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Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference
Three supervised inference methods were developed here to predict DTI and used for drug repositioning and indicated that these methods could be powerful tools in prediction of DTIs and drugRepositioning.
Multifractal detrended cross-correlation analysis for two nonstationary signals.
  • Wei‐Xing Zhou
  • Physics
    Physical review. E, Statistical, nonlinear, and…
  • 19 March 2008
A method to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously is proposed, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on.
Discrete hierarchical organization of social group sizes
This study combines data on human grouping patterns in a comprehensive and systematic study and identifies a discrete hierarchy of group sizes with a preferred scaling ratio close to three, which could reflect a hierarchical processing of social nearness by human brains.
Detrending moving average algorithm for multifractals.
The backward MFDMA algorithm is applied to analyzing the time series of Shanghai Stock Exchange Composite Index and its multifractal nature is confirmed, and it is found that the backward M FDMA algorithm also outperforms the multifractional detrended fluctuation analysis.
Detrended fluctuation analysis for fractals and multifractals in higher dimensions.
The generalization of the one-dimensional DFA and MFDFA to higher-dimensional versions works well when tested with synthetic surfaces including fractional Brownian surfaces and multifractal surfaces.
Statistical tests for power-law cross-correlated processes.
Using ρ(DCCA)(T,n), it is shown that the Chinese financial market's tendency to follow the U.S. market is extremely weak and an additional statistical test is proposed that can be used to quantify the existence of cross-correlations between two power-law correlated time series.
Multifractal detrending moving-average cross-correlation analysis.
This work develops in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA, and applies these algorithms to the return time series of two stock market indexes and to their volatilities.
Emergence of long memory in stock volatility from a modified Mike-Farmer model
The Mike-Farmer (MF) model was constructed empirically based on the continuous double auction mechanism in an order-driven market, which can successfully reproduce the cubic law of returns and the