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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Chi-Huang Chen Xiao-Ou Ping Zi-Jun Wang Sheau-Ling Hsieh Li-Chin Chen Yi-Ju Tseng Ching-Wei Hsu Feipei Lai Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronic and Bioinformatics National Taiwan University Taipei Taiwan EECS International Graduate Program Institute IT Center National Chiao Tung University Hsinchu Taiwan

The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data retrieval from the non-structuralized textual clinical documents such as radiology reports, pathology reports, etc. The system provides keyword-based and semantic-driven data matching methodology to extract the specific information from the textual clinical documents. The matching methodology provides the capabilities to recognize the selected keywords and the related semantics in the documents. Through the extraction verification interface, clinicians can extract and verify the matched information semi-automatically. The extracted data can be filled into predefined case-oriented templates. The structuralized data can be stored back into the clinical data warehouse for further analyzing. Moreover, the case-oriented templates can support collecting corresponding extracted data for various researches.

关键词： Data mining Semantics Pattern matching Tumors Radiology Pathology Cancer

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Characterizing Canine Lymphoma As a Potential Large Animal Model of Human Diffuse Large B-Cell Lymphoma

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Blood 2011年第21期118卷 5193-5193页

作者： Kristy L. Richards Alison Motsinger-Reif Hsiao-Wei Chen Yuri D. Fedoriw Cheng Fan Dahlia M. Nielsen Rachael Thomas Chris Smith Sandeep S. Dave Charles M. Perou Matthew Breen Steven E. Suter Division of Hematology/Oncology University of North Carolina Chapel Hill NC USA Department of Statistics North Carolina State University Genomic Sciences Graduate Program North Carolina State University Department of Pathology University of North Carolina Lineberger Comprehensive Cancer Center University of North Carolina Chapel Hill NC USA Department of Genetics North Carolina State University Center for Comparative Medicine & Translational Research North Carolina State University Raleigh NC USA Bioinformatics Research Center North Carolina State University Duke University Durham NC USA Department of Molecular Biomedical Sciences North Carolina State University Department of Clincal Sciences North Carolina State University

Abstract 5193 Diffuse large B-cell lymphoma (DLBCL) affects ∼25,000 people in the U.S. each year, and fewer than half of them are cured with standard therapy. DLBCL can be divided into two subtypes by gene expression profiling, germinal center B-cell (GCB) type and activated B-cell (ABC) type. ABC-type DLBCL patients have significantly poorer outcomes. To improve therapeutic options, better animal models that accurately mimic human DLBCL (hDLBCL) are needed. Canine DLBCL is one of the most common cancers in veterinary oncology. Similar to human DLBCL patients, dogs with lymphoma are treated with both CHOP-like regimens and autologous stem cell transplants. Morphologically, canine lymphomas are similar to hDLBCL, with shared histologic markers, such as CD20 and PAX5. With recent technologies based on knowledge of the canine genome sequence, it is now possible to evaluate dogs as a potential large-animal model for hDLBCL. We evaluated 58 canine B-cell lymphomas by generating comprehensive gene expression profiles and comparing them to previously published hDLBCL expression profiles. Canine B-cell lymphoma expression profiles were similar in some ways to hDLBCLs. For instance, increased expression of NF-kB pathway genes was noted in a subset of lymphomas, mirroring NF-kB pathway activation in human ABC-type DLBCL. Furthermore, immunoglobulin heavy chain (IGH) mutation status, which is correlated with ABC/GCB cell of origin in hDLBCL, separated canine DLBCL into two groups with statistically different progression-free and overall survival times. However, canine DLBCL differed from hDLBCL in other aspects, including rare immunohistochemical positivity for BCL6 and MUM1/IRF4. Collectively, these results define aspects of canine B-cell lymphomas that resemble hDLBCL, identifying molecular similarities that could allow dogs to be used as a representative model of hDLBCL. Further comparative studies, including therapeutic trials, could potentially improve outcomes in both sp

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Quantum dot conjugates for targeted silencing of bcr/abl gene by RNA interference in human myelogenous leukemia K562 cells

Quantum dot conjugates for targeted silencing of bcr/abl gen...

