Results 11  20
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20,989
Features of similarity.
 Psychological Review
, 1977
"... Similarity plays a fundamental role in theories of knowledge and behavior. It serves as an organizing principle by which individuals classify objects, form concepts, and make generalizations. Indeed, the concept of similarity is ubiquitous in psychological theory. It underlies the accounts of stimu ..."
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Cited by 1455 (2 self)
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. These models represent objects as points in some coordinate space such that the observed dissimilarities between objects correspond to the metric distances between the respective points. Practically all analyses of proximity data have been metric in nature, although some (e.g., hierarchical clustering) yield
Scalable molecular dynamics with NAMD.
 J Comput Chem
, 2005
"... Abstract: NAMD is a parallel molecular dynamics code designed for highperformance simulation of large biomolecular systems. NAMD scales to hundreds of processors on highend parallel platforms, as well as tens of processors on lowcost commodity clusters, and also runs on individual desktop and la ..."
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Cited by 849 (63 self)
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Abstract: NAMD is a parallel molecular dynamics code designed for highperformance simulation of large biomolecular systems. NAMD scales to hundreds of processors on highend parallel platforms, as well as tens of processors on lowcost commodity clusters, and also runs on individual desktop
CATH  a hierarchic classification of protein domain structures
 STRUCTURE
, 1997
"... Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structurebased classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can ..."
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Cited by 470 (33 self)
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Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structurebased classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function
Correlation functions, cluster functions, and spacing distributions for random matrices
 J. Statist. Phys
, 1998
"... The usual formulas for the correlation functions in orthogonal and symplectic matrix models express them as quaternion determinants. From this representation one can deduce formulas for spacing probabilities in terms of Fredholm determinants of matrixvalued kernels. The derivations of the various f ..."
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Cited by 133 (14 self)
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formulas are somewhat involved. In this article we present a direct approach which leads immediately to scalar kernels for the unitary ensembles and matrix kernels for the orthogonal and symplectic ensembles, and the representations of the correlation functions, cluster functions, and spacing distributions
Similarity estimation techniques from rounding algorithms
 In Proc. of 34th STOC
, 2002
"... A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, Prh∈F[h(x) = h(y)] = sim(x,y), where sim(x,y) ∈ [0, 1] is some similarity function defined on the collection of objects. Such a scheme leads ..."
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Cited by 449 (6 self)
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A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, Prh∈F[h(x) = h(y)] = sim(x,y), where sim(x,y) ∈ [0, 1] is some similarity function defined on the collection of objects. Such a scheme leads
Correlation Clustering
 MACHINE LEARNING
, 2002
"... We consider the following clustering problem: we have a complete graph on # vertices (items), where each edge ### ## is labeled either # or depending on whether # and # have been deemed to be similar or different. The goal is to produce a partition of the vertices (a clustering) that agrees as mu ..."
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Cited by 332 (4 self)
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clusters). This formulation is motivated from a document clustering problem in which one has a pairwise similarity function # learned from past data, and the goal is to partition the current set of documents in a way that correlates with # as much as possible; it can also be viewed as a kind of "
A framework for clustering evolving data streams. In:
 Proc of VLDB’03,
, 2003
"... Abstract The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream renders most traditional algorithms too inefficient. In recent years, a few onepass clustering algorithms have been developed for the data stream proble ..."
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Cited by 359 (36 self)
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algorithm requires much greater functionality in discovering and exploring clusters over different portions of the stream. The widely used practice of viewing data stream clustering algorithms as a class of onepass clustering algorithms is not very useful from an application point of view. For example, a
Clusters, functional regions and cluster policies
 JIBS and CESIS Electronic Working Paper Series (84
, 2007
"... (JIBS and CESIS) This paper gives an overview of research on economic clusters and clustering and is motivated by the growing intellectual and political interest for the subject. Functional regions have the features that agglomeration of economic activities i.e. clusters, benefit from. Functional re ..."
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Cited by 1 (0 self)
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(JIBS and CESIS) This paper gives an overview of research on economic clusters and clustering and is motivated by the growing intellectual and political interest for the subject. Functional regions have the features that agglomeration of economic activities i.e. clusters, benefit from. Functional
The use of gene clusters to infer functional coupling
 Proceedings of the National Academy of Sciences, USA
, 1999
"... Earlier, we presented evidence that it is possible to predict functional coupling between genes based on conservation of gene clusters between genomes. With the rapid increase in availability of prokaryotic sequence data, it has become possible to verify and apply the technique. In this paper, we ..."
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Cited by 298 (12 self)
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Earlier, we presented evidence that it is possible to predict functional coupling between genes based on conservation of gene clusters between genomes. With the rapid increase in availability of prokaryotic sequence data, it has become possible to verify and apply the technique. In this paper, we
Genetic Network Inference: From CoExpression Clustering To Reverse Engineering
, 2000
"... motivation: Advances in molecular biological, analytical and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using highthroughput gene expression assays, we are able to measure the output of the ge ..."
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Cited by 336 (0 self)
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of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of coexpression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various
Results 11  20
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20,989