We clustered the 441 datasets, each representing a single time course, by applying the k-means algorithm and using a refined ... Identification of differentially expressed genes and cluster analysis. First, the dataset was reduced to 454 clones that showed ... Both of these clusters represent the slightest gene expression changes of our study. Within cluster 6, genes decrease the most ... 3B, Table 1). Most genes fall into clusters that display only slight expression changes (clusters 2, 4, 5, 6, 7, 10). Clusters ...http://www.jneurosci.org/content/24/26/5982
HCS clustering algorithm - Wikipedia
... is an algorithm based on graph connectivity for Cluster analysis, by first representing the similarity data in a similarity ... "Survey of clustering algorithms." Neural Networks, IEEE Transactions The CLICK clustering algorithm is an adaptation of HCS ... clustering algorithm (also known as the HCS algorithm , and other names such as Highly Connected Clusters/Components/Kernels) ... and recursively run HCS clustering algorithm on H and H'. The following animation shows how the HCS clustering algorithm ...https://en.wikipedia.org/wiki/HCS_clustering_algorithm
Systematic determination of patterns of gene expression during Drosophila embryogenesis | Genome Biology | Full Text
Systematic analysis of rigorously annotated patterns of gene expression will complement and extend the types of analyses ... that can be used to identify genes involved in developmental processes that have been missed by traditional genetic analysis. ... We present an approach for organizing the data by hierarchical clustering of annotation terms that allows us to group tissues ... Figure 8 represents one possible outcome of the clustering analysis of the annotation dataset. Filtering of the genes and ...https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0088
Clustering analysis of top 50 ranked genes is shown. Each gray block represents a tumor with higher expression than the maximum ... Using this algorithm we found that Abcb1b was among the top outliers and formed a cluster with several other genes (Fig. 3 and ... Unsupervised hierarchical cluster analysis did not separate good from poor responders (Supplementary Fig. S2). For the ... Unsupervised hierarchical cluster analysis did not separate sensitive from resistant tumors. Instead, tumors derived from the ...http://cancerres.aacrjournals.org/content/72/9/2350
Determining requirements for patient-centred care: a participatory concept mapping study | BMC Health Services Research | Full...
Analysis included the development of a similarity matrix, multidimensional scaling, hierarchical cluster analysis, selection of ... The clusters were grouped into three overarching domains, representing a cross-sectoral approach: humanity and partnership; ... ROPCCS incorporates 123 statements sorted into 13 clusters. Cluster labels were: shared responsibility for personalised health ... and achievement of each patient-centred care requirement and cluster. The study has empirically determined requirements for ...http://bmchealthservres.biomedcentral.com.preview-live.oscarjournals.springer.com/articles/10.1186/s12913-017-2741-y
Optimization of sequence alignment for simple sequence repeat regions | BMC Research Notes | Full Text
The cluster analysis resulted in completely different phylogenic trees before and after applying the new algorithm (Figure 6). ... These sequences were obtained from 26 plants representing 26 alleles. The sequences were aligned using the clustalW algorithm ... Algorithm. In this paper, we compare our new algorithm for SSR alignment with the common alignment algorithms used in other ... However, the phylogenic trees indicated that 50% of the samples showed a similar cluster before and after the new algorithm ...https://bmcresnotes.biomedcentral.com/articles/10.1186/1756-0500-4-239
GenCLiP: a software program for clustering gene lists by literature profiling and constructing gene co-occurrence networks...
... such as those identified by microarray analyses. Literature mining is an important way to assist in this task. Many literature ... We present our software program, GenCLiP (Gene Cluster with Literature Profiles), which is based on the methods presented by ... Chaussabel and Sher (Genome Biol 2002, 3(10):RESEARCH0055) that search gene lists to identify functional clusters of genes ... An array file is then generated and used to do clustering analysis with the average linkage hierarchical clustering algorithm ...https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-308
Microarray analysis of Long non-coding RNA expression profiles in human gastric cells and tissues with Helicobacter pylori...
GO and KEGG analyses have indicated that the functions of aberrantly expressed mRNAs in H.pylori infection were related closely ... LncRNA-mRNA co-expression network was constructed based on Pearson correlation analysis. Gene Ontology (GO) and KEGG Pathway ... analyses of aberrantly expressed mRNAs were performed to identify the related biological functions and pathologic pathways. The ... expression profiles of lncRNAs and mRNAs in GES-1 cells with or without H.pylori infection were explored by microarray analysis ...https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-015-0159-0
Performance evaluation of the boundary-layer height from lidar and the weather research and forecasting model at an urban...
