PFC: A Novel Perceptual Features-Based Framework for Time Series Classification.

Time series classification (TSC) is a significant problem in data mining with several applications in different domains. Mining different distinguishing features is the primary method. One promising method is algorithms based on the morphological structure of time series, which are interpretable and accurate.

A Hybrid Method Based on Extreme Learning Machine and Wavelet Transform Denoising for Stock Prediction.

The trend prediction of the stock is a main challenge. Accidental factors often lead to short-term sharp fluctuations in stock markets, deviating from the original normal trend. The short-term fluctuation of stock price has high noise, which is not conducive to the prediction of stock trends.

A Labeling Method for Financial Time Series Prediction Based on Trends.

Time series prediction has been widely applied to the finance industry in applications such as stock market price and commodity price forecasting. Machine learning methods have been widely used in financial time series prediction in recent years. How to label financial time series data to determine the prediction accuracy of machine learning models and subsequently determine final investment returns is a hot topic.

Activeness and Loyalty Analysis in Event-Based Social Networks.

Event-based social networks (EBSNs) are widely used to create online social groups and organize offline events for users. Activeness and loyalty are crucial characteristics of these online social groups in terms of determining the growth or inactiveness of the social groups in a specific time frame. However, there is less research on these concepts to clarify the existence of groups in event-based social networks.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

Background: One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data.

Epigenetic modification of MiR-429 promotes liver tumour-initiating cell properties by targeting Rb binding protein 4.

Objective: Liver tumour-initiating cells (T-ICs) are critical for hepatocarcinogenesis. However, the underlying mechanism regulating the function of liver T-ICs remains unclear.

Methods: Tissue microarrays containing 242 hepatocellular carcinoma (HCC) samples were used for prognostic analysis.

FastDMA: an infinium humanmethylation450 beadchip analyzer.

DNA methylation is vital for many essential biological processes and human diseases. Illumina Infinium HumanMethylation450 Beadchip is a recently developed platform studying genome-wide DNA methylation state on more than 480,000 CpG sites and a few CHG sites with high data quality. To analyze the data of this promising platform, we developed FastDMA which can be used to identify significantly differentially methylated probes.

Population dynamics of cancer cells with cell state conversions.

Cancer stem cell (CSC) theory suggests a cell-lineage structure in tumor cells in which CSCs are capable of giving rise to the other non-stem cancer cells (NSCCs) but not vice versa. However, an alternative scenario of bidirectional interconversions between CSCs and NSCCs was proposed very recently. Here we present a general population model of cancer cells by integrating conventional cell divisions with direct conversions between different cell states, namely, not only can CSCs differentiate into NSCCs by asymmetric cell division, NSCCs can also dedifferentiate into CSCs by cell state conversion.

A novel left-handed double helicate constructed from L-tartrate bridged molybdenum(vi) and gadolinium(iii) atoms.

The one-dimensional double helicate, [NH4][Mo2O4Gd(H2O)6(L-C4H2O6)2] x 4H2O (1), which was synthesized by the reaction of GdCl3, L-tartaric acid and ammonium molybdate in acidified water solution, is built up by two heft-handed single-helical chains, linked up further by eight-coordinated GdIII pieces in an enantiopure left-handed double helical configuration, of which each helix is formed by L-tartrate bridged six-coordinated MoVI atoms.