An Effective Clustering Approach to Stock Market Prediction

In this paper, we propose an effective clustering method, HRK (Hierarchical agglomerative and Recursive K-means clustering), to predict the short-term stock price movements after the release of financial reports. The proposed method consists of three phases. First, we convert each financial report into a feature vector and use the hierarchical agglomerative clustering method to divide the converted feature vectors into clusters. Second, for each cluster, we recursively apply the K-means clustering method to partition each cluster into sub-clusters so that most feature vectors in each sub-cluster belong to the same class. Then, for each sub-cluster, we choose its centroid as the representative feature vector. Finally, we employ the representative feature vectors to predict the stock price movements. The experimental results show the proposed method outperforms SVM in terms of accuracy and average profits

Lrf suppresses prostate cancer through repression of a Sox9-dependent pathway for cellular senescence bypass and tumor invasion

Lrf has been previously described as a powerful proto-oncogene. Here we surprisingly demonstrate that Lrf plays a critical oncosuppressive role in the prostate. Prostate specific inactivation of Lrf leads to a dramatic acceleration of Pten-loss-driven prostate tumorigenesis through a bypass of Pten-loss-induced senescence (PICS). We show that LRF physically interacts with and functionally antagonizes SOX9 transcriptional activity on key target genes such as MIA, which is involved in tumor cell invasion, and H19, a long non-coding RNA precursor for an Rb-targeting miRNA. Inactivation of Lrf in vivo leads to Rb down-regulation, PICS bypass and invasive prostate cancer. Importantly, we found that LRF is genetically lost, as well as down-regulated at both the mRNA and protein levels in a subset of human advanced prostate cancers. Thus, we identify LRF as a context-dependent cancer gene that can act as an oncogene in some contexts but also displays oncosuppressive-like activity in Pten−/− tumors

Specificity factors in cytoplasmic polyadenylation

Poly(A) tail elongation after export of an messenger RNA (mRNA) to the cytoplasm is called cytoplasmic polyadenylation. It was first discovered in oocytes and embryos, where it has roles in meiosis and development. In recent years, however, has been implicated in many other processes, including synaptic plasticity and mitosis. This review aims to introduce cytoplasmic polyadenylation with an emphasis on the factors and elements mediating this process for different mRNAs and in different animal species. We will discuss the RNA sequence elements mediating cytoplasmic polyadenylation in the 3′ untranslated regions of mRNAs, including the CPE, MBE, TCS, eCPE, and C-CPE. In addition to describing the role of general polyadenylation factors, we discuss the specific RNA binding protein families associated with cytoplasmic polyadenylation elements, including CPEB (CPEB1, CPEB2, CPEB3, and CPEB4), Pumilio (PUM2), Musashi (MSI1, MSI2), zygote arrest (ZAR2), ELAV like proteins (ELAVL1, HuR), poly(C) binding proteins (PCBP2, αCP2, hnRNP-E2), and Bicaudal C (BICC1). Some emerging themes in cytoplasmic polyadenylation will be highlighted. To facilitate understanding for those working in different organisms and fields, particularly those who are analyzing high throughput data, HUGO gene nomenclature for the human orthologs is used throughout. Where human orthologs have not been clearly identified, reference is made to protein families identified in man

Isoform Diversity and Regulation in Peripheral and Central Neurons Revealed through RNA-Seq

To fully understand cell type identity and function in the nervous system there is a need to understand neuronal gene expression at the level of isoform diversity. Here we applied Next Generation Sequencing of the transcriptome (RNA-Seq) to purified sensory neurons and cerebellar granular neurons (CGNs) grown on an axonal growth permissive substrate. The goal of the analysis was to uncover neuronal type specific isoforms as a prelude to understanding patterns of gene expression underlying their intrinsic growth abilities. Global gene expression patterns were comparable to those found for other cell types, in that a vast majority of genes were expressed at low abundance. Nearly 18% of gene loci produced more than one transcript. More than 8000 isoforms were differentially expressed, either to different degrees in different neuronal types or uniquely expressed in one or the other. Sensory neurons expressed a larger number of genes and gene isoforms than did CGNs. To begin to understand the mechanisms responsible for the differential gene/isoform expression we identified transcription factor binding sites present specifically in the upstream genomic sequences of differentially expressed isoforms, and analyzed the 3′ untranslated regions (3′ UTRs) for microRNA (miRNA) target sites. Our analysis defines isoform diversity for two neuronal types with diverse axon growth capabilities and begins to elucidate the complex transcriptional landscape in two neuronal populations

ICAR: endoscopic skull‐base surgery

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