Noise in Genotype Selection Model

We study the steady state properties of a genotype selection model in presence of correlated Gaussian white noise. The effect of the noise on the genotype selection model is discussed. It is found that correlated noise can break the balance of gene selection and induce the phase transition which can makes us select one type gene haploid from a gene group.Comment: 8 pages, 4 figure

Current Reversals in a inhomogeneous system with asymmetric unbiased fluctuations

We present a study of transport of a Brownian particle moving in periodic symmetric potential in the presence of asymmetric unbiased fluctuations. The particle is considered to move in a medium with periodic space dependent friction. By tuning the parameters of the system, the direction of current exhibit reversals, both as a function of temperature as well as the amplitude of rocking force. We found that the mutual interplay between the opposite driving factors is the necessary term for current reversals.Comment: 9 pages, 7 figure

Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy

Background: It is necessary and essential to discovery protein function from the novel primary sequences. Wet lab experimental procedures are not only time-consuming, but also costly, so predicting protein structure and function reliably based only on amino acid sequence has significant value. TATA-binding protein (TBP) is a kind of DNA binding protein, which plays a key role in the transcription regulation. Our study proposed an automatic approach for identifying TATA-binding proteins efficiently, accurately, and conveniently. This method would guide for the special protein identification with computational intelligence strategies. Results: Firstly, we proposed novel fingerprint features for TBP based on pseudo amino acid composition, physicochemical properties, and secondary structure. Secondly, hierarchical features dimensionality reduction strategies were employed to improve the performance furthermore. Currently, Pretata achieves 92.92% TATA- binding protein prediction accuracy, which is better than all other existing methods. Conclusions: The experiments demonstrate that our method could greatly improve the prediction accuracy and speed, thus allowing large-scale NGS data prediction to be practical. A web server is developed to facilitate the other researchers, which can be accessed at http://server.malab.cn/preTata/

Computing Energy Performance of Building Density, Shape and Typology in Urban Context

AbstractThis paper aims to better understand the impact of urban context on building energy consumption. The factors of external shading, shapes generated from zoning ordinances, and local climate are examined concerning three main questions: (1) how density influences building energy consumption generally, (2) how a given density generates alternative building shapes that have different impacts on energy performance, and (3) how different typologies affect the energy-density relationship. To answer them, a series of parametric simulation experiments are conducted based on Martin and March's urban block structure. For more than 14,000 hypothetical models located at the Portland urban grid, the energy consumptions for the purposes of cooling and heating are simulated using AutoCAD script, MATLAB and Energy Plus 8. The results suggest that, different from the common perceptions, building energy consumptions for cooling and heating purposes do not always have a negative relationship with density. Instead, the energy consumption has a negative relationship with density before a turning point, and then the relationship changes to be positive. Also with the same FAR, different building cover ratio and typologies can lead to large variations in energy consumption. By the experiments on different building shapes generated by urban frit, it was found that even with the same typology, the building energy consumption can still vary significantly. Finally, the exploration of climate factors indicates that in both Portland and Atlanta, the findings are similar except that the energy-density relationship is weaker in Atlanta than in Portland

The Influence of ALS-associated MATR3 Toxicity on Cell Size in the Yeast Model

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease1. The pathology of ALS is described as the progressive degeneration of motor neurons that initially leads to atrophy of the voluntary muscles followed by the involuntary muscles1,2. Ultimately, the cause of death is pulmonary distress due to loss of function of the diaphragm2. Life expectancy after diagnosis is usually one year, and there are currently no cures or effective treatments for this fatal disease3. Approximately 90% of all ALS cases are sporadic meaning that the disease is developed randomly, while around 10% of the cases are familial meaning that the disease is passed down within a family3,4. Over 30 years, many genes have been identified and linked to the development of familial ALS. One of these genes is MATR3 which codes for Matrin-3, a nuclear matrix protein that binds to DNA and RNA with various roles in the nucleus5. Matrin-3 is normally found in the nucleus; however, when the gene is mutated, Matrin-3 is depleted from the nucleus and accumulates in clusters in the cytoplasm6. Matrin-3 associated toxicity is hypothesized to be either due to the loss of function of the protein in the nucleus or a gain of toxicity function in the cytoplasm leading to neuronal cell death. Furthermore, with increasing MATR3 toxicity in yeast, an increase in cell size was observed