Results 101 to 110 of about 1,986,530 (277)
KoG, 2016 In this paper, k-means algorithm is presented. It is a heuristic algorithm for solving NP-hard optimisation problem of classifying a given data into clusters, with a number of clusters fixed apriori. The algorithm is simple and it's convergence is fast, what makes it widely used, despite its tendency of stoping in a local minimum and inability of ...
openaire +1 more source
Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity
Molecular Oncology, EarlyView.Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung +17 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris +10 more
wiley +1 more source
Pattern classification using principal components regression [PDF]
In this paper we will classify patterns using an algorithm analogous to the k-means algorithm and the principal components regression (PCR). We will also present a financial application in which we apply PCR if the points represent the interests for ...
Ciuiu, Daniel
core +1 more source
Tumor mutational burden as a determinant of metastatic dissemination patterns
Molecular Oncology, EarlyView.This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Finding Optimal Number of Clusters Using Heuristic Clustering Algorithms
Ibn Al-Haitham Journal for Pure and Applied SciencesThe problem of estimating the number of clusters k is considered one of the major challenges for partition clustering. The k-means algorithm is a division-based clustering method where only objects are entered into a set of K, and the algorithm ...
Hanin Haqi, Tareef Kamil Mustafa
doaj +1 more source
FINGER KNUCKLE PRINT RECOGNITION WITH SIFT AND K-MEANS ALGORITHM [PDF]
ICTACT Journal on Image and Video Processing, 2013 In general, the identification and verification are done by passwords, pin number, etc., which is easily cracked by others. Biometrics is a powerful and unique tool based on the anatomical and behavioral characteristics of the human beings in order to ...
A. Muthukumar, S. Kannan
doaj
A Feature-Reduction Multi-View k-Means Clustering Algorithm
IEEE Access, 2019 The k-means clustering algorithm is the oldest and most known method in cluster analysis. It has been widely studied with various extensions and applied in a variety of substantive areas.
Miin-Shen Yang, Kristina P. Sinaga
doaj +1 more source
Pattern classification using polynomial and linear regression [PDF]
In this paper we will classify patterns using an algorithm analogous to the k-means algorithm and the regression polynomial of the degree k (for instance, if k=1 we obtain the regression line, and if k=2 we obtain the regression parable), and the ...
Ciuiu, Daniel
core +1 more source