scholarly journals A dynamic programming algorithm for finding alternative RNA secondary structure

1986 ◽  
Vol 14 (1) ◽  
pp. 299-315 ◽  
Author(s):  
Arthur L. Williams ◽  
Ignacio Tinoco
Keyword(s):  
Dynamic Programming ◽  
Secondary Structure ◽  
Rna Secondary Structure ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm

DSARna: RNA Secondary Structure Alignment Based on Digital Sequence Representation

2020 ◽  
Vol 23 ◽  
Author(s):  
Longjian Gao ◽  
Chengzhen Xu ◽  
Wangan Song ◽  
Feng Xiao ◽  
Xiaomin Wu ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
High Throughput Sequencing ◽  
Structural Information ◽  
Dynamic Programming Algorithm ◽  
Structure Alignment ◽  
Programming Algorithm ◽  
Structure Information ◽  
Alignment Algorithms

Background: With increasing applications and development of high-throughput sequencing, knowledge of the primary structure of RNA has expanded exponentially. Moreover, the function of RNA is determined by the secondary or higher RNA structure, and similar structures are related to similar functions, such as the secondary clover structure of tRNA. Therefore, RNA structure alignment is an important subject in computational biology and bioinformatics to accurately predict function. However, the traditional RNA structure alignment algorithms have some drawbacks such as high complexity and easy loss of secondary structure information. Objective: To study RNA secondary structure alignment according to the shortcomings of existing secondary structure alignment algorithms and the characteristics of RNA secondary structure. Method: We propose a new digital sequence RNA structure representation algorithm named “DSARna” . Then based on a dynamic programming algorithm, the scoring matrix and binary path matrix are simultaneously constructed. The backtracking path is identified in the path matrix, and the optimal result is predicted according to the path length. Conclusions: Upon comparison with the existing SimTree algorithm through experimental analysis, the proposed method showed higher accuracy and could ensure that the structural information is not easily lost in terms of improved specificity, sensitivity, and the Matthews correlation coefficient.

RANKING VALID TOPOLOGIES OF THE SECONDARY STRUCTURE ELEMENTS USING A CONSTRAINT GRAPH

2011 ◽  
Vol 09 (03) ◽  
pp. 415-430 ◽  
Author(s):  
KAMAL AL NASR ◽  
DESH RANJAN ◽  
MOHAMMAD ZUBAIR ◽  
JING HE
Keyword(s):  
Dynamic Programming ◽  
Secondary Structure ◽  
Protein Complexes ◽  
Dynamic Programming Algorithm ◽  
Weighted Graph ◽  
Minimum Cost ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Constraint Graph ◽  
Density Maps

Electron cryo-microscopy is a fast advancing biophysical technique to derive three-dimensional structures of large protein complexes. Using this technique, many density maps have been generated at intermediate resolution such as 6–10 Å resolution. Although it is challenging to derive the backbone of the protein directly from such density maps, secondary structure elements such as helices and β-sheets can be computationally detected. Our work in this paper provides an approach to enumerate the top-ranked possible topologies instead of enumerating the entire population of the topologies. This approach is particularly practical for large proteins. We developed a directed weighted graph, the topology graph, to represent the secondary structure assignment problem. We prove that the problem of finding the valid topology with the minimum cost is NP hard. We developed an O(N2 2N) dynamic programming algorithm to identify the topology with the minimum cost. The test of 15 proteins suggests that our dynamic programming approach is feasible to work with proteins of much larger size than we could before. The largest protein in the test contains 18 helical sticks detected from the density map out of 33 helices in the protein.

scholarly journals A new entropy model for RNA: part IV, The Minimum Free Energy (mFE) and the thermodynamically most-probable folding pathway (TMPFP)

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Wayne Dawson ◽  
Gota Kawai
Keyword(s):  
Free Energy ◽  
Dynamic Programming ◽  
Secondary Structure ◽  
Dynamic Programming Algorithm ◽  
Minimum Free Energy ◽  
Programming Algorithm ◽  
Folding Pathway ◽  
Rna Sequences ◽  
Entropy Model ◽  
Suboptimal Structure

Here we discuss four important questions (1) how can we be sure that the thermodynamically most-probable folding-pathway yields the minimum free energy for secondary structure using the dynamic programming algorithm (DPA) approach, (2) what are its limitations, (3) how can we extend the DPA to find the minimum free energy with pseudoknots, and finally (4) what limitations can we expect to find in a DPA approach for pseudoknots. It is our supposition that some structures cannot be fit uniquely by the DPA, but may exist in real biology situations when disordered regions in the biomolecule are necessary. These regions would be identifiable by using suboptimal structure analysis. This grants us some qualitative tools to identify truly random RNA sequences, because such are likely to have greater degeneracy in their thermodynamically most-probable folding-pathway.

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