Monte Carlo Methods for Rough Free Energy Landscapes: Population Annealing and Parallel Tempering

Parallel tempering and population annealing are both effective methods for simulating equilibrium systems with rough free energy landscapes. Parallel tempering, also known as replica exchange Monte Carlo, is a Markov chain Monte Carlo method while population annealing is a sequential Monte Carlo method. Both methods overcome the exponential slowing associated with high free energy barriers. The convergence properties and efficiency of the two methods are compared. For large systems, population annealing initially converges to equilibrium more rapidly than parallel tempering for the same amount of computational work. However, parallel tempering converges exponentially and population annealing inversely in the computational work so that ultimately parallel tempering approaches equilibrium more rapidly than population annealing.Comment: 10 pages, 3 figure

Identification of New SRF Binding Sites in Genes Modulated by SRF Over-Expression in Mouse Hearts

Background To identify in vivo new cardiac binding sites of serum response factor (SRF) in genes and to study the response of these genes to mild over-expression of SRF, we employed a cardiac-specific, transgenic mouse model, with mild over-expression of SRF (Mild-O SRF Tg). Methodology Microarray experiments were performed on hearts of Mild-O-SRF Tg at 6 months of age. We identified 207 genes that are important for cardiac function that were differentially expressed in vivo. Among them the promoter region of 192 genes had SRF binding motifs, the classic CArG or CArG-like (CArG-L) elements. Fifty-one of the 56 genes with classic SRF binding sites had not been previously reported. These SRF-modulated genes were grouped into 12 categories based on their function. It was observed that genes associated with cardiac energy metabolism shifted toward that of carbohydrate metabolism and away from that of fatty acid metabolism. The expression of genes that are involved in transcription and ion regulation were decreased, but expression of cytoskeletal genes was significantly increased. Using public databases of mouse models of hemodynamic stress (GEO database), we also found that similar altered expression of the SRF-modulated genes occurred in these hearts with cardiac ischemia or aortic constriction as well. Conclusion and significance SRF-modulated genes are actively regulated under various physiological and pathological conditions. We have discovered that a large number of cardiac genes have classic SRF binding sites and were significantly modulated in the Mild-O-SRF Tg mouse hearts. Hence, the mild elevation of SRF protein in the heart that is observed during typical adult aging may have a major impact on many SRF-modulated genes, thereby affecting Cardiac structure and performance. The results from our study could help to enhance our understanding of SRF regulation of cellular processes in the aged heart