crops; singular value decomposition; bio-energy; crops; data matrix; feed; food; geographical locations; group soybean sample; multiple-view data; multiview co-clustering method; multiview singular value decomposition approach; soybean biodiversity conservation; soybean clusters; soybean domestication; soybean phenotypes; soybean phenotypic variation; soybean population structure; soybean varieties; sparse integrative cluster analysis; sparse singular vectors; Clustering algorithms; Matrix decomposition; Optimization; Sociology; Sparse matrices; Statistics; Vectors; multi-view clustering; multi-view data analysis; soybean population structure; soybean trait analysis;
机译:整合微阵列分析和大豆基因组以了解大豆铁缺乏反应
机译:综合表型框架(IPF):多个OMIC数据的综合聚类识别新型肺病椎体型
机译:不同结瘤表型的田间大豆的微生物群落分析
机译:整合统计和子空间聚类模型以分析自闭症谱系障碍表型
机译:大豆run藜6号染色体的序列分析与Rpg1抗性簇的进化
机译:整合微阵列分析和大豆基因组以了解大豆铁缺乏反应
机译:整合表型框架(iPF):多个组学数据的整合聚类确定了新的肺部疾病亚型