Effect of data normalization on fuzzy clustering of DNA microarray data

BACKGROUND: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. RESULTS: In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. CONCLUSION: Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods when samples have varying expression patterns or are noisy. In particular, the FCM method slightly outperformed the hard clustering methods when the expression patterns of genes overlapped and was advantageous in finding co-regulated genes. Thus, the FCM approach offers a convenient method for finding subsets of genes that are strongly associated to a given cluster

Analysis of import changes through shift-share, location quotient and BCG techniques: Gwangyang Port in Asia

The main aim of this article is to analyze the import changes of Gwangyang Port using shift-share, location quotient and BCG matrix techniques. We perform the standard shift-share analysis and spatial shift-share analysis for the period 2010–2018 and investigate the import performance of Gwangyang Port for coal, iron ore, natural gas and vegetable matter. The static analysis shows that the regional shift effect, which is the most important component, is negative for coal and iron ore, but positive for natural gas and vegetable matter. The spatial shift-share analysis also indicates that Gwangyang Port experiences not only the gains in regional competitiveness but the industrial advantage for iron ore, natural gas and vegetable matter owing to its higher competitiveness. Incorporating location coefficients into BCG matrix for coal imports, we also show that Gwangyang Port succeeds upgrading its position for natural gas and vegetable matter, but fails escaping from transformation category or upgrading its position for coal and iron ore

Clinical Characteristics of Monomorphic Post-transplant Lymphoproliferative Disorders

Post-transplant lymphoproliferative disorders (PTLD) are a heterogeneous group of lymphoproliferative disorders associated with immunosuppression and Epstein-Barr virus infection. PTLD is classified into three major categories: early lesions, polymorphic PTLD, and monomorphic PTLD. The majority of monomorphic PTLD cases are non-Hodgkin's lymphoma of B-cell origin. This retrospective study was conducted to investigate the incidence, clinical manifestation, treatment, and outcomes of monomorphic PTLD among 5,817 recipients of solid organ or allogeneic hematopoietic stem cell transplantation from five institutions. Fourteen patients with monomorphic PTLD were identified (male:female 11:3; median age 42.6 yr, range 24-60). The overall incidence rate was 0.24%. The most common disease type was diffuse large B cell lymphoma (n=7). The median time between the transplant and diagnosis of PTLD was 85.8 months. However, all cases of PTLD after allogeneic hematopoietic stem cell transplantation occurred within 1 yr after transplantation. Ten of the 14 patients had EBV-positive tumor. Fourteen patients received combination systemic chemotherapy and four patients were treated with radiation therapy. Ten patients achieved a complete response (CR) and two patients a partial response (PR). The median follow-up period for surviving patients was 36.6 months. Nine patients remain alive (eight CR, one PR). Nine of 11 solid organ transplantations preserved graft function. The present study indicates a lower incidence rate and a longer median time before the development of PTLD than those of previous reports. Careful monitoring was needed after allogeneic hematopoietic stem cell transplantation for PTLD

Digital Workflow for Retrofitting a Surveyed Crown Using a Removable Partial Denture as an Antagonist

Digital workflow expedites the procedure of retrofitting a surveyed crown against an existing removable partial denture (RPD). This article describes a simple and straightforward technique of digital workflow where an existing RPD is scanned as an antagonist to design the rest seat, guide plane, and height of contour of a surveyed crown.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156192/2/jopr13187_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156192/1/jopr13187.pd