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Related papers: A steepest descent calculation of RNA pseudoknots

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We investigate the topology of a double cover of a complex affine plane branching along a nodal real line arrangement. We define certain topological 2-cycles in the double plane using the real structure of the arrangement, and calculate…

Algebraic Geometry · Mathematics 2025-05-06 Ichiro Shimada

We examine the conformations of a model for a short segment of closed DNA. The molecule is represented as a cylindrically symmetric elastic rod with a constraint corresponding to a specification of the linking number. We obtain analytic…

Soft Condensed Matter · Physics 2009-10-31 Boris Fain , Joseph Rudnick

In this paper we use complex techniques to study the structure of real Henon diffeomorphisms of maximal topological entropy.

Dynamical Systems · Mathematics 2007-05-23 Eric Bedford , John Smillie

The representation of a biochemical network as a graph is the coarsest level of description in cellular biochemistry. By studying the network structure one can draw conclusions on the large scale organisation of the biochemical processes.…

Molecular Networks · Quantitative Biology 2007-05-23 Petter Holme , Mikael Huss

The Nystr\"om method is a popular choice for finding a low-rank approximation to a symmetric positive semi-definite matrix. The method can fail when applied to symmetric indefinite matrices, for which the error can be unboundedly large. In…

Numerical Analysis · Mathematics 2023-10-10 Taejun Park , Yuji Nakatsukasa

Topological entanglements are abundant, and often detrimental, in polymeric systems in biology and materials science. Here we theoretically investigate the topological simplification of knots by diffusing slip-links (SLs), which may…

Soft Condensed Matter · Physics 2020-11-02 Andrea Bonato , Davide Marenduzzo , Davide Michieletto

We develop a theoretical description of the topological disentanglement occurring when torus knots reach the ends of a semi-flexible polymer under tension. These include decays into simpler knots and total unknotting. The minimal number of…

Statistical Mechanics · Physics 2020-11-04 Michele Caraglio , Boris Marcone , Fulvio Baldovin , Enzo Orlandini , Attilio L. Stella

A growing number of RNA sequences are now known to have distributions of multiple stable sequences. Recent algorithms use the list of nucleotides in a sequence and auxiliary experimental data to predict such distributions. Although the…

Combinatorics · Mathematics 2020-09-14 Torin Greenwood , Christine E. Heitsch

Single-cell RNA sequencing (scRNA-seq) is a relatively new technology that has stimulated enormous interest in statistics, data science, and computational biology due to the high dimensionality, complexity, and large scale associated with…

Machine Learning · Statistics 2023-10-25 Yuta Hozumi , Guo-Wei Wei

Doubly periodic tangles (DP tangles) are configurations of curves embedded in the thickened plane, invariant under translations in two transversal directions. In this paper we extend the classical theory of DP tangles by introducing the…

Geometric Topology · Mathematics 2025-08-20 Ioannis Diamantis , Sofia Lambropoulou , Sonia Mahmoudi

In the framework of the Relativistic Mean Field Approach a pseudospin dependence of the residual forces in nuclei is considered. It is shown that this dependence is relatively weak. As a consequence, a pseudospin dependence of the…

Nuclear Theory · Physics 2008-11-26 R. V. Jolos , V. V. Voronov

We introduce a novel fully convolutional neural network (FCN) architecture for predicting the secondary structure of ribonucleic acid (RNA) molecules. Interpreting RNA structures as weighted graphs, we employ deep learning to estimate the…

Biomolecules · Quantitative Biology 2024-06-07 Marc Harary , Chengxin Zhang

We modify and extend the recently developed statistical mechanical model for predicting the thermodynamic properties of chain molecules having noncovalent double-stranded conformations, as in RNA or ssDNA, and $\beta-$sheets in protein, by…

Soft Condensed Matter · Physics 2009-11-07 Fei Liu , Luru Dai , Zhong-can Ou-Yang

We extend an hypergraph representation, introduced by Finkelstein and Roytberg, to unify dynamic programming algorithms in the context of RNA folding with pseudoknots. Classic applications of RNA dynamic programming energy minimization,…

Quantitative Methods · Quantitative Biology 2011-06-21 Yann Ponty , Cédric Saule

Kernel methods are used frequently in various applications of machine learning. For large-scale high dimensional applications, the success of kernel methods hinges on the ability to operate certain large dense kernel matrix K. An enormous…

Numerical Analysis · Mathematics 2021-12-30 Difeng Cai , James Nagy , Yuanzhe Xi

Networks are ubiquitous structure that describes complex relationships between different entities in the real world. As a critical component of prediction task over nodes in networks, learning the feature representation of nodes has become…

Machine Learning · Computer Science 2018-09-10 Hansheng Xue , Jiajie Peng , Xuequn Shang

Following our previous study of the recursive structure of Baikov representations, we discuss its application in the integration-by-parts reduction of Feynman integrals. We combine the top-down reduction approach with the recursive…

High Energy Physics - Phenomenology · Physics 2024-04-25 Xuhang Jiang , Ming Lian , Li Lin Yang

Models for RNA secondary structures (the topology of folded RNA) without pseudo knots are disordered systems with a complex state-space below a critical temperature. Hence, a complex dynamical (glassy) behavior can be expected, when…

Disordered Systems and Neural Networks · Physics 2008-02-02 S. Wolfsheimer , B. Burghardt , A. Mann , A. K. Hartmann

RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures using…

Biomolecules · Quantitative Biology 2020-01-10 Liang Zhang , He Zhang , David H. Mathews , Liang Huang

Neutron star crusts are studied using a classical molecular dynamics model developed for heavy ion reactions. After the model is shown to produce a plethora of the so-called "pasta" shapes, a series of techniques borrowed from nuclear…

Nuclear Theory · Physics 2015-06-11 C. O. Dorso , P. A. Giménez Molinelli , J. A. López
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