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28. Huppert, J. L., Bugaut, A., Kumari, S., & Balasubramanian, S. (2008). G-quadruplexes: The
beginning and end of UTRs. Nucleic Acids Research, 36(19), 6260–6268.
29. Stoltenburg, R., Reinemann, C., & Strehlitz, B. (2007). SELEX–a (r)evolutionary method to
generate high-affinity nucleic acid ligands. Biomolecular Engineering, 24(4), 381–403.
30. Breaker, R. R. (1997). DNA aptamers and DNA enzymes. Current Opinion in Chemical
Biology, 1(1), 26–31.
31. Doherty, E. A., & Doudna, J. A. (2000). Ribozyme structures and mechanisms. Annual
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32. Ohno, H., Akamine, S., & Saito, H. (2018). RNA nanostructures and scaffolds for
biotechnology applications. Current Opinion in Biotechnology, 28(58), 53–61.
33. Zalatan, J. G. (2017). CRISPR-Cas RNA scaffolds for transcriptional programming in yeast.
Methods in Molecular Biology, 1632, 341–357.
34. Jiang, S., Hong, F., Hu, H., Yan, H., & Liu, Y. (2017). Understanding the elementary steps in
DNA tile-based self-assembly. ACS Nano, 11(9), 9370–9381.
35. Endo, M., & Sugiyama, H. (2018). DNA origami nanomachines. Molecules, 23(7), E1766.
36. Auffinger, P., D’Ascenzo, L., & Ennifar, E. (2016). Sodium and potassium interactions with
nucleic acids. Metal Ions in Life Sciences, 16, 167–201.
37. Kolev, S. K., Petkov, P. S., Rangelov, M. A., Trifonov, D. V., Milenov, T. I., & Vayssilov, G.
N. (2018). Interaction of Na(
+ ), K(
+ ), Mg(
2+ ) and Ca(
2+ ) counter cations with RNA.
Metallomics, 10(5), 659–678.
38. Westhof, E., Masquida, B., & Jaeger, L. (1996). RNA tectonics: Towards RNA design.
Folding and Design, 1(4), R78–R88.
39. Eremeeva, E., Abramov, M., Margamuljana, L., & Herdewijn, P. (2017). Base-modified
nucleic acids as a powerful tool for synthetic biology and biotechnology. Chemistry, 23(40),
9560–9576.
40. Karcher, S., Willighagen, E. L., Rumble, J., Ehrhart, F., Evelo, C. T., Fritts, M., et al. (2018).
Integration among databases and data sets to support productive nanotechnology: Challenges
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41. Purawat, S., Ieong, P. U., Malmstrom, R. D., Chan, G. J., Yeung, A. K., Walker, R. C., et al.
(2017). A kepler workflow tool for reproducible AMBER GPU molecular dynamics.
Biophysical Journal, 112(12), 2469–2474.
42. Walker, M. A., Madduri, R., Rodriguez, A., Greenstein, J. L., & Winslow, R. L. (2016).
Models and simulations as a service: Exploring the use of galaxy for delivering computational
models. Biophysical Journal, 110(5), 1038–1043.
43. Fillbrunn, A., Dietz, C., Pfeuffer, J., Rahn, R., Landrum, G. A., & Berthold, M. R. (2017).
KNIME for reproducible cross-domain analysis of life science data. Journal of Biotechnology,
10(261), 149–156.
44. Coimbatore Narayanan, B., Westbrook, J., Ghosh, S., Petrov, A. I., Sweeney, B., Zirbel, C.
L., et al. (2014). The nucleic acid database: New features and capabilities. Nucleic Acids
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45. Parlea, L. G., Sweeney, B. A., Hosseini-Asanjan, M., Zirbel, C. L., & Leontis, N. B. (2016).
The RNA 3D motif atlas: Computational methods for extraction, organization and evaluation
of RNA motifs. Methods, 1(103), 99–119.
46. Garant, J. M., Luce, M. J., Scott, M. S., & Perreault, J. P. (2015). G4RNA: An RNA
G-quadruplex database. Database (Oxford), 2015, bav059.
47. Mishra, S. K., Tawani, A., Mishra, A., & Kumar, A. (2016). G4IPDB: A database for
G-quadruplex structure forming nucleic acid interacting proteins. Scientific Reports, 1(6),
38144.
228
P. Arrigo and D. Baroni
12(1), 83–93.
27. Zaccaria, F., & Fonseca, G. C. (2018). RNA versus DNA G-quadruplex: The origin of
increased stability. Chemistry, 24(61), 16315–16322.
