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Search Results: 1 - 10 of 22906 matches for " Shinsheng Yuan "
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Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study
Wei Sun, Shinsheng Yuan, Ker-Chau Li
BMC Genomics , 2008, DOI: 10.1186/1471-2164-9-242
Abstract: To overcome this limitation, we study the expression of a pair of genes and treat the variation in their co-expression pattern as a two dimensional quantitative trait. We develop a method to find gene pairs, whose co-expression patterns, including both signs and strengths, are mediated by genetic variations and map these 2D-traits to the corresponding genetic loci. We report several applications by combining 1D-trait mapping with 2D-trait mapping, including the contribution of genetic variations to the perturbations in the regulatory mechanisms of yeast metabolic pathways.Our approach of 2D-trait mapping provides a novel and effective way to connect the genetic variation with higher order biological modules via gene expression profiles.Known as "eQTL" or "genetical genomics", the approach of treating gene expression profiles as quantitative traits and mapping them to genetic loci have been applied in yeast [1,2], worm [3], plant [4,5], fly [6], mouse [7,8], rat [9], and human [10,11] recently. These studies have shown that the level of gene expression is highly heritable, and it can be linked to either a local locus (cis-linkage) or a distant locus (trans-linkage). Most eQTL studies consider the expression profiles of different genes as different traits to be mapped one by one separately. The expression profile of a single gene can be compared with the genotype profiles of densely distributed genetic markers to find significant linkages/associations (Figure 1(a)). This is 1D (one dimension) trait mapping.In this work, we shall investigate a different type of genetic interference that cannot be analyzed under the above one-gene one-trait formulation. Recent studies have demonstrated that transcription regulation of functionally associated genes can be dependent on the relevant cellular states such as fluctuations in the levels of nutrients, metabolites, hormones or other signaling molecules [12]. This raises the question of whether the co-regulation pattern, hence th
A method for analyzing censored survival phenotype with gene expression data
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Chen, Ker-Chau Li
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-417
Abstract: We propose a method for an integrated study of survival time and gene expression. This method can be summarized as a two-step procedure: in the first step, a moderate number of genes are pre-selected using correlation or liquid association (LA). Imputation and transformation methods are employed for the correlation/LA calculation. In the second step, the dimension of the predictors is further reduced using the modified sliced inverse regression for censored data (censorSIR).The new method is tested via both simulated and real data. For the real data application, we employed a set of 295 breast cancer patients and found a linear combination of 22 gene expression profiles that are significantly correlated with patients' survival rate.By an appropriate combination of feature selection and dimension reduction, we find a method of identifying gene expression signatures which is effective for survival prediction.The DNA microarray technique allows researchers to simultaneously interrogate the expression levels of all genes in an organism. It has been widely applied in disease studies, such as cancer subtype discovery, cancer/normal sample discrimination, disease gene identification [1-3]. Recently several studies have focused on dissecting the relation between survival time and gene expression [4-7]. One difficulty of these studies is that the survival times are often right-censored. For example, at the ends of the studies, some patients may still be alive. We only know that their survival times are greater than the last follow-up time, but not the exact survival times. Thus, treating these censored survival times as the true life times without adjustment will lead to systematic bias. Another difficulty is that microarray gene expression data are often measured at the full genome scale with tens of thousands of gene expression profiles, while the number of patients under study is relatively small, thereby presenting a difficult variable selection problem.Many methods of c
Genome-wide expression links the electron transfer pathway of Shewanella oneidensis to chemotaxis
Shang-Kai Tai, GuanI Wu, Shinsheng Yuan, Ker-Chau Li
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-319
Abstract: Through a web of information obtained by our data analysis, a network of transcriptional regulatory relationship between chemotaxis and electron transfer pathways is revealed, highlighting the important roles of the chemotaxis gene cheA-1, the magnesium transporter gene mgtE-1, and a triheme c-type cytochrome gene SO4572.We found previously unknown relationship between chemotaxis and electron transfer using LA system. The study has the potential of helping researchers to overcome the intrinsic metabolic limitation of the microorganisms for improving power density output of an MFC.Shewanella oneidensis MR-1 (= ATCC 700550 = CIP 106686 = BCRC 17276), previously designated Alteromonas putrefaciens MR-1 or Shewanella putrefaciens strain MR-1, is a facultative anaerobic gram-negative bacterium with a single unsheathed polar flagellum [1-4]. The strain MR-1, isolated from Oneida Lake in New York, shows bioremediation potential and metabolically versatile properties. Under aerobic conditions, S. oneidensis