Sentence examples for clustering function from inspiring English sources

Gene ontology analyses were performed using the functional annotation clustering function of DAVID (http://david.abcc.ncifcrf.gov/).abcc.ncifcrf.gov/

To visualize the function-based genomic comparison, the 27 mycobacterial genomes were clustered based on functional profiles; the PCA clustering analysis was conducted using the genome clustering function of the JGI IMG system (https://img.jgi.doe.gov/cgi-bin/w/main.cgi) with the condition: clustering type, COG and clustering method, Principal Components Analysis (PCA).

This later clustering function of myosin II depends on EGF receptor signaling.

(3) By adopting different power coefficients in converting or clustering function, different task-sequences or task-clusters can be obtained.

Moreover, each text corpus was annotated using our proposed Slovak morphological classifier[13] based on a hidden Markov model (HMM) together with suffix-based word clustering function and restricted by manually morphologically annotated lexicon of words.

As a consequence, ANNs can be used for a variety of applications, among which are classification in medical applications [3, 5, 23, 35], descriptive modeling, clustering, function approximation, time series prediction [36] and sonar or radar detection [37].

GLay not only supplements existing clustering functions, but also provides structured and informative visualization for more efficient exploration and analysis of large biological networks.

Here we review recent studies focusing on how molecular clustering functions in different biological contexts, the potential importance of clustering for information processing, as well as the physical nature of cluster formation.

The cluster centroids were randomly initialized by the internal mechanisms of the clustering functions, in order to respect the unbiased nature of the study.

This tool supports various types of distance functions (euclidean, maximum, manhattan, binary, minkowski) and various types of clustering functions (complete, average, single).

Furthermore, in this model, a new stochastic search algorithm is applied to optimize the clustering objective function.