AtPAN: an integrated system for reconstructing transcriptional regulatory networks in Arabidopsis thaliana

<p>Abstract</p> <p>Background</p> <p>Construction of transcriptional regulatory networks (TRNs) is of priority concern in systems biology. Numerous high-throughput approaches, including microarray and next-generation sequencing, are extensively adopted to examine transcriptional expression patterns on the whole-genome scale; those data are helpful in reconstructing TRNs. Identifying transcription factor binding sites (TFBSs) in a gene promoter is the initial step in elucidating the transcriptional regulation mechanism. Since transcription factors usually co-regulate a common group of genes by forming regulatory modules with similar TFBSs. Therefore, the combinatorial interactions of transcription factors must be modeled to reconstruct the gene regulatory networks.</p> <p>Description For systems biology applications, this work develops a novel database called <it>Arabidopsis thaliana </it>Promoter Analysis Net (AtPAN), capable of detecting TFBSs and their corresponding transcription factors (TFs) in a promoter or a set of promoters in <it>Arabidopsis</it>. For further analysis, according to the microarray expression data and literature, the co-expressed TFs and their target genes can be retrieved from AtPAN. Additionally, proteins interacting with the co-expressed TFs are also incorporated to reconstruct co-expressed TRNs. Moreover, combinatorial TFs can be detected by the frequency of TFBSs co-occurrence in a group of gene promoters. In addition, TFBSs in the conserved regions between the two input sequences or homologous genes in <it>Arabidopsis </it>and rice are also provided in AtPAN. The output results also suggest conducting wet experiments in the future.</p> <p>Conclusions</p> <p>The AtPAN, which has a user-friendly input/output interface and provide graphical view of the TRNs. This novel and creative resource is freely available online at <url>http://AtPAN.itps.ncku.edu.tw/</url>.</p

The Relationship between Stock Price and EPS: Evidence Based on Taiwan Panel Data

In this study, we use panel cointegration methods to investigate the relationship between stock prices and earnings-per-share (EPS). Furthermore, we consider whether stock prices respond to EPS under the different level of growth rate of operating revenue. The empirical result indicated that the cointegration relationship existed between stock prices and EPS in the long-run. Furthermore, we found that for the firm with a high level of growth rate, EPS has less power in explaining the stock prices however, for the firm with a low level of growth rate, EPS has a strong impact in stock prices.Earnings Response Coefficient (ERC)

Missing Corner in the Sky: Massless Three-Point Celestial Amplitudes

We study three-point celestial amplitudes in Minkowski space for massless scalars, photons, gluons, and gravitons. The corresponding scattering amplitudes in the plane wave basis vanish for generic momenta due to momentum conservation. However, the delta function for the momentum conservation has support in the soft and colinear regions, and contributes to the Mellin and shadow integrals that give non-zero celestial amplitudes. We show that the amplitudes with the incoming (outgoing) particles in the (shadow) conformal basis take the standard form of correlators in two-dimensional conformal field theory. In particular, the three-point celestial gluon amplitudes take the form of a three-point function of a spin-one current with two spin-one primary operators, which strongly supports the relation between soft spinning particles and conserved currents. Moreover, the three-point celestial amplitudes of one graviton and two massless scalars take the form of a correlation function involving a primary operator of conformal weight one and spin two, whose level-one descendent is the supertranslation current

Shape restricted regression with random Bernstein polynomials

Shape restricted regressions, including isotonic regression and concave regression as special cases, are studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors have large supports, select only smooth functions, can easily incorporate geometric information into the prior, and can be generated without computational difficulty. Algorithms generating priors and posteriors are proposed, and simulation studies are conducted to illustrate the performance of this approach. Comparisons with the density-regression method of Dette et al. (2006) are included.Comment: Published at http://dx.doi.org/10.1214/074921707000000157 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Split representation in celestial holography

We develop a split representation for celestial amplitudes in celestial holography, by cutting internal lines of Feynman diagrams in Minkowski space. More explicitly, the bulk-to-bulk propagators associated with the internal lines are expressed as a product of two boundary-to-bulk propagators with a coinciding boundary point integrated over the celestial sphere. Applying this split representation, we compute the conformal partial wave and conformal block expansions of celestial four-point functions of massless scalars and photons on the Euclidean celestial sphere. In the $t$-channel massless scalar amplitude, we observe novel intermediate exchanges of staggered modules in the conformal block expansion.Comment: 76 page

Can Mergers And Acquisitions Be The Successful Path Of Internationalisation For MNEs? Cases Analyse From Unilever Experiences.

Internationalisation is the greatest tendency for all the businesses, which brings about the competitions for companies to scramble for the global markets. The quickest way to expand the overseas market is via the approach of mergers and acquisitions (M&A). Through M&A firms can transform a small firm into a large corporation or increase the market share significantly. Therefore, M&A turns into one of the common process of foreign direct investment (FDI). The topic for discover the M&A activities by MNEs was chosen based on this perception of the rapid changing business environment. In this paper, by using the qualitative research methodology with the cases of Unilever and examining the topic based on the theoretical framework. The aim of the paper is to analyse to what extent M&A can bring the success to MNEs. Key Words: entry modes, mergers and acquisitions (M&A), internationalisation, transaction costs, value creation, empire-building, Unilever, Alberto Culver, Concern Kalina

A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

"An Econometric Analysis of SARS and Avian Flu on International Tourist Arrivals to Asia"

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu will be compared directly according to human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.

Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites

[[abstract]]Abstract: Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in fivefold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 2526-2537, 200