Calculating Biological Behaviors of Epigenetic States in Phage lambda Life Cycle

Gene regulatory network of lambda phage is one the best studied model systems in molecular biology. More 50 years of experimental study has provided a tremendous amount of data at all levels: physics, chemistry, DNA, protein, and function. However, its stability and robustness for both wild type and mutants has been a notorious theoretical/mathematical problem. In this paper we report our successful calculation on the properties of this gene regulatory network. We believe it is of its first kind. Our success is of course built upon numerous previous theoretical attempts, but following 3 features make our modeling uniqu: 1) A new modeling method particular suitable for stability and robustness study; 2) Paying a close attention to the well-known difference of in vivo and in vitro; 3) Allowing more important role for noise and stochastic effect to play. The last two points have been discussed by two of us (Ao and Yin, cond-mat/0307747), which we believe would be enough to make some of previous theoretical attempts successful, too. We hope the present work would stimulate a further interest in the emerging field of gene regulatory network.Comment: 16 pages, 3 figures, 1 tabl

Lateral shearing interferometry for high-NA EUV wavefront metrology

We present a lateral shearing interferometer suitable for high-NA EUV wavefront metrology. In this interferometer, a geometric model is used to accurately characterize and predict systematic errors that come from performing interferometry at high NA. This interferometer is compatible with various optical geometries, including systems where the image plane is tilted with respect to the optical axis, as in the Berkeley MET5. Simulation results show that the systematic errors in tilted geometries can be reduced by aligning the shearing interferometer grating and detector parallel to the image plane. Subsequent residual errors can be removed by linear fitting

The Vector and Axial-Vector Charmonium-like States

After constructing all the tetraquark interpolating currents with $J^{PC}=1^{-+}, 1^{--}, 1^{++}$ and $1^{+-}$ in a systematic way, we investigate the two-point correlation functions to extract the masses of the charmonium-like states with QCD sum rule. For the $1^{--}$ $qc\bar q\bar c$ charmonium-like state, $m_X=4.6\sim4.7$ GeV, which implies a possible tetraquark interpretation for the state Y(4660). The masses for both the $1^{++}$ $qc\bar q\bar c$ and $sc\bar s\bar c$ charmonium-like states are around $4.0\sim 4.2$ GeV, which are slightly above the mass of X(3872). For the $1^{-+}$ $qc\bar q\bar c$ charmonium-like state, the extracted mass is $4.5\sim 4.7$ GeV. We also discuss the possible decay modes and experimental search of the $1^{-+}$ charmonium-like states.Comment: 18 pages, 6 figures and 6 table

Community detection in multiplex networks using locally adaptive random walks

Multiplex networks, a special type of multilayer networks, are increasingly applied in many domains ranging from social media analytics to biology. A common task in these applications concerns the detection of community structures. Many existing algorithms for community detection in multiplexes attempt to detect communities which are shared by all layers. In this article we propose a community detection algorithm, LART (Locally Adaptive Random Transitions), for the detection of communities that are shared by either some or all the layers in the multiplex. The algorithm is based on a random walk on the multiplex, and the transition probabilities defining the random walk are allowed to depend on the local topological similarity between layers at any given node so as to facilitate the exploration of communities across layers. Based on this random walk, a node dissimilarity measure is derived and nodes are clustered based on this distance in a hierarchical fashion. We present experimental results using networks simulated under various scenarios to showcase the performance of LART in comparison to related community detection algorithms