Analysis of flow cytometry data by matrix relevance learning vector quantization
about
Studying the human immunome: the complexity of comprehensive leukocyte immunophenotyping.Leukemia prediction using sparse logistic regression.Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples.Prototype-based models in machine learning.Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.
P2860
Analysis of flow cytometry data by matrix relevance learning vector quantization
description
2013 nî lūn-bûn
@nan
2013 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի մարտին հրատարակված գիտական հոդված
@hy
2013年の論文
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2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Analysis of flow cytometry data by matrix relevance learning vector quantization
@ast
Analysis of flow cytometry data by matrix relevance learning vector quantization
@en
type
label
Analysis of flow cytometry data by matrix relevance learning vector quantization
@ast
Analysis of flow cytometry data by matrix relevance learning vector quantization
@en
prefLabel
Analysis of flow cytometry data by matrix relevance learning vector quantization
@ast
Analysis of flow cytometry data by matrix relevance learning vector quantization
@en
P2860
P1433
P1476
Analysis of flow cytometry data by matrix relevance learning vector quantization
@en
P2093
Petra Schneider
P2860
P304
P356
10.1371/JOURNAL.PONE.0059401
P407
P577
2013-03-18T00:00:00Z