Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A new approach for detecting riboswitches in DNA sequences.

ABSTRACT: Riboswitches are short sequences of messenger RNA that can change their structural conformation to regulate the expression of adjacent genes. Computational prediction of putative riboswitches can provide direction to molecular biologists studying riboswitch-mediated gene expression.The Denison Riboswitch Detector (DRD) is a new computational tool with a Web interface that can quickly identify putative riboswitches in DNA sequences on the scale of bacterial genomes. Riboswitch descriptions are easily modifiable and new ones are easily created. The underlying algorithm converts the problem to a 'heaviest path' problem on a multipartite graph, which is then solved using efficient dynamic programming. We show that DRD can achieve ? 88-99% sensitivity and >99.99% specificity on 13 riboswitch families.DRD is available at http://drd.denison.edu.

SUBMITTER: Havill JT

PROVIDER: S-EPMC4609007 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A new approach for detecting riboswitches in DNA sequences.

Havill Jessen T JT Bhatiya Chinmoy C Johnson Steven M SM Sheets Joseph D JD Thompson Jeffrey S JS

Bioinformatics (Oxford, England) 20140711 21

<h4>Motivation</h4>Riboswitches are short sequences of messenger RNA that can change their structural conformation to regulate the expression of adjacent genes. Computational prediction of putative riboswitches can provide direction to molecular biologists studying riboswitch-mediated gene expression.<h4>Results</h4>The Denison Riboswitch Detector (DRD) is a new computational tool with a Web interface that can quickly identify putative riboswitches in DNA sequences on the scale of bacterial geno ...[more]

PMID: 25015992

Similar Datasets

Development of a new sequential block finding strategy for detection of conserved sequences in riboswitches.

Project description:Introduction: Some non-coding RNAs have an important role in the regulation of gene expression and consequently cellular function. Riboswitches are examples of these regulatory RNAs. Riboswitches are classified into various families according to sequential and structural similarities. Methods: In this study, a block finder algorithm for identification of frequently appearing sequential blocks in five families of riboswitches from Rfam 12.0 database, without the use of alignment methods, was developed. Results: The developed program identified 21 frequently appearing blocks in five families of riboswitches. Conclusion: Comparison of the results of the proposed algorithm with those of sequential alignment methods revealed that our method can recognize most of the patterns present in conserved areas of individual riboswitch families and determine them as specific blocks, implying potential of the developed program as a platform for further studies and developments.

| S-EPMC5915704 | biostudies-literature

Pulse Detecting Genetic Circuit - A New Design Approach.

Project description:A robust cellular counter could enable synthetic biologists to design complex circuits with diverse behaviors. The existing synthetic-biological counters, responsive to the beginning of the pulse, are sensitive to the pulse duration. Here we present a pulse detecting circuit that responds only at the falling edge of a pulse-analogous to negative edge triggered electric circuits. As biological events do not follow precise timing, use of such a pulse detector would enable the design of robust asynchronous counters which can count the completion of events. This transcription-based pulse detecting circuit depends on the interaction of two co-expressed lambdoid phage-derived proteins: the first is unstable and inhibits the regulatory activity of the second, stable protein. At the end of the pulse the unstable inhibitor protein disappears from the cell and the second protein triggers the recording of the event completion. Using stochastic simulation we showed that the proposed design can detect the completion of the pulse irrespective to the pulse duration. In our simulation we also showed that fusing the pulse detector with a phage lambda memory element we can construct a counter which can be extended to count larger numbers. The proposed design principle is a new control mechanism for synthetic biology which can be integrated in different circuits for identifying the completion of an event.

| S-EPMC5131961 | biostudies-literature

Evaluation of methods for detecting recombination from DNA sequences: computer simulations.

Project description:Recombination is a key evolutionary process that shapes the architecture of genomes and the genetic structure of populations. Although many statistical methods are available for the detection of recombination from DNA sequences, their absolute and relative performance is still unknown. Here we evaluated the performance of 14 different recombination detection algorithms. We used the coalescent with recombination to simulate DNA sequences with different levels of recombination, genetic diversity, and rate variation among sites. Recombination detection methods were applied to these data sets, and whether they detected or not recombination was recorded. Different recombination methods showed distinct performance depending on the amount of recombination, genetic diversity, and rate variation among sites. The model of nucleotide substitution under which the data were generated did not seem to have a significant effect. Most methods increase power with more sequence divergence. In general, recombination detection methods seem to capture the presence of recombination, but they are not very powerful. Methods that use substitution patterns or incompatibility among sites were more powerful than methods based on phylogenetic incongruence. Most methods do not seem to infer more false positives than expected by chance. Especially depending on the amount of diversity in the data, different methods could be used to attain maximum power while minimizing false positives. Results shown here will provide some guidance in the selection of the most appropriate method/s for the analysis of the particular data at hand.

| S-EPMC61114 | biostudies-literature

Applicability of a computational design approach for synthetic riboswitches.

Project description:Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand-dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer structures not corresponding to the calculated MFE state.

| S-EPMC5397205 | biostudies-literature

Detecting change in stochastic sound sequences.

Project description:Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance). In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG) responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.

| S-EPMC5993325 | biostudies-literature

A new approach for detecting low-level mutations in next-generation sequence data.

