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3 | 3 |
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4 | 4 | @string{aps = {American Physical Society,}}
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5 | 5 |
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| 6 | +
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| 7 | +@article{nakajima2023counting, |
| 8 | + title={Counting Distinguishable RNA Secondary Structures}, |
| 9 | + author={Nakajima, Masaru and Smith, Andrew D}, |
| 10 | + journal={Journal of Computational Biology}, |
| 11 | + year={2023}, |
| 12 | + publisher={Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New~…}, |
| 13 | + pdf={nakajima-smith-2023-counting-distinguishable-rna-secondary-structures.pdf}, |
| 14 | + abstract={RNA secondary structures are essential abstractions for understanding |
| 15 | + spacial folding behaviors of those macromolecules. Many secondary structure |
| 16 | + algorithms involve a common dynamic programming setup to exploit the property |
| 17 | + that secondary structures can be decomposed into substructures. Dirks et al. |
| 18 | + noted that this setup cannot directly address an issue of distinguishability |
| 19 | + among secondary structures, which arises for classes of sequences that admit |
| 20 | + nontrivial symmetry. Circular sequences are among these. We examine the problem |
| 21 | + of counting distinguishable secondary structures. Drawing from elementary results |
| 22 | + in group theory, we identify useful subsets of secondary structures. |
| 23 | + We then extend an algorithm due to Hofacker et al. for computing the sizes of |
| 24 | + these subsets. This yields a cubic-time algorithm to count distinguishable |
| 25 | + structures compatible with a given circular sequence. Furthermore, this general |
| 26 | + approach may be used to solve similar problems for which the RNA structures of |
| 27 | + interest involve symmetries.} |
| 28 | +} |
| 29 | + |
| 30 | + |
| 31 | + |
6 | 32 | @article{nakajima2022development,
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7 | 33 | title={Development of an interactive code for quick data analyses between STOR-M tokamak experimental plasma discharges},
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8 | 34 | author={Nakajima, Masaru and Basu, Debjyoti and Melnikov, Alexander V and McColl, David and Xiao, Chijin},
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