C. Brunel and P. Romby, Probing RNA structure and RNA-ligand complexes with chemical probes, Methods Enzymol, vol.318, pp.3-21, 2000.

S. Busan and K. M. Weeks, Accurate detection of chemical modifications in rna by mutational profiling (map) with shapemapper 2, RNA, vol.24, issue.2, pp.143-148, 2018.

S. Busan, A. Chase-a-weidmann, K. M. Sengupta, and . Weeks, Guidelines for SHAPE Reagent Choice and Detection Strategy for RNA Structure Probing Studies, Biochemistry (Mosc ), vol.58, pp.2655-2664, 2019.

S. Butcher and J. Burke, Structure-mapping of the hairpin ribozyme. Magnesium-dependent folding and evidence for tertiary interactions within the ribozyme-substrate complex, J Mol Biol, vol.244, pp.52-63, 1994.

Y. Clarence, W. Cheng, . Kladwang, R. Joseph-d-yesselman, and . Das, RNA structure inference through chemical mapping after accidental or intentional mutations, Proc Natl Acad Sci U S A, vol.114, issue.37, pp.9876-9881, 2017.

P. Cordero and R. Das, Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis, PLoS Comput Biol, vol.11, p.1004473, 2015.

P. Cordero, W. Kladwang, C. Christopher, R. Vanlang, and . Das, Quantitative Dimethyl Sulfate Mapping for Automated RNA Secondary Structure Inference, Biochemistry (Mosc ), vol.51, issue.36, pp.7037-7039, 2012.

P. Cordero, J. B. Lucks, and R. Das, An RNA mapping data base for curating RNA structure mapping experiments, Bioinformatics, vol.28, issue.22, pp.3006-3008, 2012.

J. Deforges, M. Sylvain-de-breyne, N. Ameur, N. Ulryck, A. Chamond et al., Two ribosome recruitment sites direct multiple translation events within HIV1 Gag open reading frame, Nucleic Acids Res, vol.45, pp.7382-7400, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01505282

K. E. Deigan, T. W. Li, D. H. Mathews, and K. M. Weeks, Accurate SHAPE-directed RNA structure determination, Proc Natl Acad Sci U S A, vol.106, issue.1, pp.97-102, 2009.

F. Deng, M. Ledda, S. Vaziri, and S. Aviran, Data-directed RNA secondary structure prediction using probabilistic modeling, RNA, vol.22, issue.8, pp.1109-1119, 2016.

Y. Ding and C. E. Lawrence, A statistical sampling algorithm for RNA secondary structure prediction, Nucleic Acids Res, vol.31, issue.24, pp.7280-7301, 2003.

C. Ehresmann, M. Baudin, P. Mougel, J. Romby, B. Ebel et al., Probing the structure of RNAs in solution, Nucleic Acids Res, vol.15, pp.9109-9128, 1987.

E. Frezza, . Courban, . Allouche, S. Sargueil, and . Pasquali, The Interplay between Molecular Flexibility and RNA Chemical Probing Reactivities Analyzed at the Nucleotide Level via an Extensive Molecular Dynamics Study, pp.108-127, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02387476

Z. Costin-m-gherghe, K. A. Shajani, G. Wilkinson, K. M. Varani, and . Weeks, Strong correlation between SHAPE chemistry and the generalized NMR order parameter (S2) in RNA, J Am Chem Soc, vol.130, pp.12244-12245, 2008.

J. Gorodkin, G. Stricklin, and . Stormo, Discovering common stem-loop motifs in unaligned RNA sequences, Nucleic Acids Res, vol.29, pp.2135-2144, 2001.

L. Gross, Q. Vicens, E. Einhorn, A. Noireterre, L. Schaeffer et al., The IRES 5'UTR of the dicistrovirus cricket paralysis virus is a type III IRES containing an essential pseudoknot structure, Nucleic Acids Res, vol.45, pp.8993-9004, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02171275

C. E. Hajdin, S. Bellaousov, W. Huggins, C. W. Leonard, D. H. Mathews et al., Accurate SHAPEdirected RNA secondary structure modeling, including pseudoknots, Proc Natl Acad Sci U S A, vol.110, issue.14, pp.5498-5503, 2013.

