The prediction performance based on the phenomenon is better than those of existing prediction methods and is tested on various datasets, including a dataset of enzymes that do not have any bounded ligand in their crystallographic structures.
This type of machine learning has been used to analyze various datasets including domain mapping of amino acid sequences in proteins and facial recognition in pictures on the web.
Fiori and Jager [ 9], Fiori et al. [ 10]; Fiori et al. [ 19] and Litwin [ 20] used social network measures from various datasets including the Wisconsin Longitudinal Study, Americans Changing Lives Studyy, the Berlin Aging Study, and data from the Israeli Central Bureau of Statistics to classify types of individuals' social networks in old age.
Further evaluation conducted by integrating various dataset including routine core analysis, facies description, thin section, and petrophysical logs revealed that: 1. Micrites and micritization in the studied reservoir occurred on all the identified facies.
Combinatorial fusion has also been used for enhancing the analysis of various biomedical datasets including virtual screening for molecular compounds [3], protein structure prediction [24], and ChIP-seq peak detection [25].
From their experiments, it is seen that MWMOTE outperforms RAMO and SMOTE on various benchmark datasets including biomedical data.
Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed.
We integrated various type of datasets, including miRNA-target interactions, transcription factor (TF) and their targets, expression profiles, genomic annotations and pathways, into a comprehensive database, and developed various statistical and mining tools, together with a user-friendly web interface.
We identified additional strong CTCF enrichment at the KCNK9 promoter and a region within intron 17 of TRAPPC9 (regions 1 and 3 of Figures 3 and 5C, respectively), which has an enhancer chromatin signature with the co-enrichment of H3K4me1, H3K27ac and p300 in various brain ChIP-seq datasets, including the frontal cortex [ 28, 29].
After an initial hiatus (which will probably happen), we will soon come to balance the benefits of various features of datasets, including size of data, source of data, quality of data, strength of effect, plausibility of effect, reproducibility of effect, as well as issues about prespecification and multiplicity adjustments.
Comparison with various types of experimental datasets (including QTL fine-mapping and Genome Wide Association Study results) indicated both statistical significance and biological relevance of the obtained connections between genes and traits.