28. Huppert, J. L., Bugaut, A., Kumari, S., & Balasubramanian, S. (2008). G-quadruplexes: The
beginning and end of UTRs. Nucleic Acids Research, 36(19), 6260–6268.
29. Stoltenburg, R., Reinemann, C., & Strehlitz, B. (2007). SELEX–a (r)evolutionary method to
generate high-affinity nucleic acid ligands. Biomolecular Engineering, 24(4), 381–403.
30. Breaker, R. R. (1997). DNA aptamers and DNA enzymes. Current Opinion in Chemical
Biology, 1(1), 26–31.
31. Doherty, E. A., & Doudna, J. A. (2000). Ribozyme structures and mechanisms. Annual
Review of Biochemistry, 69, 597–615.
32. Ohno, H., Akamine, S., & Saito, H. (2018). RNA nanostructures and scaffolds for
biotechnology applications. Current Opinion in Biotechnology, 28(58), 53–61.
33. Zalatan, J. G. (2017). CRISPR-Cas RNA scaffolds for transcriptional programming in yeast.
Methods in Molecular Biology, 1632, 341–357.
34. Jiang, S., Hong, F., Hu, H., Yan, H., & Liu, Y. (2017). Understanding the elementary steps in
DNA tile-based self-assembly. ACS Nano, 11(9), 9370–9381.
35. Endo, M., & Sugiyama, H. (2018). DNA origami nanomachines. Molecules, 23(7), E1766.
36. Auffinger, P., D’Ascenzo, L., & Ennifar, E. (2016). Sodium and potassium interactions with
nucleic acids. Metal Ions in Life Sciences, 16, 167–201.
37. Kolev, S. K., Petkov, P. S., Rangelov, M. A., Trifonov, D. V., Milenov, T. I., & Vayssilov, G.
N. (2018). Interaction of Na(
+ ), K(
+ ), Mg(
2+ ) and Ca(
2+ ) counter cations with RNA.
Metallomics, 10(5), 659–678.
38. Westhof, E., Masquida, B., & Jaeger, L. (1996). RNA tectonics: Towards RNA design.
Folding and Design, 1(4), R78–R88.
39. Eremeeva, E., Abramov, M., Margamuljana, L., & Herdewijn, P. (2017). Base-modified
nucleic acids as a powerful tool for synthetic biology and biotechnology. Chemistry, 23(40),
9560–9576.
40. Karcher, S., Willighagen, E. L., Rumble, J., Ehrhart, F., Evelo, C. T., Fritts, M., et al. (2018).
Integration among databases and data sets to support productive nanotechnology: Challenges
and recommendations. NanoImpact, 9, 85–101.
41. Purawat, S., Ieong, P. U., Malmstrom, R. D., Chan, G. J., Yeung, A. K., Walker, R. C., et al.
(2017). A kepler workflow tool for reproducible AMBER GPU molecular dynamics.
Biophysical Journal, 112(12), 2469–2474.
42. Walker, M. A., Madduri, R., Rodriguez, A., Greenstein, J. L., & Winslow, R. L. (2016).
Models and simulations as a service: Exploring the use of galaxy for delivering computational
models. Biophysical Journal, 110(5), 1038–1043.
43. Fillbrunn, A., Dietz, C., Pfeuffer, J., Rahn, R., Landrum, G. A., & Berthold, M. R. (2017).
KNIME for reproducible cross-domain analysis of life science data. Journal of Biotechnology,
10(261), 149–156.
44. Coimbatore Narayanan, B., Westbrook, J., Ghosh, S., Petrov, A. I., Sweeney, B., Zirbel, C.
L., et al. (2014). The nucleic acid database: New features and capabilities. Nucleic Acids
Research, 42(Database issue), D114–D122.
45. Parlea, L. G., Sweeney, B. A., Hosseini-Asanjan, M., Zirbel, C. L., & Leontis, N. B. (2016).
The RNA 3D motif atlas: Computational methods for extraction, organization and evaluation
of RNA motifs. Methods, 1(103), 99–119.
46. Garant, J. M., Luce, M. J., Scott, M. S., & Perreault, J. P. (2015). G4RNA: An RNA
G-quadruplex database. Database (Oxford), 2015, bav059.
47. Mishra, S. K., Tawani, A., Mishra, A., & Kumar, A. (2016). G4IPDB: A database for
G-quadruplex structure forming nucleic acid interacting proteins. Scientific Reports, 1(6),
38144.
228
P. Arrigo and D. Baroni