H. Cécile, L. Herbreteau, D. Weill, D. Décimo, J. Prévôt et al., HIV-2 genomic RNA contains a novel type of IRES located downstream of its initiation codon, Nature structural & molecular biology, vol.12, pp.1001-1007, 2005.

T. Hurst, X. Xu, P. Zhao, and S. Chen, Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis, The journal of physical chemistry. B, vol.122, pp.4771-4783, 2018.

L. James and B. Sargueil, RNA secondary structure of the feline immunodeficiency virus 5'UTR and Gag coding region, Nucleic Acids Res, vol.36, pp.4653-4666, 2008.

S. Janssen and R. Giegerich, The rna shapes studio, Bioinformatics, vol.31, pp.423-425, 2015.

F. Karabiber, J. L. Mcginnis, O. V. Favorov, and K. M. Weeks, QuShape: rapid, accurate, and best-practices quantification of nucleic acid probing information, resolved by capillary electrophoresis, RNA, vol.19, pp.63-73, 2013.

G. Knapp, Enzymatic approaches to probing of RNA secondary and tertiary structure, Methods Enzymol, vol.180, pp.192-212, 1989.

A. Christopher, R. Lavender, G. Lorenz, R. Zhang, . Tamayo et al., Model-Free RNA Sequence and Structure Alignment Informed by SHAPE Probing Reveals a Conserved Alternate Secondary Structure for 16S rRNA, PLoS Comput Biol, vol.11, 2015.

R. Lorenz, H. Stephan, C. Bernhart, H. Höner-zu-siederdissen, C. Tafer et al., ViennaRNA Package 2.0. Algorithms for molecular biology : AMB, 6:26, 2011.

R. Lorenz, D. Luntzer, L. Ivo, . Hofacker, F. Peter et al., SHAPE directed RNA folding, Bioinformatics, vol.32, pp.145-147, 2016.

H. J. Xiang-jun-lu, W. K. Bussemaker, and . Olson, DSSR: An integrated software tool for dissecting the spatial structure of RNA, Nucleic Acids Res, vol.43, issue.21, 2015.

Z. Lu, J. W. Gloor, and D. Mathews, Improved RNA secondary structure prediction by maximizing expected pair accuracy, RNA, vol.15, issue.10, pp.1805-1813, 2009.

H. David, . Mathews, D. Matthew, J. L. Disney, S. J. Childs et al., Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure, Proc Natl Acad Sci U S A, vol.101, issue.19, pp.7287-92, 2004.

A. Christopher, A. Mattson, and . Messac, Pareto frontier based concept selection under uncertainty, with visualization, Optimization and Engineering, vol.6, issue.1, pp.85-115, 2005.

J. Mccaskill, The equilibrium partition function and base pair binding probabilities for RNA secondary structure, Biopolymers, vol.29, issue.6-7, pp.1105-1119, 1990.

L. Jennifer, J. A. Mcginnis, J. Dunkle, H. Cate, and K. M. Weeks, The mechanisms of RNA SHAPE chemistry, J Am Chem Soc, vol.134, pp.6617-6624, 2012.

M. Meyer, H. Nielsen, V. Olieric, P. Roblin, S. D. Johansen et al., Speciation of a group I intron into a lariat capping ribozyme, Proc. Natl. Acad. Sci. U.S.A, vol.111, issue.21, pp.7659-7664, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02633667

Z. Miao, W. Ryszard, M. Adamiak, . Antczak, T. Robert et al., RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme, RNA, vol.23, pp.655-672, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02171291

V. Mlýnský and G. Bussi, Molecular Dynamics Simulations Reveal an Interplay between SHAPE Reagent Binding and RNA Flexibility. The journal of physical chemistry letters, vol.9, pp.313-318, 2018.

D. Moazed, H. Stern, and . Noller, Rapid chemical probing of conformation in 16 S ribosomal RNA and 30 S ribosomal subunits using primer extension, J Mol Biol, vol.187, pp.22-2836, 1986.

J. Paillart, M. Dettenhofer, X. Yu, C. Ehresmann, B. Ehresmann et al., First snapshots of the hiv-1 rna structure in infected cells and in virions, Journal of Biological Chemistry, vol.279, issue.46, pp.48397-48403, 2004.

