Literature DB >> 32813048

Can artificial neural replicators be useful for studying RNA replicators?

Alexandr A Ezhov1.   

Abstract

Here, I discuss the usefulness of the application of special artificial neural systems - neural replicators - to study viroids - small pathogens that are short replicating RNA sequences. Using special representations of nucleotide sequences in the form of two sequences with binary components - these two sequences are incomplete representations of the same nucleotide sequence - I show that these neural systems of different sizes are replicated in a special way on them. This allows us to extract some useful information about viroids and their structure, motifs, and relationships. This study is only the first attempt to use neural replicators to analyze genetic data.

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Year:  2020        PMID: 32813048     DOI: 10.1007/s00705-020-04779-0

Source DB:  PubMed          Journal:  Arch Virol        ISSN: 0304-8608            Impact factor:   2.574


  31 in total

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Journal:  J Mol Evol       Date:  2010-08-26       Impact factor: 2.395

2.  A novel representation of genomic sequences for taxonomic clustering and visualization by means of self-organizing maps.

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Authors:  N Qian; T J Sejnowski
Journal:  J Mol Biol       Date:  1988-08-20       Impact factor: 5.469

5.  Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin.

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Journal:  FEBS Lett       Date:  1988-12-05       Impact factor: 4.124

6.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

Review 7.  A primer on deep learning in genomics.

Authors:  James Zou; Mikael Huss; Abubakar Abid; Pejman Mohammadi; Ali Torkamani; Amalio Telenti
Journal:  Nat Genet       Date:  2018-11-26       Impact factor: 38.330

Review 8.  Deep learning for computational biology.

Authors:  Christof Angermueller; Tanel Pärnamaa; Leopold Parts; Oliver Stegle
Journal:  Mol Syst Biol       Date:  2016-07-29       Impact factor: 11.429

9.  DeePromoter: Robust Promoter Predictor Using Deep Learning.

Authors:  Mhaned Oubounyt; Zakaria Louadi; Hilal Tayara; Kil To Chong
Journal:  Front Genet       Date:  2019-04-05       Impact factor: 4.599

10.  Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases.

Authors:  Rocio Chavez-Alvarez; Arturo Chavoya; Andres Mendez-Vazquez
Journal:  PLoS One       Date:  2014-04-03       Impact factor: 3.240

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