We present, in this paper, a detailed translation from algorithms implemented on a standard model of parallel computation — the CREW PRAM — to DNA-based methods. Our translation is efficient in the following sense: if A is a PRAM algorithm using P (n) processors, S (n) space, and taking T (n) time then the total volume of DNA used is O ( P (n) T (n) S (n) logS (n) ); furthermore, the total comp...

We present a randomized DNA algorithm for k-SAT based on the classical algorithm of Paturi et al. [8]. For an n-variable, m-clause instance of k-SAT (m > n), our algorithm finds a satisfying assignment, assuming one exists, with probability 1−e−α, in worst-case time O(kmn) and space O(2(1− 1 k ). This makes it the most space-efficient DNA k-SAT algorithm for k > 3 and k < n/ logα (i.e. the clau...

Biocomputing, especially DNA, computing has got great development. It is widely used in information security. In this paper, a novel algorithm of reversible data hiding based on DNA computing is proposed. Inspired by the algorithm of histogram modification, which is a classical algorithm for reversible data hiding, we combine it with DNA computing to realize this algorithm based on biological t...

Aimed to address the defects of the large mean square error (MSE), and the slow convergence speed in equalizing the multi-modulus signals of the constant modulus algorithm (CMA), a multi-modulus algorithm (MMA) based on global artificial fish swarm (GAFS) intelligent optimization of DNA encoding sequences (GAFS-DNA-MMA) was proposed. To improve the convergence rate and reduce the MSE, this prop...

Background and Aims: New advances in the use of cell-free fetal DNA (cffDNA) in maternal plasma of pregnant women has provided the possibility of applying cffDNA in prenatal diagnosis as a non-invasive method. One of the applications of prenatal diagnosis is fetal gender determination. Early prenatal determination of fetal sex is required for pregnant women at risk of X-linked and some endocrin...

In this paper we propose a model of encoding data into DNA strands so that this data can be used in the simulation of a genetic algorithm based on molecular operations. DNA computing is an impressive computational model that needs algorithms to work properly and efficiently. The first problem when trying to apply an algorithm in DNA computing must be how to codify the data that the algorithm wi...

We demonstrate how to solve constraint satisfaction problems (CSPs) with DNA computing. Assuming that DNA operations can be faulty, we estimate error probability of our algorithm. We show that for any k-CSP, there is a polynomial-time DNA algorithm with bounded probability of error. Thus, k-CSPs belong to a DNA analogue of BPP.

This study provides an effective design of search technique of a distributed bioinformatics computing system for analysis of DNA sequences using OPTSDNA algorithm. This system could be used for disease detection, criminal forensic analysis, gene prediction, genetic system and protein analysis. Different types of distributed algorithms for the search and identification for DNA segments and repea...

Identifying the promoter regions play a vital role in understanding human genes. This paper presents a new cellular automata based text clustering algorithm for identifying these promoter regions in genomic DNA. Experimental results confirm the applicability of cellular automata based text clustering algorithm for identifying these regions. We also note an increase in accuracy of fining these p...

We present a randomized DNA algorithm for k SAT based on the classical algorithm of Paturi et al For an n variable m clause instance of k SAT m n our algorithm nds a satisfying assignment assuming one exists with probability e in worst case time O k mn and space O k n log This makes it the most space e cient DNA k SAT algo rithm for k and k n log i e the clause size is small compared to the num...