In bottom-up tissue engineering, a method to integrate a pathway of nutrition and oxygen into the resulting macroscopic tissue has been highly desired, but yet to be established.
We apply the proposed method to integrate a set of heterogeneous data sources including the expression profiles of miRNAs and genes on 385 human ovarian cancer samples, computationally predicted miRNA gene interactions, and gene gene interactions.
Using a large replicate data set we found that signal variability in microarray data is in fact probe set-specific, and developed a novel method to integrate a priori-generated, replicate-based information on signal intensity and probe set variability into profiling differential gene expression.
We propose a two-step method to integrate an ORC to a background process, optimally considering the modifications of the ORC to increase the thermal efficiency and heat recovered by the working fluid simultaneously.
To overcome this lack of uniformity, it is important to develop methods to integrate EHRs to provide a multi-nation dataset of health.
We pursued two distinct approaches: (a) create methods to integrate the VE with commercially available ergonomic analysis tools for a synergistic use of functionalities and capabilities; (b) create a built-in ergonomic analysis module in the VE.
Different methods to integrate reaction and separation in a membrane reactor are studied in the present work, with the aim being to highlight the pros and cons of the different alternatives and the effects of the intervening parameters.
The introduction of computational methods to integrate and quantify biological data is an important step in the development of the emerging field of systems biology.
Recall that the main goal of this group of methods is to integrate a set of variables in a small number of new representative variables (components or factors), using as main criterion correlations of the examined variables, thus understanding the links between them.
For all the methods, we tried to integrate a list of 57,902 variants with a genomic feature with 17,524 regions.
In Sections 2.1 and 2.2, two different methods are investigated to integrate a single Laplacian matrix with a single kernel matrix for clustering, where the main difference is to either optimize the cluster assignment affinity matrix A as a generalized Rayleigh quotient (ratio model) or as a Rayleigh quotient (additive model).
