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Complete probabilistic analysis of RNA shapes
2006
BMC Biology
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From these results, and the fact that we use a complete and exact analysis of the folding space, we conclude that this approach opens up new and promising routes for investigating and understanding RNA ...
An in-depth analysis of the folding space as a whole appeared necessary to deduce the structural properties of a given RNA molecule reliably. ...
Acknowledgements The authors thank an anonymous reviewer for pointing out the mathematical reason for the sequence length independence of the sample size M. ...
doi:10.1186/1741-7007-4-5
pmid:16480488
pmcid:PMC1479382
fatcat:m4n2c6ltazgdxlhait6bn7qmxy
Probabilistic Methods in Cancer Biology
2011
European Journal of Control
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gene regulatory networks, analyzing the significance of expression levels for collections of genes, and discriminating between drivers (mutations that cause cancer) and passengers (mutations that are ...
For persons trained in control theory, there is now a significant opportunity to work with biologists to create a virtuous cycle of hypothesis generation and experimental validation. ...
I would also like to thank Tamer Başar, Aniruddha Datta, Vibhav Gogate, Steve Marcus and Roberto Tempo for ...
doi:10.3166/ejc.17.483-511
fatcat:rqvf2p6xrbc7da5jmt3kss3owe
Probabilistic analysis of the human transcriptome with side information
[article]
2011
arXiv
pre-print
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Statistical learning and probabilistic models provide a natural framework for such modeling tasks. ...
The key contributions of the thesis are general exploratory tools for high-throughput data analysis that have provided new insights to cell-biological networks, cancer mechanisms and other aspects of genome ...
, ribosomal RNA and transfer-RNA molecules (Carninci, 2009; Johnson et al., 2005) . ...
arXiv:1102.5509v1
fatcat:zlwxrob7c5hapgje2v2tstx6uy
Probabilistic and Flux Landscapes of the Phage λ Genetic Switch
[article]
2012
arXiv
pre-print
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In this work, a dynamical model of the non-equilibrium statistical mechanics is revisited and generalized. ...
To this end, general integral forms for advection-diffusion equations have been developed and numerically solved for a variety of mutants and assumptions about the state of the cells. ...
Mistake, seemed to have already been taken, though time has now evolved sufficiently long to have absorbed enough contribution from elsewhere to break this continuity sufficiently to warrant a new name and ...
arXiv:1204.1953v1
fatcat:do4vjinaojadphxoe3vowb54oe
Evaluation of a sophisticated SCFG design for RNA secondary structure prediction
2011
Theory in biosciences
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on probabilistic RNA models. ...
relevant for biologists) yield the conclusion that the Boltzmann distribution of the PF sampling approach is more centered than the ensemble distribution induced by the sophisticated SCFG model, which ...
Acknowledgements The authors wish to thank two anonymous reviewers for their careful and helpful remarks and suggestions made for a previous version of this article. ...
doi:10.1007/s12064-011-0139-7
pmid:22135038
fatcat:a7p4b62w4nedxewvuuranz5r2q
MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts
2022
BMC Bioinformatics
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Consequently, reads from total-RNA-seq libraries may cause ambiguous genomic alignments, demanding for flexible quantification approaches. ...
Results Here we present Multi-Graph count (MGcount), a total-RNA-seq quantification tool combining two strategies for handling ambiguous alignments. ...
Acknowledgements We would like to thank Professor Martin Simon for contributing to the improvement of our work with interesting discussions on small-RNA-seq and for providing with the mouse liver and nematode ...
doi:10.1186/s12859-021-04544-3
pmid:35030988
pmcid:PMC8760670
fatcat:akduthfdtfdwbnzplilphpvday
Identifying differentially expressed transcripts from RNA-seq data with biological variation
2012
Computer applications in the biosciences : CABIOS
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The analysis of transcriptome expression levels and differential expression estimation requires a probabilistic approach to properly account for ambiguity caused by shared exons and finite read sampling ...
We demonstrate the advantages of our method using simulated data as well as an RNA-seq dataset with technical and biological replication for both studied conditions. ...
Graphical representation of the RNA-seq data probabilistic model. ...
doi:10.1093/bioinformatics/bts260
pmid:22563066
pmcid:PMC3381971
fatcat:awexp7n36fcbhgnkb5f2cht2ni
Research on folding diversity in statistical learning methods for RNA secondary structure prediction
2018
International Journal of Biological Sciences
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The existing prediction methods for a single sequence do not fully consider the folding diversity which may occur among RNAs with different functions or sources. ...
