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Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler
2008
Journal of Molecular Graphics and Modelling
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Here we present algorithms for automating or assisting many of the steps that are involved in creating RNA structures from building blocks: (1) assembling building blocks into nanostructures using either ...
We show several examples of how the algorithms can be utilized to generate RNA tecto-shapes. ...
This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. ...
doi:10.1016/j.jmgm.2008.05.004
pmid:18838281
pmcid:PMC3744370
fatcat:jodndgepyvhkxp6oolscuzh2ri
From consensus structure prediction to RNA gene finding
2009
Briefings in Functional Genomics & Proteomics
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Since the accuracy of structure prediction from single sequences is limited, one often resorts to computing the consensus structure for a set of related RNA sequences. ...
Here we review different strategies for the prediction of consensus secondary structures, and show how these approaches can be used to predict non-coding RNA genes. ...
Using a DP algorithm, the optimal secondary structure for every pair of sequences is found. ...
doi:10.1093/bfgp/elp043
pmid:19833701
fatcat:w6oxxm76svhhzauzgulabco2xa
Bioinformatics: A Challenge to Constraint Programming
[chapter]
2010
Hybrid Optimization
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Bioinformatics is a rapidly growing field at the intersection of biology and computer science. As such, it poses a wealth of problems, opportunities and challenges for both areas. ...
At this light, the paper briefly presents the selected problems together with the solutions found so far, that illustrate the versatility of CP techniques that have been used in this area and the need ...
RNA secondary structure is defined by the graph of pairings between bases in the same RNA molecule. ...
doi:10.1007/978-1-4419-1644-0_14
fatcat:wpukgksb45da3i2ctaxhdgn6ya
Computational approaches to RNA structure prediction, analysis, and design
2011
Current Opinion in Structural Biology
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Here, we review recent advances in RNA folding algorithms, RNA tertiary motif discovery, applications of graph theory approaches to RNA structure and function, and in silico generation of RNA sequence ...
Although modeling approaches for the study of RNA structures and dynamics lag behind efforts in protein folding, much progress has been achieved in the past two years. ...
Acknowledgements This work was supported by NSF (EMT award CCF-0727001) and NIH (grants GM081410 and ES01269201). ...
doi:10.1016/j.sbi.2011.03.015
pmid:21514143
pmcid:PMC3112238
fatcat:rgqhbrxvkndrvdl6io7ew7rn24
Adventures with RNA graphs
2018
Methods
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In this chapter, we outline the development of the RNA-As-Graphs (or RAG) approach and highlight current applications to RNA structure prediction and design. ...
The structure of RNA has been a natural subject for mathematical modeling, inviting many innovative computational frameworks. ...
The author is grateful to Swati Jain for preparing many of the figures.
Literature cited ...
doi:10.1016/j.ymeth.2018.03.009
pmid:29621619
pmcid:PMC6051918
fatcat:bfsktwmieve4ro7sys6ehc3pfa
Advances in Structure Modeling Methods forCryo-Electron Microscopy Maps
2019
Molecules
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It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. ...
For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. ...
This work was partly supported by the National Institutes of Health (R01GM123055), the National Science Foundation (DMS1614777, CMMI1825941, and MCB1925643) and the Purdue Institute for Drug Discovery. ...
doi:10.3390/molecules25010082
pmid:31878333
pmcid:PMC6982917
fatcat:ctutiaxvnbhsjed7ozokiq5txu
Artificial Neural Network in Drug Delivery and Pharmaceutical Research
2013
The Open Bioinformatics Journal
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Interestingly, ANN simulates the biological nervous system and draws on analogues of adaptive biological neurons. ...
Because of their capacity for making predictions, pattern recognition, and modeling, ANNs have been very useful in many aspects of pharmaceutical research including modeling of the brain neural network ...
Additionally, ANNs enable simulation of drug molecules and protein structures and help determine the folding and secondary structure of RNA strand [103, 104] . ...
doi:10.2174/1875036201307010049
fatcat:z2zeq4xgrfcu5iuzjxu7ji6434
Natural computing methods in bioinformatics: A survey
2009
Information Fusion
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In this article we survey the role of natural computing in the domains of protein structure prediction, microarray data analysis and gene regulatory network generation. ...
Often data analysis problems in Bioinformatics concern the fusion of multisensor outputs or the fusion of multi-source information, where one must integrate different kinds of biological data. ...
