Elastic property of single double-stranded DNA molecules: Theoretical study and comparison with experiments

This paper aims at a comprehensive understanding on the novel elastic property of double-stranded DNA (dsDNA) discovered very recently through single-molecule manipulation techniques. A general elastic model for double-stranded biopolymers is proposed and a new structural parameter called the folding angle $\phi$ is introduced to characterize their deformations. The mechanical property of long dsDNA molecules is then studied based on this model, where the base-stacking interactions between DNA adjacent nucleotide basepairs, the steric effects of basepairs, and the electrostatic interactions along DNA backbones are taken into account. Quantitative results are obtained by using path integral method, and excellent agreement between theory and the observations reported by five major experimental groups are attained. The strong intensity of the base-stacking interactions ensures the structural stability of DNA, while the short-ranged nature of such interactions makes externally-stimulated large structural fluctuations possible. The entropic elasticity, highly extensibility, and supercoiling property of DNA are all closely related to this account. The present work also suggests the possibility that negative torque can induce structural transitions in highly extended DNA from right-handed B-form to left-handed configurations similar with Z-form configuration. Some formulae concerned with the application of path integral method to polymeric systems are listed in the Appendix.Comment: 19 pages in latex format, including 7 EPS figures and 1 table. Submitted to PR

Entropic Elasticity, Cooperative Extensibility and Supercoiling Property of DNA: A Unified Viewpoint

A unified model is constructed to study the recently observed DNA entropic elasticity, cooperative extensibility, and supercoiling property. With the introduction of a new structural parameter (the folding angle $\phi$), bending deformations of sugar-phosphate backbones, steric effects of nucleotide basepairs, and short-range basestacking interactions are considered. The comprehensive agreement of theoretical results with experimental observations on both torsionally relaxed and negatively supercoiled DNAs strongly indicates that, basestacking interactions, although short-ranged in nature, dominate the elasticity of DNA and hence are of vital biological significance.Comment: 4 pages in Latex format, with 3 EPS figures included. A typographic mistake in Eq. (7) is corrected in this version. A slightly different version of this paper will appear in PR

Maximum matching on random graphs

The maximum matching problem on random graphs is studied analytically by the cavity method of statistical physics. When the average vertex degree \mth{c} is larger than \mth{2.7183}, groups of max-matching patterns which differ greatly from each other {\em gradually} emerge. An analytical expression for the max-matching size is also obtained, which agrees well with computer simulations. Discussion is made on this {\em continuous} glassy phase transition and the absence of such a glassy phase in the related minimum vertex covering problem.Comment: 7 pages with 2 eps figures included. Use EPL style. Submitted to Europhysics Letter

Nonequilibrium work equalities in isolated quantum systems

We briefly introduce the quantum Jarzynski and Bochkov-Kuzovlev equalities in isolated quantum Hamiltonian systems, which includes the origin of the equalities, their derivations using a quantum Feynman-Kac formula, the quantum Crooks equality, the evolution equations governing the characteristic functions of the probability density functions for the quantum work, the recent experimental verifications. Some results are given here first time. We particularly emphasize the formally structural consistence between these quantum equalities and their classical counterparts, which shall be useful in understanding the existing equalities and pursuing new fluctuation relations in other complex quantum systems.Comment: 1 figur

Can pulling cause right- to left-handed structural transitions in negatively supercoiled DNA double-helix?

The folding angle distribution of stretched and negatively supercoiled DNA double-helix is investigated based on a theoretical model we proposed earlier [H. Zhou et al., Phys. Rev. Lett. 82, 4560 (1999)]. It is shown that pulling can transit a negatively supercoiled DNA double-helix from the right-handed B-form to a left-handed configuration which resembles DNA Z-form in some important respects. The energetics of this possible transition is calculated and the comparison with recent experimental observations are qualitatively discussed.Comment: 3 pages. A new paragraph as well as two figures are added in the revised paper. A new reference (Ref. 7) is include

Prediction analysis for microbiome sequencing data

One primary goal of human microbiome studies is to predict host traits based on human microbiota. However, microbial community sequencing data present significant challenges to the development of statistical methods. In particular, the samples have different library sizes, the data contain many zeros and are often over-dispersed. To address these challenges, we introduce a new statistical framework, called predictive analysis in metagenomics via inverse regression (PAMIR). An inverse regression model is developed for over-dispersed microbiota counts given the trait, and then a prediction rule is constructed by taking advantage of the dimension-reduction structure in the model. An efficient Monte Carlo expectation-maximization algorithm is designed for carrying out maximum likelihood estimation. We demonstrate the advantages of PAMIR through simulations and a real data example

