The Forkhead box transcription factor FOXM1 is required for the maintenance of cell proliferation and protection against oxidative stress in human embryonic stem cells

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ChIP-Array 2: integrating multiple omics data to construct gene regulatory networks

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Real-time experimental implementation of predictive control schemes in a small-scale pasteurization plant

Model predictive control (MPC) is one of the most used optimization-based control strategies for large-scale systems, since this strategy allows to consider a large number of states and multi-objective cost functions in a straightforward way. One of the main issues in the design of multi-objective MPC controllers, which is the tuning of the weights associated to each objective in the cost function, is treated in this work. All the possible combinations of weights within the cost function affect the optimal result in a given Pareto front. Furthermore, when the system has time-varying parameters, e.g., periodic disturbances, the appropriate weight tuning might also vary over time. Moreover, taking into account the computational burden and the selected sampling time in the MPC controller design, the computation time to find a suitable tuning is limited. In this regard, the development of strategies to perform a dynamical tuning in function of the system conditions potentially improves the closed-loop performance. In order to adapt in a dynamical way the weights in the MPC multi-objective cost function, an evolutionary-game approach is proposed. This approach allows to vary the prioritization weights in the proper direction taking as a reference a desired region within the Pareto front. The proper direction for the prioritization is computed by only using the current system values, i.e., the current optimal control action and the measurement of the current states, which establish the system cost function over a certain point in the Pareto front. Finally, some simulations of a multi-objective MPC for a real multi-variable case study show a comparison between the system performance obtained with static and dynamical tuning.Peer ReviewedPostprint (author's final draft

Crime data mining: A general framework and some examples

A general framework for crime data mining that draws on experience gained with the Coplink project at the University of Arizona is presented. By increasing efficiency and reducing errors, this scheme facilitates police work and enables investigators to allocate their time to other valuable tasks.published_or_final_versio

Gender inequalities in employment and wage-earning among internal labour migrants in Chinese cities

© 2016 Min Qin et al. BACKGROUND: Recent trends show an unprecedented feminisation of migration in China, triggered by the increasing demand for cheap labour in big cities and the availability of women in the labour market. These trends corroborate the evidence that non-agricultural work and remittance from urban labour migrants have become the major sources of rural household income. OBJECTIVE: This paper investigates the extent of gender inequalities in job participation and wage earning among internal labour migrants in China. We hypothesize that female migrants in cities are economically more disadvantaged than male migrants in the job market. METHODS: We use data from the 2010 National Migrant Dynamics Monitoring Survey conducted in 106 cities representing all 31 provinces and geographic regions. The study applies the standard Heckman two-step Probit-OLS method to model job participation and wage- earning, separately for 59,225 males and 41,546 females aged 16-59 years, adjusting for demographic and social characteristics and potential selection effects. RESULTS: Female migrants have much lower job-participation and wage-earning potential than male migrants. Male migrants earn 26% higher hourly wages than their female counterparts. Decomposition analysis confirms potential gender discrimination, suggesting that 88% of the gender difference in wages (or 12% of female migrant wage) is due to discriminatory treatment of female migrants in the Chinese job market. Migrants with rural hukou status have a smaller chance of participation in the job market and they earn lower wages than those with urban hukou, regardless of education advantage. CONCLUSIONS: There is evidence of significant female disadvantage among internal labour migrants in the job market in Chinese cities. Household registration by urban and rural areas, as controlled by the hukou status, partly explains the differing job participation and wage earning among female labour migrants in urban China

An adaptive control system to deliver Interactive Virtual Environment content to handheld devices

Wireless communication advances have enabled emerging video streaming applications to mobile handheld devices. For example, it is possible to display and interact with complex 3D virtual environments on mobile devices that don't have enough computational and storage capabilities (e.g. smart phones, PDAs) through remote rendering techniques, where a server renders 3D data and streams the corresponding image flow to the client. However, due to fluctuations in bandwidth characteristics and limited mobile device CPU capabilities, it is extremely challenging to design effective systems for streaming interactive multimedia over wireless networks. This paper presents a novel approach based on a controller that can automatically adjust streaming parameters basing on feedback measures from the client device. Experimental results prove the effectiveness of the proposed solution in coping with bandwidth changes, thus providing high Quality of Service (QoS) in remote visualization

ProteoMirExpress: inferring microRNA-centered regulatory networks from high-throughput proteomic and transcriptome data

MicroRNAs (miRNAs) regulate gene expression through translational repression and RNA degradation. Recently developed high-throughput proteomic methods measure gene expression changes at protein levels, and therefore can reveal the direct effects of miRNAs’ translational repression. Here, we present a web server, ProteoMirExpress that integrates proteomic and mRNA expression data together to infer miRNA-centered regulatory networks. With both high throughput data from the users, ProteoMirExpress is able to discover not only miRNA targets that have mRNA decreased, but also subgroups of targets whose proteins are suppressed but mRNAs are not significantly changed or whose mRNAs are decreased but proteins are not significantly changed, which were usually ignored by most current methods. Furthermore, both direct and indirect targets of miRNAs can be detected. Therefore ProteoMirExpress provides more comprehensive miRNA-centered regulatory networks. We use several published data to assess the quality of our inferred networks and prove the value of our server. ProteoMirExpress is available at http://jjwanglab.org/ProteoMirExpress, with free access to academic users.postprin

PTHGRN: unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data

Interactions among transcriptional factors (TFs), cofactors and other proteins or enzymes can affect transcriptional regulatory capabilities of eukaryotic organisms. Post-translational modifications (PTMs) cooperate with TFs and epigenetic alterations to constitute a hierarchical complexity in transcriptional gene regulation. While clearly implicated in biological processes, our understanding of these complex regulatory mechanisms is still limited and incomplete. Various online software have been proposed for uncovering transcriptional and epigenetic regulatory networks, however, there is a lack of effective web-based software capable of constructing underlying interactive organizations between post-translational and transcriptional regulatory components. Here, we present an open web server, post-translational hierarchical gene regulatory network (PTHGRN) to unravel relationships among PTMs, TFs, epigenetic modifications and gene expression. PTHGRN utilizes a graphical Gaussian model with partial least squares regression-based methodology, and is able to integrate protein-protein interactions, ChIP-seq and gene expression data and to capture essential regulation features behind high-throughput data. The server provides an integrative platform for users to analyze ready-to-use public high-throughput Omics resources or upload their own data for systems biology study. Users can choose various parameters in the method, build network topologies of interests and dissect their associations with biological functions. Application of the software to stem cell and breast cancer demonstrates that it is an effective tool for understanding regulatory mechanisms in biological complex systems. PTHGRN web server is publically available at web site http://www.byanbioinfo.org/pthgrn.published_or_final_versio

An integrative method to decode regulatory logics in gene transcription

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF-TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.published_or_final_versio