Cluster analysis for autocorrelated and cyclic chemical process dataBEAVER, Scott; PALAZOGLU, Ahmet; ROMAGNOLI, José A et al.Industrial & engineering chemistry research. 2007, Vol 46, Num 11, pp 3610-3622, issn 0888-5885, 13 p.Article

iBBiG: iterative binary bi-clustering of gene setsGUSENLEITNER, Daniel; HOWE, Eleanor A; BENTINK, Stefan et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 19, pp 2484-2492, issn 1367-4803, 9 p.Article

Comparing clustering and pre-processing in taxonomy analysisBONDER, Marc J; ABELN, Sanne; ZAURA, Egija et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 22, pp 2891-2897, issn 1367-4803, 7 p.Article

Bayesian correlated clustering to integrate multiple datasetsKIRK, Paul; GRIFIFIN, Jim E; SAVAGE, Richard S et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 24, pp 3290-3297, issn 1367-4803, 8 p.Article

Detecting genome-wide epistases based on the clustering of relatively frequent itemsMINZHU XIE; JING LI; TAO JIANG et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 1, pp 5-12, issn 1367-4803, 8 p.Article

A Hybrid Approach for Normal Factorization of PolynomialsKARCANIAS, Nicos; MITROULI, Marilena; TRIANTAFYLLOU, Dimitrios et al.Lecture notes in computer science. 2006, pp 399-406, issn 0302-9743, isbn 3-540-34379-2, 8 p.Conference Paper

A novel clustering-neural tree for pattern classificationZHAO, Zhong-Qiu; HUANG, De-Shuang; LIN GUO et al.International Joint Conference on Neural Networks. 2004, isbn 0-7803-8359-1, 4Vol, Vol2, 1303-1308Conference Paper

A new cluster concept and its application to quasi-crystals of the i-AlMnSi family and closely related crystalline structuresKREINER, G; FRANZEN, H. F.Journal of alloys and compounds. 1995, Vol 221, Num 1-2, pp 15-36, issn 0925-8388Article

Second-order analysis of spatial clustering for inhomogeneous populationsDIGGLE, P. J; CHETWYND, A. G.Biometrics. 1991, Vol 47, Num 3, pp 1155-1163, issn 0006-341XArticle

Accelerated similarity searching and clustering of large compound sets by geometric embedding and locality sensitive hashingYIQUN CAO; TAO JIANG; GIRKE, Thomas et al.Bioinformatics (Oxford. Print). 2010, Vol 26, Num 7, pp 953-959, issn 1367-4803, 7 p.Article

Choosing the initial set of exemplars when learning with an NGE-based systemBAGGIO FIGUEIRA, Lucas; DO CARMO NICOLETTI, Maria.International conference on information technology. 2004, pp vol2.193-vol2.197, isbn 0-7695-2108-8, 2VolConference Paper

Non-uniqueness and inversions in cluster analysisMORGAN, B. J. T; RAY, A. P. G.Applied statistics. 1995, Vol 44, Num 1, pp 117-134, issn 0035-9254Article

Hierarchical Cluster Analysis of Matrix Effects on 110 Pesticide Residues in 28 Tea MatrixesYAN LI; PANG, Guo-Fang; FAN, Chun-Lin et al.Journal of AOAC International. 2013, Vol 96, Num 6, pp 1453-1465, issn 1060-3271, 13 p.Article

CD-HIT: accelerated for clustering the next-generation sequencing dataLIMIN FU; BEIFANG NIU; ZHENGWEI ZHU et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 23, pp 3150-3152, issn 1367-4803, 3 p.Article

Robust perron cluster analysis for various applications in computational life scienceWEBER, Marcus; KUBE, Susanna.Lecture notes in computer science. 2005, pp 57-66, issn 0302-9743, isbn 3-540-29104-0, 1Vol, 10 p.Conference Paper

Supervised cluster analysis for microarray data based on multivariate Gaussian mixtureYI QU; SHIZHONG XU.Bioinformatics (Oxford. Print). 2004, Vol 20, Num 12, pp 1905-1913, issn 1367-4803, 9 p.Article

An effectiveness measure for software clustering algorithmsZHIHUA WEN; TZERPOS, Vassilios.International Workshop on Program Comprehension. 2004, pp 194-203, isbn 0-7695-2149-5, 1Vol, 10 p.Conference Paper

Using diversity in cluster ensemblesKUNCHEVA, Ludmila I; HADJITODOROV, Stefan T.International Conference on Systems, Man and Cybernetics. 2004, isbn 0-7803-8566-7, vol2, 1214-1219Conference Paper

An overview of clustering algorithmsTRESHANSKY, Allyn; MCGRAW, Robert.SPIE proceedings series. 2001, pp 41-51, isbn 0-8194-4062-0Conference Paper

Wide context acoustic modeling in read vs. spontaneous speechFINKE, M; ROGINA, I.International conference on acoustics, speech, and signal processing. 1997, pp 1743-1746, isbn 0-8186-7919-0Conference Paper

A simple and fast method to determine the parameters for fuzzy c―means cluster analysisSCHWÄMMLE, Veit; NØRREGAARD JENSEN, Ole.Bioinformatics (Oxford. Print). 2010, Vol 26, Num 22, pp 2841-2848, issn 1367-4803, 8 p.Article

Approximation schemes for metric clustering problemsKENYON, Claire.Lecture notes in computer science. 2004, pp 1-3, issn 0302-9743, isbn 3-540-21236-1, 3 p.Conference Paper

Multifunctional proteins revealed by overlapping clustering in protein interaction networkBECKER, Emmanuelle; ROBISSON, Benoît; CHAPPLE, Charles E et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 1, pp 84-90, issn 1367-4803, 7 p.Article

flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak findingYONGCHAO GE; SEALFON, Stuart C.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 15, pp 2052-2058, issn 1367-4803, 7 p.Article

MetaABC—an integrated metagenomics platform for data adjustment, binning and clusteringSU, Chien-Hao; HSU, Ming-Tsung; WANG, Tse-Yi et al.Bioinformatics (Oxford. Print). 2011, Vol 27, Num 16, pp 2298-2299, issn 1367-4803, 2 p.Article