The secondary structure of the P5abc subdomain (a 56-nt RNA) of the Tetrahymena thermophila group I intron ribozyme has been determined by NMR. Its base pairing in aqueous solution in the absence of magnesium ions is significantly different from the RNA in a crystal but is consistent with thermodynamic predictions. On addition of magnesium ions, the RNA folds into a tertiary structure with grea...

In this paper we study the performance of probabilistic networks in the context of protein sequence analysis in molecular biology. Speci cally, we report the results of our initial experiments applying this framework to the problem of protein secondary structure prediction. One of the main advantages of the probabilistic approach we describe here is our ability to perform detailed experiments w...

In this paper we study the performance of probabilistic networks in the context of protein sequence analysis in molecular biology. Specifically, we report the results of our initial experiments applying this framework to the problem of protein secondary structure prediction. One of the main advantages of the probabilistic approach we describe here is our ability to perform detailed experiments ...

RNAbow diagrams are a versatile tool for visualizing and comparing ensembles of RNA secondary structures. Previously, RNAbows have proved useful when investigating individual ensembles of folds, performing cluster analysis, and identifying conformational changes caused by single nucleotide polymorphisms [Aalberts and Jannen, RNA, 19, 475–478 (2013)]. This contest submission highlights their use...

The biomedical importance of small RNA molecules only continues to grow. Yet, even at this length scale, reliably predicting the native base pairings of an RNA sequence remains a significant open problem in computational molecular biology. We present a novel combinatorial method, RNA profiling, for identifying the most probable combinations of native base pairs across a Boltzmann ensemble of se...

For certain categories of sequences, information from both the past and the future can be used for analysis and predictions at time t. This is the case for biological sequences where the nature and function of a region in a sequence may strongly depend on events located both upstream and downstream. We develop a new family of adaptive graphical model architectures for learning non-causal sequen...

Proteins are linear chain biomolecules composed of 20 different amino acids which form secondary structures such as helixes and loops [8]. Here, we use deep recurrent memory networks and deep convectional networks for predicting secondary structure annotations on sequences from the Uniprot database. We compare different network architectures and memory models, and discuss possible improvements....

We describe a new classifier for protein secondary structure prediction that is formed by cascading together different types of classifiers using neural networks and linear discrimination. The new classifier achieves an accuracy of 76.7% (assessed by a rigorous full Jack-knife procedure) on a new nonredundant dataset of 496 nonhomologous sequences (obtained from G.J. Barton and J.A. Cuff). This...

The range of roles played by structured RNAs in biological systems is vast. At the same time as we are learning more about the importance of RNA structure, recent advances in reagents, methods and technology mean that RNA secondary structural probing has become faster and more accurate. As a result, the capabilities of laboratories that already perform this type of structural analysis have incr...

The secondary structures of the RNAs from the signal recognition particle, termed SRP-RNA, were derived buy comparative analyses of an alignment of 39 sequences. The models are minimal in that only base pairs are included for which there is comparative evidence. The structures represent refinements of earlier versions and include a new short helix.