Cluster Based Term Weighting Model for Web Document Clustering

The term weight is based on the frequency with which the term appears in that document. The term weighting scheme measures the importance of a term with respect to a document and a collection. A term with higher weight is more important than a term with lower weight. A document ranking model uses these term weights to find the rank of a document in a collection. We propose a cluster-based term weighting models based on the TF-IDF model. This term weighting model update the inter-cluster and intra-cluster frequency components uses the generated clusters as a reference in improving the retrieved relevant documents. These inter cluster and intra-cluster frequency components are used for weighting the importance of a term in addition to the term and document frequency components

Dimension reduction for systems with slow relaxation

We develop reduced, stochastic models for high dimensional, dissipative dynamical systems that relax very slowly to equilibrium and can encode long term memory. We present a variety of empirical and first principles approaches for model reduction, and build a mathematical framework for analyzing the reduced models. We introduce the notions of universal and asymptotic filters to characterize `optimal' model reductions for sloppy linear models. We illustrate our methods by applying them to the practically important problem of modeling evaporation in oil spills.Comment: 48 Pages, 13 figures. Paper dedicated to the memory of Leo Kadanof

A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression.

BACKGROUND: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which genes are differentially expressed. Often these analysis stages are applied disregarding the fact that the data is drawn from a time series. In this paper we propose a simple model for accounting for the underlying temporal nature of the data based on a Gaussian process. RESULTS: We review Gaussian process (GP) regression for estimating the continuous trajectories underlying in gene expression time-series. We present a simple approach which can be used to filter quiet genes, or for the case of time series in the form of expression ratios, quantify differential expression. We assess via ROC curves the rankings produced by our regression framework and compare them to a recently proposed hierarchical Bayesian model for the analysis of gene expression time-series (BATS). We compare on both simulated and experimental data showing that the proposed approach considerably outperforms the current state of the art. CONCLUSIONS: Gaussian processes offer an attractive trade-off between efficiency and usability for the analysis of microarray time series. The Gaussian process framework offers a natural way of handling biological replicates and missing values and provides confidence intervals along the estimated curves of gene expression. Therefore, we believe Gaussian processes should be a standard tool in the analysis of gene expression time series

Growth disrupting mutations in epigenetic regulatory molecules are associated with abnormalities of epigenetic aging.

Germline mutations in fundamental epigenetic regulatory molecules including DNA methyltransferase 3 alpha (DNMT3A) are commonly associated with growth disorders, whereas somatic mutations are often associated with malignancy. We profiled genome-wide DNA methylation patterns in DNMT3A c.2312G > A; p.(Arg771Gln) carriers in a large Amish sibship with Tatton-Brown-Rahman syndrome (TBRS), their mosaic father, and 15 TBRS patients with distinct pathogenic de novo DNMT3A variants. This defined widespread DNA hypomethylation at specific genomic sites enriched at locations annotated as genes involved in morphogenesis, development, differentiation, and malignancy predisposition pathways. TBRS patients also displayed highly accelerated DNA methylation aging. These findings were most marked in a carrier of the AML-associated driver mutation p.Arg882Cys. Our studies additionally defined phenotype-related accelerated and decelerated epigenetic aging in two histone methyltransferase disorders: NSD1 Sotos syndrome overgrowth disorder and KMT2D Kabuki syndrome growth impairment. Together, our findings provide fundamental new insights into aberrant epigenetic mechanisms, the role of epigenetic machinery maintenance, and determinants of biological aging in these growth disorders

Proteomic Profiling of Mesenchymal Stem Cell Responses to Mechanical Strain and TGF-β1

Mesenchymal stem cells (MSCs) are a potential source of smooth muscle cells (SMCs) for constructing tissue-engineered vascular grafts. However, the details of how specific combinations of vascular microenvironmental factors regulate MSCs are not well understood. Previous studies have suggested that both mechanical stimulation with uniaxial cyclic strain and chemical stimulation with transforming growth factor-β1 (TGF-β1) can induce smooth muscle markers in MSCs. In this study, we investigated the combined effects of uniaxial cyclic strain and TGF-β1 stimulation on MSCs. By using a proteomic analysis, we found differential regulation of several proteins and genes, such as the up-regulation of TGF-β1-induced protein ig-h3 (BGH3) protein levels by TGF-β1 and up-regulation of calponin 3 protein level by cyclic strain. At the gene expression level, BGH3 was induced by TGF-β1, but calponin 3 was not significantly regulated by mechanical strain or TGF-β1, which was in contrast to the synergistic up-regulation of calponin 1 gene expression by cyclic strain and TGF-β1. Further experiments with cycloheximide treatment suggested that the up-regulation of calponin 3 by cyclic strain was at post-transcriptional level. The results in this study suggest that both mechanical stimulation and TGF-β1 signaling play unique and important roles in the regulation of MSCs at both transcriptional and post-transcriptional levels, and that a precise combination of microenvironmental cues may promote MSC differentiation

Mating alters gene expression patterns in Drosophila melanogaster male heads

<p>Abstract</p> <p>Background</p> <p>Behavior is a complex process resulting from the integration of genetic and environmental information. <it>Drosophila melanogaster </it>rely on multiple sensory modalities for reproductive success, and mating causes physiological changes in both sexes that affect reproductive output or behavior. Some of these effects are likely mediated by changes in gene expression. Courtship and mating alter female transcript profiles, but it is not known how mating affects male gene expression.</p> <p>Results</p> <p>We used <it>Drosophila </it>genome arrays to identify changes in gene expression profiles that occur in mated male heads. Forty-seven genes differed between mated and control heads 2 hrs post mating. Many mating-responsive genes are highly expressed in non-neural head tissues, including an adipose tissue called the fat body. One fat body-enriched gene, <it>female-specific independent of transformer </it>(<it>fit</it>), is a downstream target of the somatic sex-determination hierarchy, a genetic pathway that regulates <it>Drosophila</it> reproductive behaviors as well as expression of some fat-expressed genes; three other mating-responsive loci are also downstream components of this pathway. Another mating-responsive gene expressed in fat, <it>Juvenile hormone esterase </it>(<it>Jhe</it>), is necessary for robust male courtship behavior and mating success.</p> <p>Conclusions</p> <p>Our study demonstrates that mating causes changes in male head gene expression profiles and supports an increasing body of work implicating adipose signaling in behavior modulation. Since several mating-induced genes are sex-determination hierarchy target genes, additional mating-responsive loci may be downstream components of this pathway as well.</p