Single-link Clustering http://soj.sysu.edu.cn/show_problem.php?pid=1000&cid=1750 题目说是单链聚类,其实就是最小生成树,输出第k-1大的边; 我用的是kruskal算法: 1#include <iostream>2#include <cstdio>3#include <cstring>4#include <cmath>5#include <algorithm>6#include <cstdlib>78usingnamespa...
The structural heterogeneity was determined by analyzing the 3D density maps reconstructed from the centroids of clusters in latent space generated by the simple Kmeans clustering algorithm45. The latent space of different methods was also visualized in 2D using UMAP21. The structural heterogeneity was...
Here we extend a previous method, significance of hierarchical clustering, to propose a model-based hypothesis testing approach that incorporates significance analysis into the clustering algorithm and permits statistical evaluation of clusters as distinct cell populations. We also adapt this approach to ...
The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perf
In particular, the number of cell types in a dataset could have an opposite effect on their estimation depending on which clustering algorithm was used, and methods such as SC3 and Seurat tend to significantly over-estimate the cell type numbers when applied to datasets under two settings (i)...
Clusters of cells are identified using the K-nearest neighbor (KNN) algorithm and the “FindClusters” function with a resolution of 0.2. Identification of candidate NAC marker genes and their cell expression activity In the discovery cohort (GSE25055) with bulk transcriptome data, the differentially...
A single-valued neutrosophic set is a generalized fuzzy set, and its clustering algorithm has attracted more and more attention. An equivalence matrix is a common tool in clustering algorithms. At present, there exist no results constructing a single-valued neutrosophic number equivalence matrix using...
As a solution, point cloud clustering was utilized for tree point cloud instance segmentation in this study. In this paper, we used the Meanshift algorithm to extract single-tree point clouds. Meanshift is a density-based clustering algorithm that assumes that data sets of different clusters ...
cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). ...
Lymphatic invasion (LI) is extremely aggressive and induces worse prognosis among patients with colorectal cancer (CRC). Thus, it is critical to characterize the cellular and molecular mechanisms underlying LI in order to establish novel and efficacious