Most significantly, the k-means clustering utilized for mask estimation is not highly robust in the presence of outliers or interference in the data.
The clustering utilized similarity over large portions of sequence length, rather than just domains, and length-based thresholds were incorporated to address fragmentary sequences and to minimize grouping of unrelated proteins.
We also applied hierarchical clustering, utilizing a Pearson's correlation coefficient.
Multilevel models were used to identify the relationship between area-level SES at the block group level and clustering utilizing a socioeconomic position index (SEP).
We applied a combination of nearest neighbor graph and hierarchical clustering, utilizing a gene-content metric, to generate a manageable set of 1073 unified pathways (SuperPaths).
The unsupervised hierarchical clustering utilized in this study showed that expression patterns of the transcription factors in PBNT embryos were more closely aligned to the donor somatic cell nucleus, which indicates in all likelihood that the key transcription regulatory pathway of PBNT was not activated as it was in BBNT embryos.
We also assume that each cluster utilizes a separate reporting channel to transmit the sensing result from local nodes to the cluster header in the case of a conventional cluster-based CSS scheme, and the guard interval between time slots is ignored.
Their scaling behavior is evaluated on a cluster utilizing up to 1024 cores.
Most of the currently available bioinformatics tools for analysis of secondary metabolite biosynthetic gene clusters utilize the "Genes to Metabolites" approach.
A more sophisticated algorithm can be used to compute the coarse-grained periodic solution of the double clusters, utilizing an equation-free fixed point algorithm [40] and the PC expansion.
