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pro vyhledávání: '"Heitsch, Christine E."'
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 algorithms are
Externí odkaz:
http://arxiv.org/abs/1801.03055
We analyze the distribution of RNA secondary structures given by the Knudsen-Hein stochastic context-free grammar used in the prediction program Pfold. We prove that the distribution of base pairs, helices and various types of loops in RNA secondary
Externí odkaz:
http://arxiv.org/abs/1204.3670
Autor:
Cooper, Joshua, Heitsch, Christine E.
The skew of a binary string is the difference between the number of zeroes and the number of ones, while the length of the string is the sum of these two numbers. We consider certain suffixes of the lexicographically-least de Bruijn sequence at natur
Externí odkaz:
http://arxiv.org/abs/1003.5939
Autor:
Hower, Valerie, Heitsch, Christine E.
We extend recent methods for parametric sequence alignment to the parameter space for scoring RNA folds. This involves the construction of an RNA polytope. A vertex of this polytope corresponds to RNA secondary structures with common branching. We us
Externí odkaz:
http://arxiv.org/abs/0904.3700
Autor:
Bakhtin, Yuri, Heitsch, Christine E.
We give a Large Deviation Principle (LDP) with explicit rate function for the distribution of vertex degrees in plane trees, a combinatorial model of RNA secondary structures. We calculate the typical degree distributions based on nearest neighbor fr
Externí odkaz:
http://arxiv.org/abs/0803.3990
Autor:
Cooper, Joshua, Heitsch, Christine E.
Publikováno v:
In Advances in Applied Mathematics April 2013 50(4):465-473
Autor:
Zeng, Yingying, Larson, Steven B., Heitsch, Christine E., McPherson, Alexander, Harvey, Stephen C.
Publikováno v:
In Journal of Structural Biology October 2012 180(1):110-116
Akademický článek
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Autor:
Heitsch, Christine E., Tetali, Prasad
Publikováno v:
Discrete Mathematics & Theoretical Computer Science.
We consider a Markov chain Monte Carlo approach to the uniform sampling of meanders. Combinatorially, a meander $M = [A:B]$ is formed by two noncrossing perfect matchings, above $A$ and below $B$ the same endpoints, which form a single closed loop. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fd590dcd8f840e6c409e5f4e6de6daa
https://doi.org/10.46298/dmtcs.2926
https://doi.org/10.46298/dmtcs.2926