1,720,960 research outputs found
Identifying cancer gene subtypes from gene expression by co-clustering algorithm and support vector machine
Full text linkCancer subtype information is significant to understand tumour heterogeneity. Present methods to find cancer subtypes have focused on utilizing traditional clustering algorithms such as hierarchical clustering. Since most of these methods depend on high dimensional data, the drawback is to divide the genes into different clusters, where a gene or a condition only belongs to one cluster. A gene may contribute to more than one biological process, so a gene may belong to multiple clusters. Besides, the centroid in the objective function of network-assisted coclustering for the identification of cancer subtypes (NCIS) dragged with outliers. So, these outliers get their cluster instead of being ignored. Hence, this research is focusing on improving the NCIS method. Enhanced NCIS (iNCIS) is basically assigned weights to genes base on a gene interaction network, and it imperatively optimizes the sum-squared residue to get co-clusters. Next, supervised infinite feature selection with multiple support vector machine (SinfFS-mSVM) is proposed to obtain significant genes from a high dimensional data by using the classes obtained from iNCIS and improve the accuracy of classification. The effectiveness of iNCIS and SinfFS-mSVM is being evaluated on a large-scale Breast Cancer (BRCA) and Glioblastoma Multiforme (GBM) from The Cancer Genome Atlas (TCGA) project. From the implementation, there are five breast cancer gene subtypes and four glioblastoma multiforme cancer gene subtypes that have been successfully identified. The weighted co-clustering approach in iNCIS provides a unique solution to integrate gene network interaction into the clustering process. The improvement of the co-clustering Rand Index and F1-measure is 54.5% and 33.9% for BRCA and 34.2% and 31.5% for GBM. Meanwhile, a significant gene subset with higher classification accuracy was selected from SinfFS-mSVM. The classification accuracy for the selected gene subset improved by 3.00% and 2.99% for BRCA and GBM, correspondingly. Furthermore, biological validation conducted on the selected genes from each subtype is to justify the validity of the results. In conclusion, the empirical study on large-scale cancer datasets using iNCIS and SinfFS-mSVM comprehensively find cancer gene subtypes and genes by achieving higher clustering and classification accuracy. Future works are needed to integrate more comprehensive gene network information and to select optimal parameters
Functional analysis of cancer gene subtype from co-clustering and classification
Get PDFCancer is a heterogeneity genetic disease with huge phenotypic alterations among dissimilar cancers types or even between same cancer types. Recent expansions of genome-wide profiling technologies offer a chance to explore molecular changes variations throughout advancement of cancer. Therefore, various statistical and machine learning algorithms have been designed and developed for the handling and interpretation of high-throughput microarray molecular data. Discovery of molecular subtypes studies have permitted the cancer to be allocated into similar groups that are deliberated to port similar molecular and clinical characteristics. Thus, the main objective of this research is to discover cancer gene subtypes and classify genes to obtain higher accuracy. In particular improved co-clustering algorithm used to discover cancer subtypes. And then supervised infinite feature selection gene selection method was combined with multi class SVM for classification of selected genes and further biological analysis. The analysis on breast cancer and glioblastoma multiforme evidences that top genes involved in cancer and the pathways present in both cancer top genes. The functional analysis is useful in medical and pharmaceutical field for cancer diagnosis and prognosis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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