RNA folding at elementary step resolution

Non protein-coding RNAs (ncRNAs) are a research hotspot in bioinformatics. Recent discoveries have revealed new ncRNA families performing a variety of roles, from gene expression regulation to catalytic activities. It is also believed that other families are still to be unveiled. Computational methods developed for protein coding genes often fail when searching for ncRNAs. Noncoding RNAs functionality is often heavily dependent on their secondary structure, which makes gene discovery very different from protein coding RNA genes. This motivated the development of specific methods for ncRNA research. This article reviews the main approaches used to identify ncRNAs and predict secondary structure.

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“…This strategy is adopted in Kinfold [43], which models RNA folding as a Markov process in the folding space.…”

Section: Kinetic Foldingmentioning

confidence: 99%

Computational methods in noncoding RNA research

2007

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“…In order to connect our present discussion with earlier work, in particular (Flamm et al 2000(Flamm et al , 2002Wolfinger et al 2004), we briefly discuss the notation of saddle points in the context of our present formalism.…”

Section: Definition 10mentioning

confidence: 93%

“…The valley G corresponds to the entire landscape A detailed investigation of the relationships between the valley structure of the landscape and the basins and barriers of the landscape discussed in earlier work (Flamm et al 2000(Flamm et al , 2002(Flamm et al , 2007Wolfinger et al 2004) goes beyond the scope of this contribution. These connections will be explored in a forthcoming contribution.…”

Section: Definition 10mentioning

confidence: 97%

“…5. We remark, finally, that the flooding algorithm implemented in the barriers program (Flamm et al 2000(Flamm et al , 2002 identifies saddle points as the lowest energy points that have neighbors with lower energy that are connected by means of gradient descent walks to local minima in two distinct valleys. This is equivalent to the existence of two adaptive walks starting at the saddle points that terminate in the same local minima.…”

Section: Definition 10mentioning

confidence: 99%

“…This construction was introduced more or less independently in several different application domains, see e.g. (Klotz and Kobe 1994;Becker and Karplus 1997;Garstecki et al 1999;Wales et al 1998;Doye et al 1999;Flamm et al 2000;Prügel-Bennett and Hallam 2005).…”

Section: Introductionmentioning

confidence: 99%

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Combinatorial vector fields and the valley structure of fitness landscapes

Stadler

2010

J. Math. Biol.

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Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

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