This paper explores the relationship between folding diversity and prediction accuracy, and puts forward a new method to improve the prediction accuracy of RNA secondary structure. ...
energy on structure and fits the nested branching structure of RNA molecules. ...
doi:10.7150/ijbs.24595
pmid:29989089
pmcid:PMC6036747
fatcat:kzyc7yxkdjb7tgtvvg7h7h3opu
Self-organization versus Watchmaker: ambiguity of molecular recognition and design charts of cellular circuitry
2007
Journal of Molecular Recognition
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pathways are inherently probabilistic, ambiguous, and context-dependent. ...
usefulness of the mechanistic assumptions and inferences embodied in the design charts of cellular circuitry. ...
Veronica Galvan (Buck Institute) for critical reading of the manuscript and Dr. Dale E. Bredesen (Buck Institute) for support and encouragement. ...
doi:10.1002/jmr.839
pmid:17847050
fatcat:ypynzncp7ndyfobdwaif6yslca
Bioinformatics---an introduction for computer scientists
2004
ACM Computing Surveys
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The topics covered include: descriptions of the current software especially developed for biologists, computer and mathematical cell models, and areas of computer science that play an important role in ...
The underlying motivation for many of the bioinformatics approaches is the evolution of organisms and the complexity of working with incomplete and noisy data. ...
ACKNOWLEDGMENTS The author wishes to express his gratitude to Mark Gerstein, Nathan Goodman and the reviewers who provided many suggestions to improve the original manuscript. ...
doi:10.1145/1031120.1031122
fatcat:i5au72xpujffrgryx3vnyiyeyy
Large-scale allosteric switch in the 7SK RNA regulates transcription in response to growth and stress
[article]
2021
bioRxiv
pre-print
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as a powerful strategy for comprehensively defining RNA structure and dynamics in cells. ...
) direct base pairing interactions, and (iii) tertiary and higher-order interactions for each conformation of multi-state RNA structural ensembles, all from a single experiment. ...
Acknowledgements We thank Khoa Dhoa (Baylor College of Medicine, BCM) for exploratory analyses, and Calla Olson (BCM), Kristen Karlin (BCM), and David Price (University of Iowa) for helpful discussions ...
doi:10.1101/2021.09.16.460563
fatcat:3blpx5jefjhsvhpkmu3azv7sly
Evaluating the effect of disturbed ensemble distributions on SCFG based statistical sampling of RNA secondary structures
2012
BMC Bioinformatics
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Recently, a novel probabilistic method for the prediction of RNA secondary structures from a single sequence has been studied which is based on generating statistically representative and reproducible ...
The key results of this paper are crucial for the design of an efficient and competitive heuristic prediction method based on the increasingly accepted and attractive statistical sampling approach. ...
All authors wish to thank an anonymous reviewer for careful reading and helpful remarks and suggestions made for a previous version of this article. ...
doi:10.1186/1471-2105-13-159
pmid:22776037
pmcid:PMC3871765
fatcat:jxixc6iyqngovhlvxcnyakdxom
Knotify: An Efficient Parallel Platform for RNA Pseudoknot Prediction Using Syntactic Pattern Recognition
2022
Methods and Protocols
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Obtaining valuable clues for noncoding RNA (ribonucleic acid) subsequences remains a significant challenge, acknowledging that most of the human genome transcribes into noncoding RNA parts related to unknown ...
The methodology achieved a F1-score equal to 0.774 and MCC equal 0.543 in discovering all the stems of an RNA sequence, outperforming the particular task. ...
Thermodynamic methods incorporate a biologically oriented, energy-driven model for RNA folding and obtain their parameters from experiments on specific short RNA molecules. ...
doi:10.3390/mps5010014
pmid:35200530
pmcid:PMC8876629
fatcat:ao2zvmqlrfc2dkhbljheqyweoa
The emerging role of physical modeling in the future of structure determination
[article]
2017
bioRxiv
pre-print
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However, recent efforts to model conformational ensembles and to make sense of sparse, ambiguous, and noisy data have revealed the value of detailed, quantitative physical models in structure determination ...
We review these two key challenges, describe different approaches to physical modeling in structure determination, and illustrate several successes and emerging technologies enabled by physical modeling ...
Acknowledgements This work was supported by funding from the Natural Sciences and Engineering Research Council of Canada. JLM is a Tier 2 Canada Research Chair. ...
doi:10.1101/228247
fatcat:yqxphotgvngwpapl4xsqx6esz4
Predictions of RNA secondary structure by combining homologous sequence information
2009
Computer applications in the biosciences : CABIOS
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Results: In this article, we propose a new method for secondary structure predictions of individual RNA sequences by taking the information of their homologous sequences into account without assuming the ...
In our computational experiments, the proposed method provides better predictions than those performed only on the basis of the formation of individual RNA sequences and those performed by using methods ...
Carvalho and C. E. Lawrence for valuable comments. The authors are also grateful to our colleagues at the Computational Biology Research Center (CBRC) for fruitful discussions. ...
doi:10.1093/bioinformatics/btp228
pmid:19478007
pmcid:PMC2687982
fatcat:bx56bl5gtrd5zodipfxeg6yubi
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