We present HotKnots, a new heuristic algorithm for the prediction of RNA secondary structures including pseudoknots. Based on the simple idea of iteratively forming stable stems, our algorithm explores many alternative secondary structures, using a free energy minimization algorithm for pseudoknot free secondary structures to identify promising candidate stems. In an empirical evaluation of the algorithm with 43 sequences taken from the Pseudobase database and from the literature on pseudoknotted structures, we found that overall, in terms of the sensitivity and specificity of predictions, HotKnots outperforms the well-known Pseudoknots algorithm of Rivas and Eddy and the NUPACK algorithm of Dirks and Pierce, both based on dynamic programming approaches for limited classes of pseudoknotted structures. It also outperforms the heuristic Iterated Loop Matching algorithm of Ruan and colleagues, and in many cases gives better results than the genetic algorithm from the STAR package of van Batenburg and colleagues and the recent pknotsRG-mfe algorithm of Reeder and Giegerich. The HotKnots algorithm has been implemented in C/C++ and is available from http://www. cs.ubc.ca/labs/beta/Software/HotKnots.
The thickness-dependent electronic states and physical properties of two-dimensional materials suggest great potential applications in electronic and optoelectronic devices. However, the enhanced surface effect in ultra-thin materials might significantly influence the structural stability, as well as the device reliability. Here, we report a spontaneous phase transformation of gallium telluride (GaTe) that occurred when the bulk was exfoliated to a few layers. Transmission electron microscopy (TEM) results indicate a structural variation from a monoclinic to a hexagonal structure. Raman spectra suggest a critical thickness for the structural transformation. First-principle calculations and thermodynamic analysis show that the surface energy and the interlayer interaction compete to dominate structural stability in the thinning process. A two-stage transformation process from monoclinic (m) to tetragonal (T) and then from tetragonal to hexagonal (h) is proposed to understand the phase transformation. The results demonstrate the crucial role of interlayer interactions in the structural stability, which provides a phase engineering strategy for device applications.
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