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Search Results: 1 - 10 of 5615 matches for " Jeremy Chien "
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Platinum-Sensitive Recurrence in Ovarian Cancer: The Role of Tumor Microenvironment
Jeremy Chien,Rui Kuang,Charles Landen,Viji Shridhar
Frontiers in Oncology , 2013, DOI: 10.3389/fonc.2013.00251
Abstract: Despite several advances in the understanding of ovarian cancer pathobiology, in terms of driver genetic alterations in high-grade serous cancer, histologic heterogeneity of epithelial ovarian cancer, cell-of-origin for ovarian cancer, the survival rate from ovarian cancer is disappointingly low when compared to that of breast or prostate cancer. One of the factors contributing to the poor survival rate from ovarian cancer is the development of chemotherapy resistance following several rounds of chemotherapy. Although unicellular drug resistance mechanisms contribute to chemotherapy resistance, tumor microenvironment and the extracellular matrix (ECM), in particular, is emerging as a significant determinant of a tumor’s response to chemotherapy. In this review, we discuss the potential role of the tumor microenvironment in ovarian cancer recurrence and resistance to chemotherapy. Finally, we propose an alternative view of platinum-sensitive recurrence to describe a potential role of the ECM in the process.
Technology Development via Human Resources Exploitation: Evidence from Southeast Asian Countries  [PDF]
Shih-Chien Chien
Technology and Investment (TI) , 2012, DOI: 10.4236/ti.2012.34030
Abstract: The purpose of this article is to summarize and integrate the articles appearing in this special issue within the unique technology development (TD) and human resources (HR) of Southeast Asian countries. This paper examines how the synergy between TD and HR can lead to improved national economic performance. We proposed that better HR exploitation can sustain the capabilities of TD. Thus, the detail indexes are first evaluated with each category, which constructs the basic meanings of TD and HR. Consequently, the contexts of TD are clustered by different patterns with similar attributes in each nation. Each pattern can monitor the performance of HR in specific TD pattern. In this empirical study, we discover that the leading three countries (Singapore, Malaysia, and Thailand) have a strong positive rank correlation between TD and HR; In contrast, the rest of countries are poor rank correlation with regard to the two categories. These results mention that the level of TD, which depends on HR exploitation, is an important indicator of technological capability and even a proof of economic growth. We also examine the TD policies with strategic grid and offer a better road path of TD to follow, not only for those type countries to retune their policy, but also to parallel development in HR areas—such as the level of education upgrading, labor force environment improving, man power utilizing. Finally, Southeast Asian countries should calibrate feasible HR when use it to elaborate TD.
Network-based Survival Analysis Reveals Subnetwork Signatures for Predicting Outcomes of Ovarian Cancer Treatment
Wei Zhang,Takayo Ota,Viji Shridhar,Jeremy Chien,Baolin Wu,Rui Kuang
PLOS Computational Biology , 2013, DOI: 10.1371/journal.pcbi.1002975
Abstract: Cox regression is commonly used to predict the outcome by the time to an event of interest and in addition, identify relevant features for survival analysis in cancer genomics. Due to the high-dimensionality of high-throughput genomic data, existing Cox models trained on any particular dataset usually generalize poorly to other independent datasets. In this paper, we propose a network-based Cox regression model called Net-Cox and applied Net-Cox for a large-scale survival analysis across multiple ovarian cancer datasets. Net-Cox integrates gene network information into the Cox's proportional hazard model to explore the co-expression or functional relation among high-dimensional gene expression features in the gene network. Net-Cox was applied to analyze three independent gene expression datasets including the TCGA ovarian cancer dataset and two other public ovarian cancer datasets. Net-Cox with the network information from gene co-expression or functional relations identified highly consistent signature genes across the three datasets, and because of the better generalization across the datasets, Net-Cox also consistently improved the accuracy of survival prediction over the Cox models regularized by or . This study focused on analyzing the death and recurrence outcomes in the treatment of ovarian carcinoma to identify signature genes that can more reliably predict the events. The signature genes comprise dense protein-protein interaction subnetworks, enriched by extracellular matrix receptors and modulators or by nuclear signaling components downstream of extracellular signal-regulated kinases. In the laboratory validation of the signature genes, a tumor array experiment by protein staining on an independent patient cohort from Mayo Clinic showed that the protein expression of the signature gene FBN1 is a biomarker significantly associated with the early recurrence after 12 months of the treatment in the ovarian cancer patients who are initially sensitive to chemotherapy. Net-Cox toolbox is available at http://compbio.cs.umn.edu/Net-Cox/.
Model Based Data Transmission: Analysis of Link Budget Requirement Reduction  [PDF]
Jeremy Straub
Communications and Network (CN) , 2012, DOI: 10.4236/cn.2012.44032
Abstract: Communications capability can be a significant constraint on the utility of a spacecraft. While conventionally enhanced through the use of a larger transmitting or receiving antenna or through augmenting transmission power, communications capability can also be enhanced via incorporating more data in every unit of transmission. Model Based Transmission Reduction (MBTR) increases the mission utility of spacecraft via sending higher-level messages which rely on preshared (or, in some cases, co-transmitted) data. Because of this a priori knowledge, the amount of information contained in a MBTR message significantly exceeds the amount the amount of information in a conventional message. MBTR has multiple levels of operation; the lowest, Model Based Data Transmission (MBDT), utilizes a pre-shared lower-resolution data frame, which is augmented in areas of significant discrepancy with data from the higher-resolution source. MBDT is examined, in detail, herein and several approaches to minimizing the required bandwidth for conveying data required to conform to a minimum level of accuracy are considered. Also considered are ways of minimizing transmission requirements when both a model and change data required to attain a desired minimum discrepancy threshold must be transmitted. These possible solutions are compared to alternate transmission techniques including several forms of image compression.
Application of Model-Based Data Transmission Techniques to Gravitational Model Data  [PDF]
Jeremy Straub
Journal of Data Analysis and Information Processing (JDAIP) , 2013, DOI: 10.4236/jdaip.2013.13007
Abstract:

