Meta-analysis for pathway enrichment analysis and biomarker detection when combining multiple genomic studies

This thesis focuses on applying meta-analysis methods for combining genomic studies on biomarker detection and pathway enrichment analysis. DNA microarray technology has been maturely developed in the past decade and led to an explosion on publicly available microarray data sets. However, the noisy nature of DNA microarray technology results in low reproducibility across microarray studies. Therefore, it is of interest to apply meta-analysis to microarray data to increase the reliability and robustness of results from individual studies. Currently most meta-analysis methods for combining genomic studies focus on biomarker detection, and meta-analysis for pathway analysis has not been systematically pursued. We investigated two natural approaches of meta-analysis for pathway enrichment (MAPE) by combining statistical significance across studies at the gene level (MAPE_G) or at the pathway level (MAPE_P). Simulation results showed increased statistical power of both approaches and their complementary advantages under different scenarios. We also developed an integrated method (MAPE_I) that incorporates advantages of both approaches. Applications to real data on drug response of a breast cancer cell line, lung and prostate cancer tissues were evaluated to compare the performance of the different methods. MAPE_P has the general advantage of not requiring gene matching across studies. When MAPE_G and MAPE_P show complementary advantages, the integrated version MAPE_I is recommended. A software package named MetaPath, was implemented to perform the MAPE analysis. In addition to developing MAPE methods, we also applied meta-analysis approach to chemotherapy research to discover robust biomarkers and multi-drug response genes, which have prognostic value and the potential of identifying new therapeutic targets

Is It the Beginning of the Era of the Rule of the Constitution? Reinterpreting China\u27s First Constitutional Case

The subject of this article is the so-called first constitutional case in China. The Qi Yuling case is, in a sense, the very first time since the foundation of the People\u27s Republic of China that constitutional provisions have been directly invoked by the Supreme People\u27s Court in a civil lawsuit to protect a citizen\u27s right to receive education, one of the fundamental rights protected by the Constitution. The Qi Yuling case, therefore, has given rise to much discussion on issues of judicial interpretation of the Constitution and the Constitution\u27s application in the private domain, as well as the institution of judicial review in China. Professor Shen\u27s article discusses the ramifications of Qi Yuling, specifically centering on the theory of constitutional justiciability from a comparative perspective, and the prospects of constitutional justiciability in China

Lessons from China\u27s Response to COVID-19: Shortcomings, Successes, and Prospects for Reform in China\u27s Regulatory State

China’s response to COVID-19 offers a case study of law, the regulatory state and governance in China. The costly delay in the initial response reflected distinctive features of the Chinese system, including perverse incentives local-level officials face to try to cover up problems, fragmentated institutions and rules, and politically weak public health bureaucracies. After the initial shortcomings, China’s largely successful efforts to contain the pandemic also reflected defining features of the Chinese system, including a highly capable, centralized and authoritarian party-state that could mobilize vast resources, coordinate across fractious institutions, create ad hoc government and party leadership bodies, and deploy highly pervasive, intrusive, and restrictive low-tech and high-tech means to monitor and control citizens’ behavior. Prospects for post-COVID reforms to address revealed shortcomings face challenges from structural features of China’s governance, pervasive difficulties in policy implementation, and the regime’s reluctance to adopt more transformative laws that would be more liberal in content and increase party-state accountability

Detecting a set of entanglement measures in an unknown tripartite quantum state by local operations and classical communication

We propose a more general method for detecting a set of entanglement measures, i.e. negativities, in an \emph{arbitrary} tripartite quantum state by local operations and classical communication. To accomplish the detection task using this method, three observers, Alice, Bob and Charlie, do not need to perform the partial transposition maps by the structural physical approximation; instead, they are only required to collectively measure some functions via three local networks supplemented by a classical communication. With these functions, they are able to determine the set of negativities related to the tripartite quantum state.Comment: 16 pages, 2 figures, revte

Trust model for certificate revocation in Ad hoc networks

In this paper we propose a distributed trust model for certificate revocation in Adhoc networks. The proposed model allows trust to be built over time as the number of interactions between nodes increase. Furthermore, trust in a node is defined not only in terms of its potential for maliciousness, but also in terms of the quality of the service it provides. Trust in nodes where there is little or no history of interactions is determined by recommendations from other nodes. If the nodes in the network are selfish, trust is obtained by an exchange of portfolios. Bayesian networks form the underlying basis for this model

Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

Artificial bee colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance

Automatic record extraction for the World Wide Web

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.Includes bibliographical references (p. 149-152).As the amount of information on the World Wide Web grows, there is an increasing demand for software that can automatically process and extract information from web pages. Despite the fact that the underlying data on most web pages is structured, we cannot automatically process these web sites/pages as structured data. We need robust technologies that can automatically understand human-readable formatting and induce the underlying data structures. In this thesis, we are focused on solving a specific facet of this general unsupervised web information extraction problem. Structured data can appear in diverse forms from lists to trees to even semi-structured graphs. However, much of the information on the web appears in a flat format we call "records". In this work, we will describe a system, MURIEL, that uses supervised and unsupervised learning techniques to effectively extract records from webpages.by Yuan Kui Shen.S.M