... we use a cluster analysis algorithm of three-day back-trajectories to determine general synoptic flow patterns over Barcelona, ... Spain arriving at heights of 0.5, 1.5, and 3 km; to represent the lower PBL, upper PBL, and lower free troposphere, ... Seven clusters are determined at each arriving altitude. Regional recirculations account for 54 % of the annual total at 0.5 km ... Lidar and radiosonde estimated PBL heights are classified under objectively-determined synoptic clusters. With the final ...https://upcommons.upc.edu/handle/2117/78947
Frontiers | Super-resolution imaging of C-type lectin spatial rearrangement within the dendritic cell plasma membrane at fungal...
Contact site CTL clusters appear as disk-shaped domains of approximately 150-175 nm in diameter. The increase in length scale ... Quantitative analysis of confocal and super-resolution images demonstrated that CTL nanodomains become concentrated in the ... Contact site CTL clusters appear as disk-shaped domains of approximately 150-175 nm in diameter. The increase in length scale ... Quantitative analysis of confocal and super-resolution images demonstrated that CTL nanodomains become concentrated in the ...https://www.frontiersin.org/articles/10.3389/fphy.2014.00046/full
A study on real-time low-quality content detection on Twitter from the users' perspective
To perform the cluster analysis, we represent the tweets with a set of features (described in details in the later section) and ... We perform EM algorithm on harvested low-quality content tweets to divide them into 4 categories. Based on which, we create a ... Cluster analysis of low-quality content. We believe it is necessary to understand users' attitudes and definitions of low- ... We designed a survey according to the cluster analysis and put it online where participants had to answer two questions related ...http://pubmedcentralcanada.ca/pmcc/articles/PMC5549928/
Pyrosequencing-based analysis reveals a novel capsular gene cluster in a KPC-producing Klebsiella pneumoniae clinical isolate...
Because genes involved in L-rhamnose biosynthesis are absent in humans, this pathway may represent potential targets for the ... We report the first description of a cps cluster from a Brazilian clinical isolate of a KPC-producing K. pneumoniae. The ... we report the unique genetic organization of the cps cluster from K. pneumoniae Kp13, a clinical isolate recovered during a ... of similarity and alignment between RFLP patterns were adapted from Needleman and Wunsch's dynamic programming algorithm. By ...https://bmcmicrobiol.biomedcentral.com/articles/10.1186/1471-2180-12-173
Visualization of Disciplinary Profiles: Enhanced Science Overlay Maps : Journal of Data and Information Science
... generating new clusters of scientific disciplines, enhancing visualizations, and providing more accessible means for analysts ... Both cluster solutions were generated in VOSviewer, using its algorithm⑫. Appendix map A-3 shows the 18-cluster basemap. ... By choosing the 18-cluster option (Figure A-3) or the five-cluster option (Figure 1), one can show the analysis at a narrow or ... Prices in € represent the retail prices valid in Germany (unless otherwise indicated). Prices are subject to change without ...https://www.degruyter.com/view/j/jdis.2017.2.issue-3/jdis-2017-0015/jdis-2017-0015.xml
Purdue e-Pubs - The Summer Undergraduate Research Fellowship (SURF) Symposium: Web-Based Interactive Social Media Visual...
Second, we extend the Social Media Analytics and Reporting Toolkit (SMART) to supporting the spatial clustering analysis and ... findings prove that today's high-resolution geo-located social media platforms can enable new types of human behavior analysis ... Identified movement patterns are extracted using clustering algorithms and represented in a visual and interactive manner. We ... Identified movement patterns are extracted using clustering algorithms and represented in a visual and interactive manner. We ...https://docs.lib.purdue.edu/surf/2017/presentations/87/
The Realities of Races
You could do a statistical cluster analysis, but that is sensitive to the population samples chosen, the individual people ... representing them, the demographic history of the populations, the assumptions of the particular algorithm, and the patterns of ... based on the assumption that a small sample of Nigerians represent "pure Africans," a small sample of Chinese represent "pure ... The extremes represent the most geographically divergent, not the purest.. In other words, this business has far more to do ...http://raceandgenomics.ssrc.org/Marks/
Clustering bioinformatics tools | Gene expression array analysis - OMICtools
Gene clustering analysis is found useful for discovering groups of correlated genes potentially co-regulated or associated to ... When applied to published data sets representing different cancers or disease outcomes, this algorithm constructs XMOTIFS that ... This algorithm generates clusters of sufficiently large sample sizes as required by the user and can clusters applications with ... A clustering analysis platform to promote streamlined evaluation, comparison and reproducibility of clustering results in the ...https://omictools.com/clustering-category
Detection of chronic kidney disease and disease progression - Technion Research and Development Foundation Ltd.