utilizes oxygen as the final electron acceptor; nevertheless, S. oneidensis undertakes respiration by reducing alternative terminal electron acceptors such as nitrite, sulfite, fumarate, metals [Mn(III/IV), Fe(III), and Cr(VI)], and radionuclides [U(VI) and Pu(IV)] under anaerobic environment [5-10]. The remarkable anaerobic respiratory plasticity (ARP) involves many genes. In this study, we only considered a subset, cymA, mtrA, mtrB, omcB (also known as mtrC), omcA, gspF, and gspD genes [11,12].The functions of these ARP genes have been characterized. The gene cymA (locus tag SO4591) encodes a cytoplasmic membrane-bound, tetraheme cytochrome c that serves as an entry point for electron flow from the cytoplasm to decaheme cytochrome c, encoded by mtrA (SO1777) [11-13]. The electrons are relayed through the periplasm to the outer membrane (OM) protein encoded by the gene mtrB (SO1776) [11-13], which also plays a role required for the proper localization and insertion of c
Finding disease candidate genes by liquid association
Ker-Chau Li, Aarno Palotie, Shinsheng Yuan, Denis Bronnikov, Daniel Chen, Xuelian Wei, Oi-Wa Choi, Janna Saarela, Leena Peltonen
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-10-r205
Abstract: Studies aiming to identify susceptibility genes in complex diseases have proceeded along two lines. The traditional candidate gene approach is limited by our ability to come up with a comprehensive list of biologically related genes. On the other hand, the 'hypothesis free' approach relies on genome-wide scans for disease loci, typically via linkage in exceptionally large families or via association in case control studies. Multiple sclerosis (MS), which is one of the most common neurologic disorders affecting young adults, is characterized by demyelination and reactive gliosis [1]. Analogous to many complex traits, genome scans in MS have identified numerous chromosomal loci often with only a nominal evidence for linkage to MS [2-6]. With the notable exception of the human leukocyte antigen (major histocompatibility complex [MHC]) locus on 6p21, evidence for specific MS genes emerging from these studies is still scanty. Thus far, the only associated non-HLA genes replicated in multiple populations are the PRKCA gene [7] and the recently reported IL2RA and IL7R genes [8]. For MS, as for most complex traits, the loci derived from linkage scans have remained quite wide because of multiple uncertainties concerning the disease model in statistical analyses. To expedite the process of gene identification in these wide DNA regions, we need novel approaches to identify potentially involved pathways and to prioritize genes on identified loci for further sequencing efforts.Our idea is to turn to full genome functional studies for these goals. As illustrated in Figure 1, our approach takes advantage of the availability of abundant microarray data and a wealth of genomic/proteomic knowledge base from the public domain. Our intention is to integrate information from both the candidate gene and the full genome scan (thus far mostly family-based linkage) approaches. In this report we use two previously reported MS susceptibility genes, identified in the same study sample [7,9], n
Tissue-specific gene expression templates for accurate molecular characterization of the normal physiological states of multiple human tissues with implication in development and cancer studies
Pei-Ing Hwang, Huan-Bin Wu, Chin-Di Wang, Bai-Ling Lin, Cheng-Tao Chen, Shinsheng Yuan, Guani Wu, Ker-Chau Li
BMC Genomics , 2011, DOI: 10.1186/1471-2164-12-439
Abstract: By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific Gene Expression Templates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis.Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity.These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.It has been well-recognized that within a cell, not only genes participate in cascades of biochemical events (pathways), but also the pathways themselves cross-talk with each other as a delicate and intriguing network system. Such complexity was reflected in the normal biological processes (tissue development, for example) as well as in the complex disease processes such as autism, cancer, rheumatoid arthritis and coronary artery disease [1,2]. In addition, the genetic interactions of oncogenes and tumor suppressor genes may perturb the normal network system through a variety of altered molecular properties of the normal genes, magnifying the difficulties encountered
Non-Negativity Preserving Numerical Algorithms for Problems in Mathematical Finance  [PDF]
Yuan Yuan
Applied Mathematics (AM) , 2018, DOI: 10.4236/am.2018.93024
We give a study result to analyze a rather different, semi-analytical numerical algorithms based on splitting-step methods with their applications to mathematical finance. As certain subsistent numerical schemes may fail due to producing negative values for financial variables which require non-negativity preserving. These algorithms which we are analyzing preserve not only the non-negativity, but also the character of boundaries (natural, reflecting, absorbing, etc.). The derivatives of the CIR process and the Heston model are being extensively studied. Beyond plain vanilla European options, we creatively apply our splitting-step methods to a path-dependent option valuation. We compare our algorithms to a class of numerical schemes based on Euler discretization which are prevalent currently. The comparisons are given with respect to both accuracy and computational time for the European call option under the CIR model whereas with respect to convergence rate for the path-dependent option under the CIR model and the European call option under the Heston model.