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00650905

J. S. Reuter and D. H. Mathews, RNAstructure: Software for RNA secondary structure prediction and analysis, BMC Bioinf, vol.11, p.129, 2010.

M. Greggory, . Rice, W. Christopher, K. M. Leonard, and . Weeks, RNA secondary structure modeling at consistent high accuracy using differential SHAPE, RNA, vol.20, pp.846-854, 2014.

I. P-j-romaniuk, C. Stevenson, P. Ehresmann, B. Romby, and . Ehresmann, A comparison of the solution structures and conformational properties of the somatic and oocyte 5S rRNAs of Xenopus laevis, Nucleic Acids Res, vol.16, pp.2295-2312, 1988.

D. Sculley, Web-scale k-means clustering, Proceedings of the 19th international conference on World Wide Web (WWW'10), pp.1177-1178, 2010.

A. N. Sexton, Y. Peter, M. Wang, M. Rutenberg-schoenberg, and . Simon, Interpreting Reverse Transcriptase Termination and Mutation Events for Greater Insight into the Chemical Probing of RNA, Biochemistry (Mosc ), vol.56, pp.4713-4721, 2017.

S. Smit, K. Rother, J. Heringa, and R. Knight, From knotted to nested RNA structures: a variety of computational methods for pseudoknot removal, RNA, vol.14, pp.410-416, 2008.

J. Matthew, G. M. Smola, S. Rice, . Busan, A. Nathan et al., Selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis, Nat Protoc, vol.10, pp.1643-1669, 2015.

S. Somarowthu, M. Legiewicz, I. Chillón, M. Marcia, F. Liu et al., HOTAIR forms an intricate and modular secondary structure, Mol Cell, vol.58, pp.353-361, 2015.

A. Spasic, S. M. Assmann, P. C. Bevilacqua, and D. H. Mathews, Modeling RNA secondary structure folding ensembles using SHAPE mapping data, Nucleic Acids Res, vol.46, issue.1, pp.314-323, 2017.

K. Steen, G. M. Rice, and K. M. Weeks, Fingerprinting noncanonical and tertiary RNA structures by differential SHAPE reactivity, J Am Chem Soc, vol.134, pp.13160-13163, 2012.

H. Douglas, D. Turner, and . Mathews, NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure, Nucleic Acids Res, vol.38, pp.280-282, 2010.

S. Washietl, L. Ivo, P. F. Hofacker, M. Stadler, and . Kellis, RNA folding with soft constraints: Reconciliation of probing data and thermodynamic secondary structure prediction, Nucleic Acids Res, vol.40, issue.10, pp.4261-4272, 2012.

L. Weill, D. Louis, and B. Sargueil, Selection and evolution of NTP-specific aptamers, Nucleic Acids Res, vol.32, pp.5045-5058, 2004.

A. Kevin, E. J. Wilkinson, K. M. Merino, and . Weeks, Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE): quantitative RNA structure analysis at single nucleotide resolution, Nat Protoc, vol.1, pp.1610-1616, 2006.

Y. Wu, B. Shi, X. Ding, T. Liu, X. Hu et al., Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data, Nucleic Acids Res, vol.43, issue.15, pp.7247-7259, 2015.

Z. Xu, A. Almudevar, and D. Mathews, Statistical evaluation of improvement in RNA secondary structure prediction, Nucleic acids research, vol.40, p.26, 2012.

M. Angela, M. E. Yu, J. B. Evans, and . Lucks, Estimating RNA structure chemical probing reactivities from reverse transcriptase stops and mutations, BioRxiv, vol.292532, 2018.

K. Zarringhalam, M. M. Meyer, I. Dotu, J. H. Chuang, and P. Clote, Integrating Chemical Footprinting Data into RNA Secondary Structure Prediction, PLoS One, vol.7, issue.10, p.45160, 2012.

A. Zaug and T. Cech, Analysis of the structure of tetrahymena nuclear rnas in vivo: telomerase rna, the selfsplicing rrna intron, and u2 snrna, RNA, vol.1, issue.4, pp.363-74, 1995.