A Survey of Compute Intensive Algorithms for Ribo Nucleic Acids Structural Detection

Abstract

<b>Problem statement:</b> Finding an accurate RNA structural alignment from primary sequence due to it is time consuming and computationally NP-hard problem is a major bioinformatics challenge. According to our investigation majority of current researches were concerned on achieving faster execution time, improving space complexity and better cache management. Recently one research introduced cache-efficient Chip Multiprocessor (CMP) algorithms with good speed-up to exploit parallelism in detection the critical path length. Our contribution in this article was a comprehensive survey of methods for solving RNA secondary structure prediction with Pseudoknots (PK) and sequence alignment in bioinformatics. The aim was to highlight the challenges related issues which would provide sufficient information to assist the new coming researchers in this field as well as a good reference guide for bioinformatics professionals. <b>Approach:</b> We computed various algorithms that predicted an RNA molecules secondary structure from primary sequence, without pseudoknots from one side and pseudoknotted RNA secondary structure in the other side. Furthermore, we also reviewed and compared in two tables the methods that developed for RNA structural predictions. <b>Results:</b> Our findings of this survey confirmed that Dynamic Programming (DP) method via CMP algorithms can be used to predict the RNA secondary structure with simple PK and it gives good results. <b>Conclusion:</b> The methods for predicting RNA's structural are coming in two groups: Firstly, pseudoknotted RNA structural problem is computationally complex and secondly, common methods significantly gave not accurate enough results for predicting pseudoknotted RNA

A Comparative Taxonomy of Parallel Algorithms for RNA Secondary Structure Prediction

“…In this paper, the researchers discussed and compared these parallel RNA methods, as shown in Table 3. They have discussed in 22 an intensive RNA detection algorithms, as a first phase of the RNA secondary research in a Bioinformatics domain. The authors classified and compared the RNA approaches in two main groups and they presented the results in the two tables.…”

“…Next, the researchers converged these RNA prediction methods, as shown in Table 1, which was adapted and extracted from. 22 This table included the most well-known existing RNA sequential prediction methods and approaches that have been produced lately to predict RNA secondary structures.…”

Use of the “DNAChecker” Algorithm for Improving Bioinformatics Research

“…Due to the advancements in computational analysis for biological data, the Python programing language can be implemented to script a code that allows the sequence to be read prior to BLAST analysis and determine the quality of the sequence based on a uniform criterion [6], [7]. Several computational algorithms for large-scale DNA analysis have been implemented, but not for a specialized task as explained in this research [8]- [10]. In various nucleotide-reading computer-based programs, uncertain nucleotides within a sequence are defined by the letter "N." The more the occurrences of "N" within a given nucleotide sequence, the "uglier" the sequence.…”

Using Threads to Overcome Synchronization Delays in Parallel Multiple Progressive Alignment Algorithms

“…One method that is extensively applied is the progressive alignment of multiple sequences. Several multiple sequence alignment algorithms have been proposed but they present, usually, a high computational complexity (Rashid et al, 2009). Among these algorithms a major category includes the progressive approach.…”