The transmission of scientific data over long distances is required to enable interplanetary science expeditions. Current approaches include transmitting all collected data or transmitting low resolution data to enable ground controller review and selection of data for transmission. Model-based data transmission (MBDT) seeks to increase the amount of knowledge conveyed per unit of data transmitted by comparing high-resolution data collected in situ to a pre-existing (or potentially co-transmitted) model. This paper describes the application of MBDT to gravitational data and characterizes its utility and performance. This is performed by applying the MBDT technique to a selection of gravitational data previously collected for the Earth and comparing the transmission requirements to the level required for raw data transmis-sion and non-application-aware compression. Levels of transmission reduction up to 31.8% (without the use maximum-error-thresholding) and up to 97.17% (with the use of maximum-error-thresholding) resulted. These levels significantly exceed what is possible with non-application-aware compression.

On the Internal Consistency of the Black-Scholes Option Pricing Model  [PDF]
Jeremy Berkowitz
Theoretical Economics Letters (TEL) , 2013, DOI: 10.4236/tel.2013.33032
Abstract:

We study the information structure implied by models in which the asset price is always risky and there are no arbitrage opportunities. Using the martingale representation of Harrison and Kreps [1], a claim takes its value from the stream of discounted expected payments. Equivalently, a pricing-kernel is sufficient to value the payment stream. If a price process is always risky, then either the payment or the discount factor must also be continually risky. This observation substantially complicates the valuation of contingent claims. Many classical option pricing formulas abstract from both risky dividends and risky discount rates. In order to value contingent claims, one of the assumptions must be abandoned.

Network-based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis
Wei Zhang,Jae-Woong Chang,Lilong Lin,Kay Minn,Baolin Wu,Jeremy Chien,Jeongsik Yong,Hui Zheng,Rui Kuang
Computer Science , 2014,
Abstract: High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA), the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification.
Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis
Wei Zhang?,Jae-Woong Chang?,Lilong Lin?,Kay Minn?,Baolin Wu?,Jeremy Chien,Jeongsik Yong?,Hui Zheng?,Rui Kuang
PLOS Computational Biology , 2015, DOI: 10.1371/journal.pcbi.1004465
Abstract: High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA), the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/.
Particle Swarm Optimization for Identifying Rainfall-Runoff Relationships  [PDF]
Chien-Ming Chou
Journal of Water Resource and Protection (JWARP) , 2012, DOI: 10.4236/jwarp.2012.43014
Abstract: Rainfall-runoff processes can be considered a single input-output system where the observed rainfall and runoff are inputs and outputs, respectively. Conventional models of these processes cannot simultaneously identify unknown structures of the system and estimate unknown parameters. This study applied a combinational optimization and Particle Swarm Optimization (PSO) for simultaneous identification of system structure and parameters of the rainfall-runoff relationship. Subsystems in proposed model are modeled using combinations of classic models. Classic models are used to transform the system structure identification problem into a combinational optimization and can be selected from those typically used in the hydrological field. A PSO is then applied to select the optimized subsystem model with the best data fit. The parameters are estimated simultaneously. The proposed model is tested in a case study of daily rainfall-runoff for the upstream Kee-Lung River. Comparison of the proposed method with simple linear model (SLM) shows that, in both calibration and validation, the PSO simulates the time of peak arrival more accurately compared to the SLM. Analytical results also confirm that the PSO accurately identifies the system structure and parameters of the rainfall-runoff relationship, which are a useful reference for water resource planning and application.
An Innovative Change in Technology Integration: Training Pre-Service Kindergarten Teachers to Be Courseware Designers  [PDF]
Chien-Heng Lin
Creative Education (CE) , 2012, DOI: 10.4236/ce.2012.37175
Abstract: This study focuses on exploring whether pre-service kindergarten teachers can be trained to be designers of digital courseware through learning a series of technology training courses in a limited period of time during their teacher training program. The results show that preschool pre-service teachers can become courseware designers and have the capacity to integrate and produce multimedia courseware in their classroom teaching. This study also demonstrates an adequate training course and pattern for training teachers to be courseware producers, which can be referenced by other teacher training institutions.
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