TFBSTools: an R/bioconductor package for transcription factor binding site analysis.

Summary: The ability to efficiently investigate transcription factor binding sites (TFBSs) genome-wide is central to computational studies of gene regulation. TFBSTools is an R/Bioconductor package for the analysis and manipulation of TFBSs and their associated transcription factor profile matrices. TFBStools provides a toolkit for handling TFBS profile matrices, scanning sequences and alignments including whole genomes, and querying the JASPAR database. The functionality of the package can be easily extended to include advanced statistical analysis, data visualization and data integration. Availability and implementation: The package is implemented in R and available under GPL-2 license from the Bioconductor website (http://bioconductor.org/packages/TFBSTools/). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration Strategies

We revisit the stochastic limited-memory BFGS (L-BFGS) algorithm. By proposing a new framework for the convergence analysis, we prove improved convergence rates and computational complexities of the stochastic L-BFGS algorithms compared to previous works. In addition, we propose several practical acceleration strategies to speed up the empirical performance of such algorithms. We also provide theoretical analyses for most of the strategies. Experiments on large-scale logistic and ridge regression problems demonstrate that our proposed strategies yield significant improvements vis-\`a-vis competing state-of-the-art algorithms

Experimental investigation on thermal comfort model between local thermal sensation and overall thermal sensation

To study the human local and overall thermal sensations, a series of experiments under various conditions were carried out in a climate control chamber. The adopted analysis method considered the effect of the weight coefficient of local average skin temperature and density of the cold receptors’ distribution in different local body areas. The results demonstrated that the thermal sensation of head, chest, back and hands is warmer than overall thermal sensation. The mean thermal sensation votes of those local areas were more densely distributed. In addition, the thermal sensation of arms, tight and calf was colder than the overall thermal sensation, which pronounced that thermal sensation votes were more dispersed. The thermal sensation of chest and back had a strong linear correlation with overall thermal sensation. Considering the actual scope of air-conditioning regulation, the human body was classified into three local parts: a) head, b) upper part of body and c) lower part of body. The prediction model of both the three-part thermal sensation and overall thermal sensation was developed. Weight coefficients were 0.21, 0.60 and 0.19 respectively. The model provides scientist basis for guiding the sage installation place of the personal ventilation system to achieve efficient energy use