Pengaruh Kegunaan, Kualitas Informasi dan Kualitas Interaksi Layanan Website Perpustakaan Universitas Riau terhadap Kepuasan Pengguna (Studi pada Mahasiswa Universitas Riau dengan Menggunakan Metode Webqual 4.0)

Internet as a new media, nowadays, has function in providing the information without limit. Internet usage in education especially use in the college can support the academicians to gather the information from a website that specially designed by the University. In this research the writer use a quantitative descriptive approach that aims to search the influence of the usability, the information quality and the service interaction quality of Riau University librarys website regarding to the user satisfaction using a questionnaire as a tool in collecting data that the queries formed by instrument of method named WebQual 4.0. Population in this research is all of students of Riau University totally sample to 100 correspondents which are selected by using a combination between cluster sampling and accidental sampling technique. The writer uses a multiple linear regression in analyzing data and a statistical product and service solutions (SPSS) software version 20 for Windows in processing data. The result shows there is a simultaneously positive effect between the usability, the information quality and the service interaction variables to user satisfaction. Parsially, the usability and the information quality variables shows the positive effect but insignificantly against to user satisfaction and the service interaction quality variable of Riau University librarys website shows the positive effect and significantly influence the user. Counting the satisfactory of Riau University students to this research instrument shows that the dominant answer are satisfied, but the time accuracy of updating information and fulfillment for services shows unsatisfied.Keywords: Information Quality, Librarys Website, New Media, Service Interaction Quality, Usability, User Satisfaction, WebQual 4.

Image-based Automated Chemical Database Annotation with Ensemble of Machine-Vision Classifiers

This paper presents an image-based annotation strategy for automated annotation of chemical databases. The proposed strategy is based on the use of a machine vision-based classifier for extracting a 2D chemical structure diagram in research articles and converting them into standard chemical file formats, a virtual Chemical Expert" system for screening the converted structures based on the level of estimated conversion accuracy, and a fragment-based measure for calculation intermolecular similarity. In particular, in order to overcome limited accuracies of individual machine-vision classifier, inspired by ensemble methods in machine learning, it is attempted to use of the ensemble of machine-vision classifiers. For annotation, calculated chemical similarity between the converted structures and entries in a virtual small molecule database is used to establish the links. Annotation test to link 121 journal articles to entries in PubChem database demonstrates that ensemble approach increases the coverage of annotation, while keeping the annotation quality (e.g., recall and precision rates) comparable to using a single machine-vision classifier.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87266/4/Saitou55.pd

Automated extraction of chemical structure information from digital raster images

Background: To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results: This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader -- a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion: The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research articles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90875/1/Saitou8.pd

Leukotriene receptor expression in esophageal squamous cell cancer and non-transformed esophageal epithelium: a matched case control study

Study questionnaire. (DOC 21 kb

A Rational Approach to Personalized Anticancer Therapy: Chemoinformatic Analysis Reveals Mechanistic Gene-Drug Associations

Purpose . To predict the response of cells to chemotherapeutic agents based on gene expression profiles, we performed a chemoinformatic study of a set of standard anticancer agents assayed for activity against a panel of 60 human tumor-derived cell lines from the Developmental Therapeutics Program (DTP) at the National Cancer Institute (NCI).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41497/1/11095_2004_Article_465512.pd

Intracellular Drug Concentrations and Transporters: Measurement, Modeling, and Implications for the Liver

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109769/1/cptclpt201378.pd

Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines

Cell-based molecular transport simulations are being developed to facilitate exploratory cheminformatic analysis of virtual libraries of small drug-like molecules. For this purpose, mathematical models of single cells are built from equations capturing the transport of small molecules across membranes. In turn, physicochemical properties of small molecules can be used as input to simulate intracellular drug distribution, through time. Here, with mathematical equations and biological parameters adjusted so as to mimic a leukocyte in the blood, simulations were performed to analyze steady state, relative accumulation of small molecules in lysosomes, mitochondria, and cytosol of this target cell, in the presence of a homogenous extracellular drug concentration. Similarly, with equations and parameters set to mimic an intestinal epithelial cell, simulations were also performed to analyze steady state, relative distribution and transcellular permeability in this non-target cell, in the presence of an apical-to-basolateral concentration gradient. With a test set of ninety-nine monobasic amines gathered from the scientific literature, simulation results helped analyze relationships between the chemical diversity of these molecules and their intracellular distributions

Intracellular Drug Concentrations and Transporters: Measurement, Modeling, and Implications for the Liver

Intracellular concentrations of drugs and metabolites are often important determinants of efficacy, toxicity, and drug interactions. Hepatic drug distribution can be affected by many factors, including physicochemical properties, uptake/efflux transporters, protein binding, organelle sequestration, and metabolism. This white paper highlights determinants of hepatocyte drug/metabolite concentrations and provides an update on model systems, methods, and modeling/simulation approaches used to quantitatively assess hepatocellular concentrations of molecules. The critical scientific gaps and future research directions in this field are discussed

Selective Targeting of Tumorigenic Cancer Cell Lines by Microtubule Inhibitors

For anticancer drug therapy, it is critical to kill those cells with highest tumorigenic potential, even when they comprise a relatively small fraction of the overall tumor cell population. We have used the established NCI/DTP 60 cell line growth inhibition assay as a platform for exploring the relationship between chemical structure and growth inhibition in both tumorigenic and non-tumorigenic cancer cell lines. Using experimental measurements of “take rate” in ectopic implants as a proxy for tumorigenic potential, we identified eight chemical agents that appear to strongly and selectively inhibit the growth of the most tumorigenic cell lines. Biochemical assay data and structure-activity relationships indicate that these compounds act by inhibiting tubulin polymerization. Yet, their activity against tumorigenic cell lines is more selective than that of the other microtubule inhibitors in clinical use. Biochemical differences in the tubulin subunits that make up microtubules, or differences in the function of microtubules in mitotic spindle assembly or cell division may be associated with the selectivity of these compounds

A Cell-based Computational Modeling Approach for Developing Site-Directed Molecular Probes

Modeling the local absorption and retention patterns of membrane-permeant small molecules in a cellular context could facilitate development of site-directed chemical agents for bioimaging or therapeutic applications. Here, we present an integrative approach to this problem, combining in silico computational models, in vitro cell based assays and in vivo biodistribution studies. To target small molecule probes to the epithelial cells of the upper airways, a multiscale computational model of the lung was first used as a screening tool, in silico. Following virtual screening, cell monolayers differentiated on microfabricated pore arrays and multilayer cultures of primary human bronchial epithelial cells differentiated in an air-liquid interface were used to test the local absorption and intracellular retention patterns of selected probes, in vitro. Lastly, experiments involving visualization of bioimaging probe distribution in the lungs after local and systemic administration were used to test the relevance of computational models and cell-based assays, in vivo. The results of in vivo experiments were consistent with the results of in silico simulations, indicating that mitochondrial accumulation of membrane permeant, hydrophilic cations can be used to maximize local exposure and retention, specifically in the upper airways after intratracheal administration