K-Means ClusteringHierarchical ClusteringExpectation and Maximization AlgorithmGrid Based CalculationClustering or group examination can be considered as a key unit in information investigation, whose primary point is to isolate the information, informational iGoyal, YogitaGoyal, YojanaSharma, AnandSocial Science Electronic Publishing
A novel joint clustering and classification (JCC) method which could discover hidden clusters features in the patient samples was developed to predict diabetes, and the method performed best among the methods that were applicable to the interpretation of prediction22. A study used neural network, ...
utilize external well-annotated source data start to gain popularity over unsupervised clustering algorithms; however, the performance of existing supervised methods is highly dependent on source data quality and they often have limited accuracy to classify cell types that are missing in the source data...
In this work we focus attention on the single-label setting and we call the considered learning task multi-type clustering and classification from heterogeneous networks. This task is not completely new in the literature and has connections with the task of multiple predicate learning [36] in ILP...
Spectral clustering for multi-type relational data. In: Cohen WW, Moore A, eds. Proc. of the 23rd Int'l Conf. on Machine Learning. New York: ACM Press, 2006. 585-592.Long, B., Zhang, Z.M., Wu´;, X., Yu, P.S.: Spectral clustering for multi-type rela- tional data. In:...
Statistical basis of non-linear Hebbian learning and application to clustering Neural Networks (1995) F. Theis Uniqueness of complex and multidimensional independent component analysis Signal Process. (2004) S.-i. Amari Natural gradient works efficiently in learning Neural Comput. (1998)View more refe...
Aevermann BD, Zhang Y, Novotny M, Keshk M, Bakken TE, Miller JA, Hodge RD, Lelieveldt B, Lein ES, Scheuermann RH. A machine learning method for the discovery of minimum marker gene combinations for cell-type identification from single-cell RNA sequencing. Genome Res. 2021 Jun 4:gr.2755...
Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis - jianhuupenn/ItClust
(FPKM + 1)) of male and female normoxic controls. Genes are ordered by hierarchical clustering of the log2FC values. In the log2FC columns (red-blue), M indicates hypoxia vs. control in males, F indicates hypoxia vs. control in females, and N indicates male vs. female in ...
Cell type deconvolution is a computational method for the determination/resolution of cell type proportions from bulk sequencing data, and is frequently used for the analysis of divergent cell types in tumour tissue samples. However, deconvolution techno