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Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler

Eckart Bindewald, Calvin Grunewald, Brett Boyle, Mary O'Connor, Bruce A. Shapiro
2008 Journal of Molecular Graphics and Modelling  
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

S. H. Bernhart, I. L. Hofacker
2009 Briefings in Functional Genomics & Proteomics  
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]

Pedro Barahona, Ludwig Krippahl, Olivier Perriquet
2010 Hybrid Optimization  
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

Christian Laing, Tamar Schlick
2011 Current Opinion in Structural Biology  
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/ pmid:21514143 pmcid:PMC3112238 fatcat:rgqhbrxvkndrvdl6io7ew7rn24

Adventures with RNA graphs

Tamar Schlick
2018 Methods  
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

Alnabati, Kihara
2019 Molecules  
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

Vijaykumar Sutariya
2013 The Open Bioinformatics Journal  
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

Francesco Masulli, Sushmita Mitra
2009 Information Fusion  
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

Tristan Cragnolini, Philippe Derreumaux, Samuela Pasquali
2015 Journal of Physics: Condensed Matter  
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

Kirill A. Afonin, Wojciech K. Kasprzak, Eckart Bindewald, Maria Kireeva, Mathias Viard, Mikhail Kashlev, Bruce A. Shapiro
2014 Accounts of Chemical Research  
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

G. Sliwoski, S. Kothiwale, J. Meiler, E. W. Lowe
2013 Pharmacological Reviews  
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

Matan Drory Retwitzer, Ilona Kifer, Supratim Sengupta, Zohar Yakhini, Danny Barash, Tamir Tuller
2015 PLoS ONE  
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

Jesus A. Beltran, Gabriel Del Rio, Carlos A. Brizuela
2020 Computational and Structural Biotechnology Journal  
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]

Wenhao Gao, Sai Pooja Mahajan, Jeremias Sulam, Jeffrey J. Gray
2020 arXiv   pre-print
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

Ligang Chen, Michael W. Deem
2001 Journal of chemical information and computer sciences  
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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