We have established and validated a quantitative assay that will be of use in assessing the presence and degree of smoke associated molecular damage in lung cancers arising in ever and never smokers.
This paper presents a further investigation into computational properties of a novel fuzzy additive spectral clustering method, Fuzzy Additive Spectral clustering (FADDIS), recently introduced by authors. Specifically, we extend our analysis to ‘difficult’ data structures from the recent literature and develop two synthetic data generators simulating affinity data of Gaussian clusters and genuine additive similarity data, with a controlled level of noise. The FADDIS is experimentally verified on these data in comparison with two state‐of‐the‐art fuzzy clustering methods. The claimed ability of FADDIS to help in determining the right number of clusters is experimentally tested, and the role of the pseudo‐inverse Laplacian data transformation in this is highlighted. A potentially useful extension of the method to biclustering is introduced.
A novel method for visualization of a fuzzy or crisp topic set is developed. The method maps the set's topics to higher ranks of the taxonomy tree of the field. The method involves a penalty function summing penalties for the chosen "head subjects" together with penalties for emerging "gaps" and "offshoots". The method finds a mapping minimizing the penalty function in recursive steps involving two different scenarios, that of 'gaining a head subject' and that of 'not gaining a head subject'. We illustrate the method by applying it to illustrative and real-world data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.