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In chapter 2, 3 and 4 we introduce methods to improve interpretation of patient's genetic variation.
Therefore, introducing effective methods to improve its dissolution rate that may result in increased bioavailability is very important.
Furthermore, some researchers considering introducing new methods to improve meta-heuristic algorithms.
Finally, we discuss visualisation techniques for fuzzy data and fuzzy rules, and introduce methods to extend and improve some existing techniques.
We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition.
We introduce two methods to improve the current state of the art.
The EU project SAFEPOWER1 targets this research gap and aims to introduce certifiable methods to improve the power efficiency of mixed-criticality real-time systems (MCRTES).
Recently, laparoscopic (LAP) and circumumbilical (UMB) approaches have been introduced as alternative methods to improve cosmesis, but concerns about greater operative times, costs, and complications remain.
In this paper, we introduce the mesh adaptive methods to improve the above numerical method.
In order to reduce the waiting time before the alarm and to possibly allow some movement in the period after, we introduced some machine-learning methods to improve the accuracy.
We introduce a set of methods to improve the interpretation of ChIP-Seq data, including the inference of mediating TFs based on TFBS motif over-representation analysis and the subsequent study of spatial distribution of TFBSs.
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