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Discovering bi-multivariate associations between genetic markers and neuroimaging quantitative traits is a major task in brain imaging genetics. Sparse Canonical Correlation Analysis (SCCA) is a popular technique in this area for its powerful capability in identifying bi-multivariate relationships coupled with feature selection. The existing SCCA methods impose either the ℓ1-norm or its variants....
Increasing variety of molecular networks emerge from high-throughput genome data. In eukaryote, transcription factor is a major regulator at transcription level. Examining relations between features of these networks and their biological significance attracts attention of many researchers. While abundant quantity of studies represented connections between protein networks and topological parameters,...
It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular. We have thus developed a unified and powerful approach termed MTdGRN (multiple time-delayed gene regulatory network) to discover the underlying gene regulations that can span any unit(s) of time intervals. A decision tree was used to extract the time-delayed...
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