... linear discriminant analysis (LDA), cluster analysis, and nearest neighbor. Each possibility represents a separate embodiment ... genetic algorithms, and fuzzy logic algorithms. Each possibility represents a separate embodiment of the present invention. In ... including linear discriminant analysis (LDA), and cluster analysis including nearest neighbor. Each possibility represents a ... discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor. 8. The method ...http://www.freepatentsonline.com/9689826.html
clusterMaker: a multi-algorithm clustering plugin for Cytoscape | BMC Bioinformatics | Full Text
... provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and ... clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, ... Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram ... and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally ...https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-436
A core-attachment based method to detect protein complexes in PPI networks | BMC Bioinformatics | Full Text
Traditional graph clustering algorithms can also be applied to detect dense clusters as protein complexes [9-11]. Markov ... This graph structure modeling is helpful for global analysis of PPI data, such as graph clustering for protein complex ... in which a vertex in vertex set V represents a protein and an edge in edge set E represents an interaction between two distinct ... Core-removal algorithm. Given a vertex v, if the core graph of G v , CG, is dense enough, core-removal algorithm will return it ...https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-169
Clustering Similar Points - Stellar Parameter Analysis Management - Colby College Wiki
To get better clusters, we first ran principal components analysis to compress the data to axes that represent almost all of ... K-Means Algorithm. *instantiate k means to start with: our algorithm divides the data into k equal parts, and selects a random ... Clusters are categorical, so it is intuitive to visualize them with color. We made 'cluster' an option for the color 'axis,' ... One goal of machine learning is to cluster data points by identifying similar points. A common method of clustering is k-means ...https://wiki.colby.edu/display/SPAM/Clustering+Similar+Points
Formal concept analysis - Wikipedia
... one to use standard definitions and algorithms from multidimensional concept analysis for computing multidimensional clusters. ... where n-dimensional clusters of similar values in n-dimensional data are represented by n+1-dimensional concepts. This ... Association rule learning Cluster analysis Commonsense reasoning Conceptual clustering Concept learning Correspondence analysis ... The formal concept analysis can be used as a qualitative method for data analysis. Since the early beginnings of FBA in the ...https://en.wikipedia.org/wiki/Formal_concept_analysis
Method of increasing murine ES cell differentiation with PCL2 - Patent # 8252761 - PatentGenius
Clustering was performed using the K-means clustering algorithm. GO analysis was performed on this gene set andover-represented ... Clustering was performed using the K-means clustering algorithm. GO analysis wasperformed on this gene set and over-represented ... Clustering was performed using the K-means clustering algorithm. GO analysis was performed on this gene set andover-represented ... Clustering was performed using the K-means clustering algorithm. GO analysis wasperformed on this gene set and over-represented ...http://www.patentgenius.com/patent/8252761.html
Stability-based validation of dietary patterns obtained by cluster analysis | Nutrition Journal | Full Text
A clustering algorithm A with a predefined number of cluster k constructs a solution Y of the data set X into k clusters (Y := ... Ak(X)). This solution Y is represented by an n-dimensional vector of labels Y = (Y1, …, Yn) where Yi = v if the i-th individual ... Formalization of cluster analysis. Let X = (X1, …, Xn) be the dataset of n = 2298 individuals to be clustered where Xi is a 45- ... Hennig C. Cluster-wise assessment of cluster stability. Computational Statistics & Data Analysis. 52(1):258-71Google Scholar. ...https://nutritionj.biomedcentral.com/articles/10.1186/s12937-017-0226-9
Age-dependent changes in prefrontal intrinsic connectivity | PNAS
... spike waveforms were sorted into separate units using an automated cluster analysis method based on the KlustaKwik algorithm, ... but this represents a random source of error for our analysis and can only dilute the difference between groups that have ... 2003) Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network. ... In fact, analyses of the distributions of young and adult cross-correlation strengths (Fig. 1C) revealed that the difference in ...http://www.pnas.org/content/111/10/3853
Saint Mary's University | Engineering - Faculty and Staff - Directory
... clustering, principle component analysis and adaptive filtering. The kernel function is employed to map the input space to a ... The term "kernel machine" refers to a family of machine learning algorithms that can be used for classification, regression, ... high dimensional feature space which gives the kernel machine the ability to represent non-linear relationships in the input ...https://smu.ca/academics/departments/engineering-upcoming-events.html