Explores visualization methodologies to conceive and represent systems and data, e.g., financial, media, economic, political, etc. Covers basic methods for research, cleaning, and analysis of datasets.
As a result, linear algebraic algorithms, and in particular matrix decompositions, have proven extremely successful in the analysis of datasets in the form of matrices.
Our aim was to investigate the effects of using four approaches for inferential analysis of datasets of varying size on model outcomes and potential conclusions.
His research is in the design and analysis of combinatorial and statistical algorithms for the analysis of biological data, with a focus on problems that arise in the analysis of datasets from high-throughput technologies.
An automated approach for robust evaluation of motion models that does not require manual intervention is highly desirable to enable analysis of datasets from high-throughput imaging technologies that contain hundreds or thousands of trajectories of biological particles, such as membrane receptors, vesicles, chromosomes or kinetochores, mRNA particles, or whole cells in developing embryos.
Comparative analysis of datasets from the regions revealed unfeasible prevalences and gender ratios in one (Multan).
The automation of the process allows for analysis of datasets with large numbers of frames.
CheS-Mapper can be employed for various purposes, including the analysis of datasets without endpoint activity information.
As mentioned earlier, the manual analysis of datasets in the size of hundreds of thousands of molecules is infeasible.
Therefore this method is not well suited for the analysis of datasets with large numbers of potential hospital markets.
My thesis research involved the analysis of datasets for which the number of degrees of freedom varies across the parameter space.