The Negative Effect of Brand Attachment: How Attachment Styles Help Explain Anti-Brand Behavior  [PDF]
Yuan Yuan, Ming Lei
Open Journal of Business and Management (OJBM) , 2017, DOI: 10.4236/ojbm.2017.51013
Abstract: Enterprises tend to attach importance to consumer brand relationship in the marketing context, especially the establishment and culture of attachment relationship, and they try to maintain brand loyalty through consumers’ high self-connection. But they ignore the possibility that brand attachment leads to anti-brand behavior; however, previous study was less involved in the negative effects of brand attachment and negative brand behavior. So on the basis of relevant research literature review, we firstly illustrate two kinds of incentive of anti-brand behavior: 1) the loss of functional benefit; 2) the violation of self-concept, and then discussed the theoretical framework that brand attachment leads to anti-brand behavior from the perspective of consumers’ individual characteristics. The purpose of this paper is to explore the strong brand attachment relationship between consumers and brand when and why it will be transformed into a strong negative brand behavior, and thus provide a new perspective on the study of brand attachment.
The Panzar-Rosse Statistic Revisited  [PDF]
Hiroshi Gunji, Yuan Yuan
Theoretical Economics Letters (TEL) , 2017, DOI: 10.4236/tel.2017.71004
Abstract: In this note, we prove that even if the technology of firms exhibits increasing returns to scale, the Panzar-Rosse statistic in a monopolistic competitive market is still available and has a negative value. Further, we show that the statistic would be greater than unity if firms with increasing-returns-to-scale technology were to choose a saddle point under certain conditions. This implies that the value of greater than unity is not actually observed.
Optimization of Dynamic Portfolio Insurance Model  [PDF]
Yuan Yao
Journal of Mathematical Finance (JMF) , 2012, DOI: 10.4236/jmf.2012.22019
Abstract: This paper establishes a dynamic portfolio insurance model under the condition of continuous time, based on Meton's optimal investment-consumption model, which combined the method of replicating dynamic synthetic put option using risk-free and risk assets. And it transfers the problem of investor's individual intertemporal dynamic portfolio insurance decision into a problem of static utility maximization under condition of continuous time, and give the optimal capital combination strategies corresponding to the optimal wealth level of the portfolio insurers, and compares the difference of strategies between this model and Merton model. The conclusions show that investors' optimal strategies of portfolio insurance are not dependent on their wealth, but market risk. That is to say, the higher the risk is, the more the demand of portfolio insurance is.
Reduced Partition Function Ratio in the Frequency Complex Plane: A Mathematical Approach  [PDF]
Jie Yuan
Open Journal of Geology (OJG) , 2014, DOI: 10.4236/ojg.2014.412049
Abstract: This paper gives a mathematical approach to calculate the fractionation factor of isotopes in a general cluster (also known as super-molecule), which composes of necessary chemical effect within three bonds outside the interested atom(s). The cluster might have imaginary frequencies after being optimized in quantum softwares. The approach includes the contribution of the difference, which is resulted from the substitution of heavy and light isotopes in the cluster, of vibrations of imaginary frequencies to give precise prediction of isotope fractionation factor. We call the new mathematical approximation “reduced partition function ratio in the frequency complex plane (RPFRC)”. If there is no imaginary frequency for a cluster, RPFRC is simplified to be Urey (1947) or Bigeleisen and Mayer (1947) formula. Final results of this new algorithm are in good agreement with those in earlier studies.
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