as web search and classification [8, 12, 30, 16] or interpretation of experimental data in molecular biology [29]. We consider a set V of n points endowed with a distance function ffi. These points have to be partitioned into a fixed number k of subsets C1 ; C2 ; Ck so as to minimize the cost of the partition, which is defined to be the sum over all clusters of the sum of pairwise distances in a ....
R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, M.Q. Zhang eds., Current Topics in Computational Biology, MIT Press, to appear.
Support Vector Clustering - Biowulf, Horn, Siegelmann, Vapnik (2001) (16 citations) (Correct)
....[1, 2, 3] Clustering may proceed according to some parametric model, as in the k means algorithm for example [4] or by hierarchically grouping points according to some distance or similarity measure as in hierarchical clustering algorithms. Other approaches include graph theoretic methods [5], physically motivated algorithms [6] and algorithms based on density estimation [7] 2] In this paper we propose a non parametric clustering algorithm based on the support vector 1 approach [8] In [9, 10] a support vector algorithm was used to characterize the support of a high dimensional ....
R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, and M.Q. Zhang, editors, Current Topics in Computational Biology. MIT Press, submitted.
Optimal Arrangement of Leaves in the Tree.. - Biedl, Brejova.. (2001) (4 citations) (Correct)
....expression profiles should be located in the same subtree. Variations of hierarchical agglomerative clustering algorithm are most commonly used for hierarchical clustering, such as average linkage clustering [24] Other options include neural networks [7] For surveys on clustering, see e.g. [3, 11, 22]. Second, the list of genes is reordered in a way consistent with the tree, i.e. so that each subtree of the tree corresponds to a contiguous sequence of genes in the list. Thus genes with similar expression profiles will be located close to each other in the list. Third, the resulting ordered ....
R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, and M. Q. Zhang, editors, Current Topics in Computational Biology. MIT press, 2001. To appear.
Continuous Representations of Time Series Gene Expression - Data Ziv Bar-Joseph (Correct)
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Sharan R. and Shamir R. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Biology, To appear.
Clustering Short Time Series Gene Expression Data - Ernst, Nau, Bar-Joseph (2005) (Correct)
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Sharan R. and Shamir R. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Biology, To appear.
A Patient-Gene Model for Temporal Expression Profiles in.. - Kaminski, Bar-Joseph (Correct)
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Sharan R, Shamir R.: Algorithmic Approaches to Clustering Gene Expression Data. Current Topics in Computational Biology. (2002) 269--300
Fixed-Parameter Tractable Generalizations of - Cluster Editing Peter (Correct)
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R. Sharan, R. Shamir. Algorithmic approaches to clustering gene expression data, in: Current Topics in Computational Molecular Biology, MIT Press, 2002, 269-300
Approximation Schemes for Clustering Problems in.. - Vega, Karpinski.. (2002) (Correct)
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R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, M.Q. Zhang eds., Current Topics in Computational Biology, MIT Press, to appear.
Continuous Representations of Time Series Gene.. - Bar-Joseph, Gerber.. (Correct)
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Sharan R. and Shamir R. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Biology, To appear.
Graph Modification Problems and Automated Search Tree Generation - Hüffner (2003) (Correct)
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Ron Shamir and Roded Sharan. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Molecular Biology, pages 269--300, 2002. 18
Clustering of Time-Course Gene Expression Data - Ya Zhang Hongyuan (2004) (1 citation) (Correct)
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Sharan,R. and Shamir,R. 2002. Algorithmic approaches to clustering gene expression data. In T. Jiang et al. (eds), Current Topics in Computational Molecular Biology. The MIT Press, pp. 269-300.
A Scale Dependent Model for Clustering by Optimization of - Homogeneity And Separation (Correct)
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Shamir, R. and Sharan, R. 2002. Algorithmic approaches to clustering gene expression data. MIT Press: Current Topics in Computational Biology, pp.269--299.
Polynomial Time Approximation Schemes for Metric.. - Vega, Karpinski.. (2002) (2 citations) (Correct)
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R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, M.Q. Zhang eds., Current Topics in Computational Biology, MIT Press, to appear.
Graph-Modeled Data Clustering: Fixed-Parameter.. - Gramm, Guo.. (2003) (3 citations) (Correct)
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R. Sharan and R. Shamir. Algorithmic approaches to clustering gene expression data. In T. Jiang et al. (eds): Current Topics in Computational Molecular Biology , pages 269--300. The MIT Press, 2002. 27
Polynomial Time Approximation Schemes for Metric.. - Vega, Karpinski.. (2002) (2 citations) (Correct)
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R. Shamir and R. Sharan. Algorithmic approaches to clustering gene expression data. In T. Jiang, T. Smith, Y. Xu, M.Q. Zhang eds., Current Topics in Computational Biology, MIT Press, to appear.
Graph Modification Problems and Automated Search Tree Generation - Hüffner (Correct)
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Ron Shamir and Roded Sharan. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Molecular Biology, pages 269--300, 2002. 18
A New Approach to Analyzing Gene Expression Time Series .. - Bar-Joseph, Gerber.. (Correct)
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Sharan R. and Shamir R. Algorithmic approaches to clustering gene expression data. Current Topics in Computational Biology, To appear.
Detecting Stable Clusters Using Principal Component Analysis - Ben-Hur, Guyon (Correct)
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Shamir, R. and Sharan, R. (2001) Algorithmic approaches to clustering gene expression data. in Jiang, T., Smith, T., Xu, Y. and Zhang, M., eds., Current Topics in Computational Biology, MIT Press.
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