Project description:We propose a new method that incorporates population re-sequencing data, distribution of reads, and strand bias in detecting low-level mutations. The method can accurately identify low-level mutations down to a level of 2.3%, with an average coverage of 500×, and with a false discovery rate of less than 1%. In addition, we also discuss other problems in detecting low-level mutations, including chimeric reads and sample cross-contamination, and provide possible solutions to them.

| S-EPMC3446287 | biostudies-literature

RandAL: a randomized approach to aligning DNA sequences to reference genomes.

Project description:BACKGROUND: The alignment of short reads generated by next-generation sequencers to genomes is an important problem in many biomedical and bioinformatics applications. Although many proposed methods work very well on narrow ranges of read lengths, they tend to suffer in performance and alignment quality for reads outside of these ranges. RESULTS: We introduce RandAL, a novel method that aligns DNA sequences to reference genomes. Our approach utilizes two FM indices to facilitate efficient bidirectional searching, a pruning heuristic to speed up the computing of edit distances, and most importantly, a randomized strategy that enables effective estimation of key parameters. Extensive comparisons showed that RandAL outperformed popular aligners in most instances and was unique in its consistent and accurate performance over a wide range of read lengths and error rates. The software package is publicly available at https://github.com/namsyvo/RandAL. CONCLUSIONS: RandAL promises to align effectively and accurately short reads that come from a variety of technologies with different read lengths and rates of sequencing error.

| S-EPMC4120144 | biostudies-literature

An Eulerian path approach to local multiple alignment for DNA sequences.

Project description:Expensive computation in handling a large number of sequences limits the application of local multiple sequence alignment. We present an Eulerian path approach to local multiple alignment for DNA sequences. The computational time and memory usage of this approach is approximately linear to the total size of sequences analyzed; hence, it can handle thousands of sequences or millions of letters simultaneously. By constructing a De Bruijn graph, most of the conserved segments are amplified as heavy Eulerian paths in the graph, and the original patterns distributed in sequences are recovered even if they do not exist in any single sequence. This approach can accurately detect unknown conserved regions, for both short and long, conserved and degenerate patterns. We further present a Poisson heuristic to estimate the significance of a local multiple alignment. The performance of our method is demonstrated by finding Alu repeats in the human genome. We compare the results with Alus marked by repeatmasker, where the two programs are in good agreement. Our method is robust under various conditions and superior to other methods in terms of efficiency and accuracy.

| S-EPMC547885 | biostudies-literature

Detecting overlapping coding sequences in virus genomes.

Project description:BACKGROUND: Detecting new coding sequences (CDSs) in viral genomes can be difficult for several reasons. The typically compact genomes often contain a number of overlapping coding and non-coding functional elements, which can result in unusual patterns of codon usage; conservation between related sequences can be difficult to interpret--especially within overlapping genes; and viruses often employ non-canonical translational mechanisms--e.g. frameshifting, stop codon read-through, leaky-scanning and internal ribosome entry sites--which can conceal potentially coding open reading frames (ORFs). RESULTS: In a previous paper we introduced a new statistic--MLOGD (Maximum Likelihood Overlapping Gene Detector)--for detecting and analysing overlapping CDSs. Here we present (a) an improved MLOGD statistic, (b) a greatly extended suite of software using MLOGD, (c) a database of results for 640 virus sequence alignments, and (d) a web-interface to the software and database. Tests show that, from an alignment with just 20 mutations, MLOGD can discriminate non-overlapping CDSs from non-coding ORFs with a typical accuracy of up to 98%, and can detect CDSs overlapping known CDSs with a typical accuracy of 90%. In addition, the software produces a variety of statistics and graphics, useful for analysing an input multiple sequence alignment. CONCLUSION: MLOGD is an easy-to-use tool for virus genome annotation, detecting new CDSs--in particular overlapping or short CDSs--and for analysing overlapping CDSs following frameshift sites. The software, web-server, database and supplementary material are available at http://guinevere.otago.ac.nz/mlogd.html.

| S-EPMC1395342 | biostudies-literature

Detecting long tandem duplications in genomic sequences.

Project description:BackgroundDetecting duplication segments within completely sequenced genomes provides valuable information to address genome evolution and in particular the important question of the emergence of novel functions. The usual approach to gene duplication detection, based on all-pairs protein gene comparisons, provides only a restricted view of duplication.ResultsIn this paper, we introduce ReD Tandem, a software using a flow based chaining algorithm targeted at detecting tandem duplication arrays of moderate to longer length regions, with possibly locally weak similarities, directly at the DNA level. On the A. thaliana genome, using a reference set of tandem duplicated genes built using TAIR,(a) we show that ReD Tandem is able to predict a large fraction of recently duplicated genes (dS ?<? 1) and that it is also able to predict tandem duplications involving non coding elements such as pseudo-genes or RNA genes.ConclusionsReD Tandem allows to identify large tandem duplications without any annotation, leading to agnostic identification of tandem duplications. This approach nicely complements the usual protein gene based which ignores duplications involving non coding regions. It is however inherently restricted to relatively recent duplications. By recovering otherwise ignored events, ReD Tandem gives a more comprehensive view of existing evolutionary processes and may also allow to improve existing annotations.

| S-EPMC3464658 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data