Literature DB >> 15215366

Sfold web server for statistical folding and rational design of nucleic acids.

Ye Ding1, Chi Yu Chan, Charles E Lawrence.   

Abstract

The Sfold web server provides user-friendly access to Sfold, a recently developed nucleic acid folding software package, via the World Wide Web (WWW). The software is based on a new statistical sampling paradigm for the prediction of RNA secondary structure. One of the main objectives of this software is to offer computational tools for the rational design of RNA-targeting nucleic acids, which include small interfering RNAs (siRNAs), antisense oligonucleotides and trans-cleaving ribozymes for gene knock-down studies. The methodology for siRNA design is based on a combination of RNA target accessibility prediction, siRNA duplex thermodynamic properties and empirical design rules. Our approach to target accessibility evaluation is an original extension of the underlying RNA folding algorithm to account for the likely existence of a population of structures for the target mRNA. In addition to the application modules Sirna, Soligo and Sribo for siRNAs, antisense oligos and ribozymes, respectively, the module Srna offers comprehensive features for statistical representation of sampled structures. Detailed output in both graphical and text formats is available for all modules. The Sfold server is available at http://sfold.wadsworth.org and http://www.bioinfo.rpi.edu/applications/sfold.

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Substances:

Year:  2004        PMID: 15215366      PMCID: PMC441587          DOI: 10.1093/nar/gkh449

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  28 in total

1.  Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.

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Journal:  J Mol Biol       Date:  1999-05-21       Impact factor: 5.469

2.  Asymmetry in the assembly of the RNAi enzyme complex.

Authors:  Dianne S Schwarz; György Hutvágner; Tingting Du; Zuoshang Xu; Neil Aronin; Phillip D Zamore
Journal:  Cell       Date:  2003-10-17       Impact factor: 41.582

3.  Functional siRNAs and miRNAs exhibit strand bias.

Authors:  Anastasia Khvorova; Angela Reynolds; Sumedha D Jayasena
Journal:  Cell       Date:  2003-10-17       Impact factor: 41.582

4.  RNAML: a standard syntax for exchanging RNA information.

Authors:  Allison Waugh; Patrick Gendron; Russ Altman; James W Brown; David Case; Daniel Gautheret; Stephen C Harvey; Neocles Leontis; John Westbrook; Eric Westhof; Michael Zuker; François Major
Journal:  RNA       Date:  2002-06       Impact factor: 4.942

5.  Mfold web server for nucleic acid folding and hybridization prediction.

Authors:  Michael Zuker
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

6.  The activity of siRNA in mammalian cells is related to structural target accessibility: a comparison with antisense oligonucleotides.

Authors:  Rosel Kretschmer-Kazemi Far; Georg Sczakiel
Journal:  Nucleic Acids Res       Date:  2003-08-01       Impact factor: 16.971

7.  Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond.

Authors:  Y Ding; C E Lawrence
Journal:  Nucleic Acids Res       Date:  2001-03-01       Impact factor: 16.971

8.  The efficacy of small interfering RNAs targeted to the type 1 insulin-like growth factor receptor (IGF1R) is influenced by secondary structure in the IGF1R transcript.

Authors:  Erin A Bohula; Amanda J Salisbury; Muhammad Sohail; Martin P Playford; Johann Riedemann; Edwin M Southern; Valentine M Macaulay
Journal:  J Biol Chem       Date:  2003-02-24       Impact factor: 5.157

9.  Thermodynamic criteria for high hit rate antisense oligonucleotide design.

Authors:  O V Matveeva; D H Mathews; A D Tsodikov; S A Shabalina; R F Gesteland; J F Atkins; S M Freier
Journal:  Nucleic Acids Res       Date:  2003-09-01       Impact factor: 16.971

10.  Efficient reduction of target RNAs by small interfering RNA and RNase H-dependent antisense agents. A comparative analysis.

Authors:  Timothy A Vickers; Seongjoon Koo; C Frank Bennett; Stanley T Crooke; Nicholas M Dean; Brenda F Baker
Journal:  J Biol Chem       Date:  2002-12-23       Impact factor: 5.157

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  205 in total

1.  Profiling small RNA reveals multimodal substructural signals in a Boltzmann ensemble.

Authors:  Emily Rogers; Christine E Heitsch
Journal:  Nucleic Acids Res       Date:  2014-11-11       Impact factor: 16.971

2.  Evaluation of a sophisticated SCFG design for RNA secondary structure prediction.

Authors:  Markus E Nebel; Anika Scheid
Journal:  Theory Biosci       Date:  2011-12-02       Impact factor: 1.919

Review 3.  A classification of bioinformatics algorithms from the viewpoint of maximizing expected accuracy (MEA).

Authors:  Michiaki Hamada; Kiyoshi Asai
Journal:  J Comput Biol       Date:  2012-02-07       Impact factor: 1.479

4.  SHAPE-directed discovery of potent shRNA inhibitors of HIV-1.

Authors:  Justin T Low; Stefanie A Knoepfel; Joseph M Watts; Olivier ter Brake; Ben Berkhout; Kevin M Weeks
Journal:  Mol Ther       Date:  2012-02-07       Impact factor: 11.454

5.  Robust translation of the nucleoid protein Fis requires a remote upstream AU element and is enhanced by RNA secondary structure.

Authors:  Maryam Nafissi; Jeannette Chau; Jimin Xu; Reid C Johnson
Journal:  J Bacteriol       Date:  2012-03-02       Impact factor: 3.490

6.  Incorporating global features of RNA motifs in predictions for an ensemble of secondary structures for encapsidated MS2 bacteriophage RNA.

Authors:  Samuel Bleckley; Susan J Schroeder
Journal:  RNA       Date:  2012-05-29       Impact factor: 4.942

Review 7.  Designing highly active siRNAs for therapeutic applications.

Authors:  S Patrick Walton; Ming Wu; Joseph A Gredell; Christina Chan
Journal:  FEBS J       Date:  2010-12       Impact factor: 5.542

8.  Software note: using probe secondary structure information to enhance Affymetrix GeneChip background estimates.

Authors:  Raad Z Gharaibeh; Anthony A Fodor; Cynthia J Gibas
Journal:  Comput Biol Chem       Date:  2007-02-20       Impact factor: 2.877

9.  STarMir Tools for Prediction of microRNA Binding Sites.

Authors:  Shaveta Kanoria; William Rennie; Chaochun Liu; C Steven Carmack; Jun Lu; Ye Ding
Journal:  Methods Mol Biol       Date:  2016

10.  Vasa promotes Drosophila germline stem cell differentiation by activating mei-P26 translation by directly interacting with a (U)-rich motif in its 3' UTR.

Authors:  Niankun Liu; Hong Han; Paul Lasko
Journal:  Genes Dev       Date:  2009-12-01       Impact factor: 11.361

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