[7] , Machine Learning approaches [8] , and general optimization techniques, such as Evolutionary Computation based on simulation of biological evolution [9, 10] , Swarm Intelligence based on simulation ...
doi:10.1016/j.inffus.2008.12.002
fatcat:hwame6u3svh4jdqb3qfetvzxeq
Ab initioRNA folding
2015
Journal of Physics: Condensed Matter
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Theoretical approaches to RNA folding have been developed since the late nineties when the first algorithms for secondary structure prediction appeared. ...
We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in ...
Laurin for their contribution in the development of HiRE-RNA during their Master internships. ...
doi:10.1088/0953-8984/27/23/233102
pmid:25993396
fatcat:sfua5jw5ivgobifajpnxwq3vry
In Silico Design and Enzymatic Synthesis of Functional RNA Nanoparticles
2014
Accounts of Chemical Research
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On one end, it encompasses the rational design and various computational schemes that promote design of the RNA-based nanoconstructs, ultimately producing a set of sequences consisting of RNA or RNA−DNA ...
This is opposite to the usual practice of predicting RNA structures from a given sequence, that is, the RNA folding problem. ...
■ MULTISTRAND SECONDARY STRUCTURE PREDICTION AND SEQUENCE DESIGN Design of RNA NPs is based on the ability to predict the pairing interactions of a given RNA nucleotide sequence. ...
doi:10.1021/ar400329z
pmid:24758371
pmcid:PMC4066900
fatcat:kpkaakvo6ffujj4tgfosht5vji
Computational Methods in Drug Discovery
2013
Pharmacological Reviews
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Authorship Contributions Wrote or contributed to the writing of the manuscript: Sliwoski, Kothiwale, Meiler, Lowe. ...
Additionally, effective sampling strategies are used while dealing with large search spaces such as evolutionary algorithms, metropolis search, or simulated annealing . ...
Ten different models are created following a simulated annealing optimization (Chang and Swaan, 2006) . ...
doi:10.1124/pr.112.007336
pmid:24381236
pmcid:PMC3880464
fatcat:4dzrdkspkjecnombnchznma2ny
An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding
2015
PLoS ONE
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Potential uses in finding novel eukaryotic riboswitches and optimizing pre-designed synthetic riboswitches based on ligand simulations are discussed. ...
The transformation to sequence space is obtained by using an extended inverse RNA folding problem solver with sequence and structure constraints, available within RNAfbinv. ...
Acknowledgments We thank Payal Singh and Sumit Mukherjee for verification runs with pHMM, and Lina Weinbrand for assistance in modifying RNAfbinv for the purpose of riboswitch identification. ...
doi:10.1371/journal.pone.0134262
pmid:26230932
pmcid:PMC4521916
fatcat:7agzct3da5cwhbvgyniavrpcpm
An automatic representation of peptides for effective antimicrobial activity classification
2020
Computational and Structural Biotechnology Journal
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Furthermore, the best classification results are achieved by using only 39 out of 272 molecular descriptors. ...
The method is based on a Genetic Algorithm that uses a variable-length chromosome for representing the selected features and uses an objective function that considers the Mathew Correlation Coefficient ...
the performance of predictive models since those 103 descriptors define the chemical space where each peptide is pro-104 jected and in consequence the efficiency of the classification 105 depends on it ...
doi:10.1016/j.csbj.2020.02.002
pmid:32180904
pmcid:PMC7063200
fatcat:cgftuvf4snditeetpz4iurfj6q
Deep Learning in Protein Structural Modeling and Design
[article]
2020
arXiv
pre-print
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We argue for the central importance of structure, following the "sequence -> structure -> function" paradigm. ...
In this review, we summarize the recent advances in applying deep learning techniques to tackle problems in protein structural modeling and design. ...
Acknowledgement Acknowledgement This work was supported by the National Institutes of Health through grant R01-GM078221. ...
arXiv:2007.08383v1
fatcat:ynpdumcqnbel7duwffbork6s2u
Monte Carlo Methods for Small Molecule High-Throughput Experimentation
2001
Journal of chemical information and computer sciences
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Among them, the biased Monte Carlo schemes exhibit particularly high efficiency in locating optimal compounds. The Monte Carlo strategies are compared to a genetic algorithm approach. ...
Although the best compounds identified by the genetic algorithm are comparable to those from the better Monte Carlo schemes, the diversity of favorable compounds identified is reduced by roughly 60%. ...
ACKNOWLEDGMENT This research was supported by National Science Foundation through grant number CTS-9702403. ...
doi:10.1021/ci000151l
pmid:11500111
fatcat:xfthfdxbcnfdbaakwlf2vpb5ty
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