According to our observation, most data analysis methods have limitations for big data, that can be described as follows: Unscalability and centralization Most data analysis methods are not for large-scale and complex dataset.
Unscalability and centralization Most data analysis methods are not for large-scale and complex dataset.
Concurrently, available genetic information has increased as a result of more sophisticated experimental methods and centralization of genetic information in public genome databases (such as Ensembl [ 11], NCBI [ 12] and UCSC [ 13]), gene expression databases (such as GEO [ 14]) and human variation databases (such as HapMap [ 15]).
Centralization signs are detected through methods originally developed by McKenzie [ 9, 10].
The original framework [23] used an existing method to measure degree centralization defined in [22].
The aberration detection method 2 (algorithmorithm with centralization and fuzzy zero correction was used to define aberrant intervals.
Centralization [ 31] is a normalization method that estimates for each pair of arrays the factor of proportionality.
We used UCINET Version 6.205 to calculate density, network centralization, and in-degree centrality [ 43].
The wiki network is found to be non-central (i.e. degree centralization is 0.1457 and betweenness centralization is 0.060).
Cardiogenic shock was defined by (1) low systolic blood pressure (<90 mmHg) without use of inotropes/vasopressors, (2) decreased cardiac output assessed by any method, reduced mixed or central venous oxygen saturation, (3) absence of hypovolemia, (4) signs of organ malperfusion (oliguria, lactate-acidosis, cyanosis, centralization, changes in mental status) [37, 38].
