Results 231 to 240 of about 1,846,894 (263)
Patterns of Preoperative Tumor Markers Can Predict Resectability and Prognosis of Peritoneal Metastases: A Clustering Analysis. [PDF]
Ann Surg OncolEnblad M, Cashin P, Ghanipour L, Graf W.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Veterinary Immunology and Immunopathology, 1996
Cluster analysis was performed on flow cytometry data generated from the reactivities of the 302 workshop monoclonal antibodies with 36 target cell preparations. The antibodies were assigned to 42 preliminary clusters that were subjected to further examination in subsequent stages of the workshop.
A. A. Afifi, V. Clark
openaire +3 more sources
Cluster analysis was performed on flow cytometry data generated from the reactivities of the 302 workshop monoclonal antibodies with 36 target cell preparations. The antibodies were assigned to 42 preliminary clusters that were subjected to further examination in subsequent stages of the workshop.
A. A. Afifi, V. Clark
openaire +3 more sources
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1980
Cluster analysis is concerned with the problem of partitioning a given set of entities into homogeneous and well-separated subsets called clusters. The concepts of homogeneity and of separation can be made precise when a measure of dissimilarity between the entities is given.
Delattre, Michel, Hansen, Pierre
openaire +2 more sources
Cluster analysis is concerned with the problem of partitioning a given set of entities into homogeneous and well-separated subsets called clusters. The concepts of homogeneity and of separation can be made precise when a measure of dissimilarity between the entities is given.
Delattre, Michel, Hansen, Pierre
openaire +2 more sources
Comprehensive cluster analysis with Transitivity Clustering
Nature Protocols, 2011Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a ...
Wittkop, T. +5 more
openaire +3 more sources
Multilevel Functional Clustering Analysis
Biometrics, 2012Summary In this article, we investigate clustering methods for multilevel functional data, which consist of repeated random functions observed for a large number of units (e.g., genes) at multiple subunits (e.g., bacteria types). To describe the within‐ and between variability induced by the hierarchical structure in the data, we take a multilevel ...
Serban, Nicoleta, Jiang, Huijing
openaire +2 more sources
2013
Systems biology refers to the quantitative analysis of the dynamic interactions among several components of a biological system and aims to understand the behavior of the system as a whole. Systems biology involves the development and application of systems theory concepts for the study of complex biological systems through iteration over mathematical ...
Christine Distefano, Diana Mindrila
+5 more sources
Systems biology refers to the quantitative analysis of the dynamic interactions among several components of a biological system and aims to understand the behavior of the system as a whole. Systems biology involves the development and application of systems theory concepts for the study of complex biological systems through iteration over mathematical ...
Christine Distefano, Diana Mindrila
+5 more sources
Clustering Consistency Analysis
Journal of the Academy of Marketing Science, 1982Cluster analysis is a frequently used technique in marketing as a method to develop partitions or classifications for market segmentation, product positioning, test market selection, etc. Because of the vast diversity in the assortment of clustering algorithms available, it is often times not obvious which algorithm or technique should be employed.
openaire +1 more source
Analytical Chemistry, 1999
This article describes how the concept of multiresolution is used with cluster analysis of spectral data. Multiresolution analysis progressively increases the resolution of a spectrum profile by adding levels of details contained in scales obtained from a discrete wavelet transform.
openaire +2 more sources
This article describes how the concept of multiresolution is used with cluster analysis of spectral data. Multiresolution analysis progressively increases the resolution of a spectrum profile by adding levels of details contained in scales obtained from a discrete wavelet transform.
openaire +2 more sources