Genetic algorithm solution for double digest problem

The strongly NP-Hard Double Digest Problem, for reconstructing the physical map of DNA sequence, in now using for efficient genotyping. Most of the existing methods are inefficient in tackling large instances due to the large search space for the problem which grows as a factorial function (a!)(b!) of the numbers a and b of the DNA fragments generated by the two restriction enzymes. Also, none of the existing methods are able to handle the erroneous data. In this paper, we develop a novel method based on genetic algorithm for solving this problem and it is adapted to handle the erroneous data. Our genetic algorithm is implemented and compared with the other well-known existing algorithms. The obtained results show the efficiency (speedup) of our algorithm with respect to the other methods, specially for erroneous data

ParaKavosh: A Parallel Algorithm for Finding Biological Network Motifs

Biological networks have recently gathered much attraction in finding their motifs. Motifs can be considered as subgraphs that occur in a particular network at significantly higher frequencies than random networks. The importance of this problem causes attention of improving the existing algorithms. As the runtime of an algorithm is an important aspect, applying parallel techniques is appropriate for better improvement. In this paper a parallel algorithm (ParaKavosh) for finding network motifs is presented. Our algorithm is tested on E. coli, S. cerevisiae, Homo sapiens and Rattus norvegicus networks. The cost optimality of the algorithm is also shown by analyzing the obtained results with an efficient sequential algorithm. The results show that the algorithm performs much better in terms of runtime

Fibrogenic stresses activate different mitogen-activated protein kinase pathways in renal epithelial, endothelial or fibroblast cell populations

Fibrogenic stresses promote progression of renal tubulointerstitial fibrosis, disparately affecting survival, proliferation and trans-differentiation of intrinsic renal cell populations through ill-defined biomolecular pathways. We investigated the effect of fibrogenic stresses on the activation of cell-specific mitogen-activated protein kinase (MAPK) in renal fibroblast, epithelial and endothelial cell populations. The relative outcomes (cell death, proliferation, trans -differentiation) associated with activation or inhibition of extracellular-regulated protein kinase (ERK) or stress activated/c-Jun N terminal kinase (JNK) were analysed in each renal cell population after challenge with oxidative stress (1 mmol/L H2O2), transforming growth factor-beta1 (TGF-beta1, 10 ng/mL) or tumour necrosis factor-alpha (TNF-alpha, 50 ng/mL) over 0-20 h. Apoptosis increased significantly in all cell types after oxidative stress (P < 0.05). In fibroblasts, oxidative stress caused the activation of ERK (pERK) but not JNK (pJNK). Inhibition of ERK by PD98059 supported its role in a fibroblast death pathway. In epithelial and endothelial cells, oxidative stress-induced apoptosis was preceded by early induction of pERK, but its inhibition did not support a pro-apoptotic role. Early ERK activity may be conducive to their survival or promote the trans -differentiation of epithelial cells. In epithelial and endothelial cells, oxidative stress induced pJNK acutely. Pretreatment with SP600125 (JNK inhibitor) verified its pro-apoptotic activity only in epithelial cells. Transforming growth factor-&beta;1 did not significantly alter mitosis or apoptosis in any of the cell types, nor did it alter MAPK activity. Tumor necrosis factor-&alpha; caused increased apoptosis with no associated change in MAPK activity. Our results demonstrate renal cell-specific differences in the activation of ERK and JNK following fibrotic insult, which may be useful for targeting excessive fibroblast proliferation in chronic fibrosis