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Cytometry Part A
Volumn 79 A, Issue 1, 2011, Pages 3-5
On extensions of k-means clustering for automated gating of flow cytometry data
Author keywords

[No Author keywords available]
Indexed keywords

AUTOMATION; BIOSTATISTICS; CLUSTER ANALYSIS; FLOW CYTOMETRY; HUMAN; METHODOLOGY; NOTE; STATISTICS;
EID: 78650467489     PISSN: 15524922     EISSN: 15524930     Source Type: Journal    
DOI: 10.1002/cyto.a.20988     Document Type: Note
Times cited : (10)
References (13)
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  • 2
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  • 3
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    • Feature significance for multivariate kernel density estimation
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  • 4
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    • Data clustering: 50 years beyond k-means
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  • 5
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    • Combining multiple clusterings using evidence accumulation
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  • 6
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  • 7
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    • Nonnegative matrix factorization: An analytical and interpretive tool in computational biology
    • Devarajan K. Nonnegative matrix factorization: An analytical and interpretive tool in computational biology. PLoS Comput Biol 2008; 4: e1000029.
    • (2008) PLoS Comput Biol , vol.4
    • Devarajan, K.1
  • 8
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee DD, Seung HS. Learning the parts of objects by non-negative matrix factorization. Nature 1999; 401: 788-791.
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  • 9
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  • 11
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    • Sparse Nonnegative Matrix Factorization for Clustering. CSE Technical Reports
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.