Attributes Coupling based Item Enhanced Matrix Factorization Technique for Recommender Systems

Recommender system has attracted lots of attentions since it helps users alleviate the information overload problem. Matrix factorization technique is one of the most widely employed collaborative filtering techniques in the research of recommender systems due to its effectiveness and efficiency in dealing with very large user-item rating matrices. Recently, based on the intuition that additional information provides useful insights for matrix factorization techniques, several recommendation algorithms have utilized additional information to improve the performance of matrix factorization methods. However, the majority focus on dealing with the cold start user problem and ignore the cold start item problem. In addition, there are few suitable similarity measures for these content enhanced matrix factorization approaches to compute the similarity between categorical items. In this paper, we propose attributes coupling based item enhanced matrix factorization method by incorporating item attribute information into matrix factorization technique as well as adapting the coupled object similarity to capture the relationship between items. Item attribute information is formed as an item relationship regularization term to regularize the process of matrix factorization. Specifically, the similarity between items is measured by the Coupled Object Similarity considering coupling between items. Experimental results on two real data sets show that our proposed method outperforms state-of-the-art recommendation algorithms and can effectively cope with the cold start item problem when more item attribute information is available.Comment: 15 page

Bell Rate Model with Dynamic Disorder: Model and Its Application in the Receptor-ligand Forced Dissociation Experiments

We extend the Bell forced dissociation rate model to take account into dynamic disorder. The motivation of the present work is from the recent forced dissociation experiments of the adhesive receptor-ligand complexes, in which some complexes were found to increase their mean lifetimes (catch bonds) when they are stretched by mechanical force, while the force increases beyond some thresholds their lifetimes decrease (slip bonds). Different from our previous model of force modulating dynamic disorder, in present work we allow that the projection of force onto the direction from the bound to the transition state of complex could be negative. Our quantitative description is based on a one-dimension diffusion-assisted reaction model. We find that, although the model can well describe the catch-slip transitions observed in the single bond P-selctin glycoprotein ligand 1(PSGL-1)-P- and L-selectin forced dissociation experiments, it might be physically unacceptable because the model predicts a slip-catch bond transitions when the conformational diffusion coefficient tends to zero.Comment: 9 pages, 6 figure

Transceiver Design for Multi-user Multi-antenna Two-way Relay Cellular Systems

In this paper, we design interference free transceivers for multi-user two-way relay systems, where a multi-antenna base station (BS) simultaneously exchanges information with multiple single-antenna users via a multi-antenna amplify-and-forward relay station (RS). To offer a performance benchmark and provide useful insight into the transceiver structure, we employ alternating optimization to find optimal transceivers at the BS and RS that maximizes the bidirectional sum rate. We then propose a low complexity scheme, where the BS transceiver is the zero-forcing precoder and detector, and the RS transceiver is designed to balance the uplink and downlink sum rates. Simulation results demonstrate that the proposed scheme is superior to the existing zero forcing and signal alignment schemes, and the performance gap between the proposed scheme and the alternating optimization is minor.Comment: 11 pages, 9 figures, 2 tables, accepted by IEEE Trans. on Commu

On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data

In this paper, we first propose a Bayesian neighborhood selection method to estimate Gaussian Graphical Models (GGMs). We show the graph selection consistency of this method in the sense that the posterior probability of the true model converges to one. When there are multiple groups of data available, instead of estimating the networks independently for each group, joint estimation of the networks may utilize the shared information among groups and lead to improved estimation for each individual network. Our method is extended to jointly estimate GGMs in multiple groups of data with complex structures, including spatial data, temporal data and data with both spatial and temporal structures. Markov random field (MRF) models are used to efficiently incorporate the complex data structures. We develop and implement an efficient algorithm for statistical inference that enables parallel computing. Simulation studies suggest that our approach achieves better accuracy in network estimation compared with methods not incorporating spatial and temporal dependencies when there are shared structures among the networks, and that it performs comparably well otherwise. Finally, we illustrate our method using the human brain gene expression microarray dataset, where the expression levels of genes are measured in different brain regions across multiple time periods