Prediction of Water Consumption in Hospitals Based on a Modified Grey GM (0, 1∣sin) Model of Oscillation Sequence: The Example of Wuhan City

Water shortage is one of the main factors limiting urban construction and development. Scientific forecasting of water consumption is an important approach for the rational allocation of water resources. Taking the hospitals in Wuhan City as an example and basing the analysis on the characteristics of actual water consumption, we proposed a modified grey GM (0, 1∣sin) model of oscillation sequence. Using the grey theory, the variable weight-strengthening buffer operator (VWSBO) was introduced into this model to weaken the interference of the disturbance term on the data sequence. The actual quarterly total water consumption data for hospitals in Wuhan City during the period from 2010 to 2012 were used to verify the effectiveness and practicality of this modified grey GM (0, 1∣sin) model in predicting water consumption. In terms of the model’s fitting performance, the mean absolute percentage error (MAPE) of the modified model was 3.77%, indicating a higher prediction accuracy than the traditional grey GM (0, 1∣sin) model of oscillation sequences. Therefore, the modified grey GM (0, 1∣sin) model we established in this study can provide a scientific reference for administrative departments to forecast water consumption

A Poisson mixture model to identify changes in RNA polymerase II binding quantity using high-throughput sequencing technology

We present a mixture model-based analysis for identifying differences in the distribution of RNA polymerase II (Pol II) in transcribed regions, measured using ChIP-seq (chromatin immunoprecipitation following massively parallel sequencing technology). The statistical model assumes that the number of Pol II-targeted sequences contained within each genomic region follows a Poisson distribution. A Poisson mixture model was then developed to distinguish Pol II binding changes in transcribed region using an empirical approach and an expectation-maximization (EM) algorithm developed for estimation and inference. In order to achieve a global maximum in the M-step, a particle swarm optimization (PSO) was implemented. We applied this model to Pol II binding data generated from hormone-dependent MCF7 breast cancer cells and antiestrogen-resistant MCF7 breast cancer cells before and after treatment with 17β-estradiol (E2). We determined that in the hormone-dependent cells, ~9.9% (2527) genes showed significant changes in Pol II binding after E2 treatment. However, only ~0.7% (172) genes displayed significant Pol II binding changes in E2-treated antiestrogen-resistant cells. These results show that a Poisson mixture model can be used to analyze ChIP-seq data

Genome-wide analysis of alternative promoters of human genes using a custom promoter tiling array

<p>Abstract</p> <p>Background</p> <p>Independent lines of evidence suggested that a large fraction of human genes possess multiple promoters driving gene expression from distinct transcription start sites. Understanding which promoter is employed in which cellular context is required to unravel gene regulatory networks within the cell.</p> <p>Results</p> <p>We have developed a custom microarray platform that tiles roughly 35,000 alternative putative promoters from nearly 7,000 genes in the human genome. To demonstrate the utility of this array platform, we have analyzed the patterns of promoter usage in 17β-estradiol (E2)-treated and untreated MCF7 cells and show widespread usage of alternative promoters. Most intriguingly, we show that the downstream promoter in E2-sensitive multiple promoter genes tends to be very close to the 3'-terminus of the gene, suggesting exotic mechanisms of expression regulation in these genes.</p> <p>Conclusion</p> <p>The usage of alternative promoters greatly multiplies the transcriptional complexity available within the human genome. The fact that many of these promoters are incapable of driving the synthesis of a meaningful protein-encoding transcript further complicates the story.</p

Analysis of Four Avermectin Drugs Residual Levels in Rose Flower Cakes and Chronic Dietary Risk Assessment

To understand whether there was a drug residue in the rose flower cake, and whether there was a risk of chronic dietary intake. In this paper, the residues of four avermectins in rose flower cake were detected, the residual levels of drug residues were analyzed, and the risk of chronic dietary intake was evaluated. The four drugs were avermectin, doramectin, acetylamineavermectin and ivermectin. A total of 43 rose flower cake samples were collected, and the optimized QuEChERS method was used to pre-treat the samples. The residue levels of the four compounds were determined by high performance liquid chromatography-tandem mass spectrometry, and their chronic dietary intake risk assessment and risk rank were performed. Results show that the four kinds of abamectin drugs line of correlation coefficient were greater than 0.99, the detection limit of the range of 0.1~0.7 µg/kg, recovery range of 94.97%~102.09%. Only avermectin was detected in the 4 target compounds, the detection rate was 79%, and residual range of 1.89~4.58 µg/kg. The food safety index analysis (IFS) of the four drugs was 1.3×10−3 for avermectin, 1.0×10−4 for doramectin, 1.7×10−6 for acetylavermectin, and 1.2×10−5 for ivermectin. Risk assessment on four kinds of target compounds, and to the risk of ordering, total four drugs were less than 50. This indicated that the residual level of avermectins in rose flower cakes was not high at present, and the risk was low. It was suggested that it should be included in the registration list of pesticides and the corresponding limit standards should be established

Size and shape analysis of error-prone shape data

We consider the problem of comparing sizes and shapes of objects when landmark data are prone to measurement error. We show that naive implementation of ordinary Procrustes analysis that ignores measurement error can compromise inference. To account for measurement error, we propose the conditional score method for matching configurations, which guarantees consistent inference under mild model assumptions. The effects of measurement error on inference from naive Procrustes analysis and the performance of the proposed method are illustrated via simulation and application in three real data examples. Supplementary materials for this article are available online

Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

<p>Abstract</p> <p>Background</p> <p>Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks.</p> <p>Results</p> <p>In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.</p> <p>We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells.</p> <p>Conclusions</p> <p>Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.</p

Diverse histone modifications on histone 3 lysine 9 and their relation to DNA methylation in specifying gene silencing

<p>Abstract</p> <p>Background</p> <p>Previous studies of individual genes have shown that in a self-enforcing way, dimethylation at histone 3 lysine 9 (dimethyl-H3K9) and DNA methylation cooperate to maintain a repressive mode of inactive genes. Less clear is whether this cooperation is generalized in mammalian genomes, such as mouse genome. Here we use epigenomic tools to simultaneously interrogate chromatin modifications and DNA methylation in a mouse leukemia cell line, L1210.</p> <p>Results</p> <p>Histone modifications on H3K9 and DNA methylation in L1210 were profiled by both global CpG island array and custom mouse promoter array analysis. We used chromatin immunoprecipitation microarray (ChIP-chip) to examine acetyl-H3K9 and dimethyl-H3K9. We found that the relative level of acetyl-H3K9 at different chromatin positions has a wider range of distribution than that of dimethyl-H3K9. We then used differential methylation hybridization (DMH) and the restriction landmark genome scanning (RLGS) to analyze the DNA methylation status of the same targets investigated by ChIP-chip. The results of epigenomic profiling, which have been independently confirmed for individual loci, show an inverse relationship between DNA methylation and histone acetylation in regulating gene silencing. In contrast to the previous notion, dimethyl-H3K9 seems to be less distinct in specifying silencing for the genes tested.</p> <p>Conclusion</p> <p>This study demonstrates in L1210 leukemia cells a diverse relationship between histone modifications and DNA methylation in the maintenance of gene silencing. Acetyl-H3K9 shows an inverse relationship between DNA methylation and histone acetylation in regulating gene silencing as expected. However, dimethyl-H3K9 seems to be less distinct in relation to promoter methylation. Meanwhile, a combination of epigenomic tools is of help in understanding the heterogeneity of epigenetic regulation, which may further our vision accumulated from single-gene studies.</p

Genome-wide mapping of RNA Pol-II promoter usage in mouse tissues by ChIP-seq

Alternative promoters that are differentially used in various cellular contexts and tissue types add to the transcriptional complexity in mammalian genome. Identification of alternative promoters and the annotation of their activity in different tissues is one of the major challenges in understanding the transcriptional regulation of the mammalian genes and their isoforms. To determine the use of alternative promoters in different tissues, we performed ChIP-seq experiments using antibody against RNA Pol-II, in five adult mouse tissues (brain, liver, lung, spleen and kidney). Our analysis identified 38 639 Pol-II promoters, including 12 270 novel promoters, for both protein coding and non-coding mouse genes. Of these, 6384 promoters are tissue specific which are CpG poor and we find that only 34% of the novel promoters are located in CpG-rich regions, suggesting that novel promoters are mostly tissue specific. By identifying the Pol-II bound promoter(s) of each annotated gene in a given tissue, we found that 37% of the protein coding genes use alternative promoters in the five mouse tissues. The promoter annotations and ChIP-seq data presented here will aid ongoing efforts of characterizing gene regulatory regions in mammalian genomes

Data analytics between human-machine interaction

There has been an increasing trend of big data analytic in the e-commerce industry in the recent years. In this information age, there had been am explosive growth in the size of data generated. Data growth influenced by ever cheaper computing power and commonness of the internet. This has caused a paradigm shift in the E-commerce sector with data collected now not seen as a byproduct of the business, but as assets to provide insights and possibly even predict trends in customers’ purchasing patterns. This report provides an overview of studying data analytic in the E-commerce, discussing possible customer trends and purchasing behavior. Further this report will present why data analytic is helping retailers to stay in trend of a new breed of customer. Lastly, the report will identify how data analytic improve business strategies or activities and challenges faced studying the data set.Bachelor of Engineerin

Quantifying the seasonal contribution of coupling urban land use types on Urban Heat Island using Land Contribution Index: A case study in Wuhan, China

Urban Heat Island (UHI) is an urban climate phenomenon which is expected to respond to the change of urban environment and land use types in the future. UHI is closely related to urbanization and urban land use changes, since the expansion of impervious surface greatly affects the thermodynamic properties of the underlying surface. New ways to measure and assess the inner quantitative relationship between land use types and UHI are thus critical to answer the questions in this field. This paper presents a new method for better quantifying the contribution of respective land use type on UHI with the proposed Land Contribution Index (LCI). Seasonal thermal contribution of each land use type to UHI can be calculated based on the difference in average temperatures between a certain land use type and the entire study area. The experiment was conducted in Wuhan, China during 2005–2015 when the city was in rapid urbanization. Results indicate that the UHI effect has become more prominent in areas of rapid urbanization in the study area, and strong UHI (including high level and extremely high level) accounted for 8.56% of the whole region in 2015 compared with 2005 (3.35%). In addition, through analyzing temporal and spatial patterns of the distribution of UHI, increasing UHI areas were mainly distributed in the central and western parts of the city during 2005–2009, and then migrated to the surroundings from 2011. Furthermore, based on the calculation of LCI, construction land had the highest contribution to the UHI effect in the summer of 2015, while water body had conversely the lowest contribution to the UHI effect in the spring of 2005. Urban green space including forest land and agricultural land had intensively negative contributions to the UHI effect, and their alleviating functions on the thermal environment were less remarkable in winter