Phylogenetic segregation of 1121, 16S rDNA sequences of 10 different Bacillus species in to 89 clusters enabled us to develop a phylogenetic frame work of 34 representative sequences.
The profiles similarity of those clusters enabled us to identify two major classes: 1) class I: (clusters 0, 2, 3, 6, 8, 10, 13, 14, 15 and 19) containing genes whose expression increased immediately after 15 min induction and decreased after 6 and 8 hours and class II: (clusters 1, 4, 5, 7, 9, 11, 12 and 16) containing genes whose expression levels increased only after 6 and 8 hours induction.
Our multipartner protein interface clusters enable us to address questions like: What makes a given site bind different proteins?
If a biological process of the parasite is conserved in yeast or human, cross-species comparison of related OPI clusters enables us to find additional evidence to support newly predicted Plasmodium genes functions.
A comparison between human, mouse and rat miRNA clusters enables us to classify miRNAs in hetero-clusters into two categories: one is conserved miRNAs, which are observed in human, mouse and rat clusters; the other is non-conserved miRNAs, which exist in human clusters but are unobtainable in mouse or rat clusters.
Specifically, unsupervised clustering enabled us to identify patterns of chromatin remodeling, which we link to signaling pathways and transcription factor activity associated with EMT through comprehensive systems-level analyses.
Relative comparisons of genomic copy-number profiles by unsupervised hierarchical clustering enabled us to categorize gastric intramucosal neoplasms according to lineage-specific patterns of CNAs and different degrees of genomic copy-number instability as stable, unstable, and intermediate.
This spatial clustering enabled us to detect lateralization in the CNV and the slow posterior positivity, as has been previously reported in the literature on instructed task switching (Astle et al. 2006; Lavric et al. 2008).
Our approach based on ortholog clustering enables us to infer functional information directly from OGs using a subsequent drastic threshold for similarity searches and offers a conceptual framework for inferring information from various genomes.
For group I genes, hierarchical cluster analysis enabled us to identify 2 major clusters, called A and B. Cluster A had the 1,482 most abundant transcripts in fruit-pericarp at 217 DPA, while cluster B bore the 2,909 most abundant transcripts in fruit-AZ at 217 DPA.
First, clustering optimization enabled us to test alignment programs and distance functions and to identify the best approach es).
