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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1959 1
1962 1
1965 1
1966 1
1968 1
1969 2
1970 1
1971 1
1972 6
1973 5
1974 8
1975 17
1976 12
1977 17
1978 15
1979 16
1980 11
1981 25
1982 25
1983 50
1984 49
1985 34
1986 51
1987 80
1988 110
1989 116
1990 118
1991 126
1992 135
1993 137
1994 162
1995 148
1996 213
1997 212
1998 203
1999 251
2000 318
2001 348
2002 347
2003 397
2004 515
2005 696
2006 712
2007 716
2008 775
2009 895
2010 938
2011 1058
2012 1074
2013 1092
2014 1327
2015 1491
2016 1515
2017 1668
2018 1881
2019 2033
2020 2413
2021 2915
2022 3162
2023 3227
2024 1360

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Page 1
Showing results for clusters k
Search for Clysters K instead (3 results)
Machine learning and statistical methods for clustering single-cell RNA-sequencing data.
Petegrosso R, Li Z, Kuang R. Petegrosso R, et al. Brief Bioinform. 2020 Jul 15;21(4):1209-1223. doi: 10.1093/bib/bbz063. Brief Bioinform. 2020. PMID: 31243426 Review.
The review focuses on how conventional clustering techniques such as hierarchical clustering, graph-based clustering, mixture models, $k$-means, ensemble learning, neural networks and density-based clustering are modified or customized to tackle …
The review focuses on how conventional clustering techniques such as hierarchical clustering, graph-based clustering, m …
The K = 2 conundrum.
Janes JK, Miller JM, Dupuis JR, Malenfant RM, Gorrell JC, Cullingham CI, Andrew RL. Janes JK, et al. Mol Ecol. 2017 Jul;26(14):3594-3602. doi: 10.1111/mec.14187. Epub 2017 Jun 14. Mol Ecol. 2017. PMID: 28544181 Review.
Assessments of population genetic structure have become an increasing focus as they can provide valuable insight into patterns of migration and gene flow. structure, the most highly cited of several clustering-based methods, was developed to provide robust estimates withou …
Assessments of population genetic structure have become an increasing focus as they can provide valuable insight into patterns of migration …
Subspace K-means clustering.
Timmerman ME, Ceulemans E, De Roover K, Van Leeuwen K. Timmerman ME, et al. Behav Res Methods. 2013 Dec;45(4):1011-23. doi: 10.3758/s13428-013-0329-y. Behav Res Methods. 2013. PMID: 23526258
To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich inter …
To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centro …
Clustering.
McLachlan GJ, Bean RW, Ng SK. McLachlan GJ, et al. Methods Mol Biol. 2017;1526:345-362. doi: 10.1007/978-1-4939-6613-4_19. Methods Mol Biol. 2017. PMID: 27896751
Clustering techniques are used to arrange genes in some natural way, that is, to organize genes into groups or clusters with similar behavior across relevant tissue samples (or cell lines). These techniques can also be applied to tissues rather than genes. Methods s …
Clustering techniques are used to arrange genes in some natural way, that is, to organize genes into groups or clusters with s …
Predicting multiple conformations via sequence clustering and AlphaFold2.
Wayment-Steele HK, Ojoawo A, Otten R, Apitz JM, Pitsawong W, Hömberger M, Ovchinnikov S, Colwell L, Kern D. Wayment-Steele HK, et al. Nature. 2024 Jan;625(7996):832-839. doi: 10.1038/s41586-023-06832-9. Epub 2023 Nov 13. Nature. 2024. PMID: 37956700 Free PMC article.
Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB(5) and found that predictions of both conformations were distributed in clusters across the KaiB family. ...To test AF-Clus …
Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protei …
The k partition-distance problem.
Chen YH. Chen YH. J Comput Biol. 2012 Apr;19(4):404-17. doi: 10.1089/cmb.2010.0186. J Comput Biol. 2012. PMID: 22468708
A partition divides all elements in N into two or more disjoint clusters that cover all elements, where a cluster contains a non-empty subset of N. ...|N|) time, where rho is the maximum number of clusters of these k partitions and |N| is the number of …
A partition divides all elements in N into two or more disjoint clusters that cover all elements, where a cluster contains a n …
Investigation of the Stability Mechanisms of Eight-Atom Binary Metal Clusters Using DFT Calculations and k-means Clustering Algorithm.
Orlando Morais F, Andriani KF, Da Silva JLF. Orlando Morais F, et al. J Chem Inf Model. 2021 Jul 26;61(7):3411-3420. doi: 10.1021/acs.jcim.1c00253. Epub 2021 Jun 23. J Chem Inf Model. 2021. PMID: 34161078
Here, we report density functional theory calculations combined with the k-means clustering algorithm and the Spearman rank correlation analysis to investigate the stability mechanisms of eight-atom binary metal AB clusters, where A and B are Fe, Co, N …
Here, we report density functional theory calculations combined with the k-means clustering algorithm and the Spearman rank co …
The utility of clusters and a Hungarian clustering algorithm.
Kume A, Walker SG. Kume A, et al. PLoS One. 2021 Aug 4;16(8):e0255174. doi: 10.1371/journal.pone.0255174. eCollection 2021. PLoS One. 2021. PMID: 34347837 Free PMC article.
Implicit in the k-means algorithm is a way to assign a value, or utility, to a cluster of points. ...The aim in this paper is to introduce an alternative way to assign a value to a cluster. Motivation is provided. Moreover, whereas the k-means algorith …
Implicit in the k-means algorithm is a way to assign a value, or utility, to a cluster of points. ...The aim in this paper is …
Using K-Means Clustering to Identify Physician Clusters by Electronic Health Record Burden and Efficiency.
Sim J, Mani K, Fazzari M, Lin J, Keller M, Kitsis E, Raheem A, Jariwala SP. Sim J, et al. Telemed J E Health. 2024 Feb;30(2):585-594. doi: 10.1089/tmj.2023.0167. Epub 2023 Aug 21. Telemed J E Health. 2024. PMID: 37603292
This study aims to use data from Signal, a tool provided by the Epic EHR, to analyze physician metadata in the Montefiore Health System via cluster analysis to assess EHR burden and efficiency. Methods: Data were obtained for a one-month period (July 2020) represent …
This study aims to use data from Signal, a tool provided by the Epic EHR, to analyze physician metadata in the Montefiore Health System via …
On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling.
Vera JF, Macías R. Vera JF, et al. Psychometrika. 2021 Jun;86(2):489-513. doi: 10.1007/s11336-021-09757-2. Epub 2021 May 19. Psychometrika. 2021. PMID: 34008128
In this situation, traditional algorithms cannot be used, and so K-means clustering procedures are being performed directly on the basis of the observed dissimilarity matrix. ...The linear invariance property in K-means clustering for squared dissimila …
In this situation, traditional algorithms cannot be used, and so K-means clustering procedures are being performed directly on …
31,880 results
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