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作者： Zhao, Yu Zhao, Lujing Zhou, Lijia Zhi, Yuan Xu, Jianming Wei, Zheng Zhang, Kelvin Xi Francis Ouellette, B.F. Shen, Hebai College of Life and Environment Science Shanghai Normal University Shanghai 200234 China Department of Hematology Zhong Shan Hospital Fu Dan University Shanghai 200032 China Graduate Program in Bioinformatics University of British Columbia Vancouver BC V6T1Z4 Canada Ontario Institute for Cancer Research MaRS Centre South Tower 101 College Street Toronto ON M5G0A3 Canada

Quantum dots (QDs) have been receiving a lot of attention recently for their unique fluorescence properties that can be used in drug discovery and bioimaging applications. We have in this article focused particularly on QDs and used it as a transfection vector as well as a fluorescence label for the RNA interference research. The siRNAs were designed to knock down the bcr/abl oncogene in leukaemia K562 cells. EDAC used as a cross-linker, COOH-functionalized QDs were conjugated with NH2-modified siRNAs to generate QD-siRNA conjugates. We also demonstrated their application to the K562 cells. Using such constructs, the delivery and transfection of siRNAs could be monitored by the presence of fluorescent QDs in the conjugates. QDs not only exhibited superior photostability for labeling cells but also worked as a good vector that remarkably increased the transfection efficiency of siRNAs into the cells. Cell proliferation was examined by the MTT assay and cell apoptosis by FACS. Our data have shown that the QD-siRNA conjugates could efficiently inhibit the viability of K562 cells and induced their apoptosis. In summary, QDs can be considered strong tools for the functional analysis of RNAi. Copyright © 2010 American Scientific Publishers.

关键词： Nanocrystals

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Chi-Huang Chen Sheau-Ling Hsieh Yung-Ching Weng Wen-Yung Chang Feipei Lai Department of Electrical Engineering National Taiwan University Taipei Taiwan EECS International Graduate Program Institute IT Center National Chiao Tung University Hsinchu Taiwan Department of Computer Science and Engineering National Taiwan University Taiwan Institute of Computer Science and Engineering College of Computer Science National Chiao Tung University Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

关键词： Semantics Biomedical measurements Correlation Kernel Training Medical services Support vector machine classification

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Web-based healthcare Hand Drawing Management System

Web-based healthcare Hand Drawing Management System

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Sheau-Ling Hsieh Yung-Ching Weng Chi-Huang Chen Kai-Ping Hsu Jeng-Wei Lin Feipei Lai EECS International Graduate Program Institute IT Center National Chiao Tung University Hsinchu Taiwan Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Computer and Information Networking Center National Taiwan University Taipei Taiwan Department of Information Management Tunghai University Taichung Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan

The paper addresses Medical Hand Drawing Management System architecture and implementation. In the system, we developed four modules: hand drawing management module; patient medical records query module; hand drawing editing and upload module; hand drawing query module. The system adapts windows-based applications and encompasses web pages by *** hosting mechanism under web services platforms. The hand drawings implemented as files are stored in a FTP server. The file names with associated data, e.g. patient identification, drawing physician, access rights, etc. are reposited in a database. The modules can be conveniently embedded, integrated into any system. Therefore, the system possesses the hand drawing features to support daily medical operations, effectively improve healthcare qualities as well. Moreover, the system includes the printing capability to achieve a complete, computerized medical document process. In summary, the system allows web-based applications to facilitate the graphic processes for healthcare operations.

关键词： Medical services Biomedical imaging Printing Conferences Web services Graphics Databases

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Erratum to: Genetic analysis of Down syndrome-associated heart defects in mice

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Human Genetics 2011年第5期130卷 633-633页

作者： Liu, Chunhong Morishima, Masae Yu, Tao Matsui, Sei-Ichi Zhang, Li Fu, Dawei Pao, Annie Costa, Alberto C. Gardiner, Katheleen J. Cowell, John K. Nowak, Norma J. Parmacek, Michael S. Liang, Ping Baldini, Antonio Yu, Y. Eugene Children’s Guild Foundation Down Syndrome Research Program Department of Cancer Genetics Roswell Park Cancer Institute Buffalo USA Department of Anatomy and Developmental Biology Department of Pediatric Cardiology Tokyo Women’s Medical University Tokyo Japan Division of Clinical Pharmacology and Toxicology Department of Medicine University of Colorado School of Medicine Aurora USA Department of Pediatrics Intellectual and Developmental Disability Research Center Human Medical Genetics and Neuroscience Programs University of Colorado Denver Aurora USA MCG Cancer Center School of Medicine Medical College of Georgia Augusta USA New York State Center of Excellence in Bioinformatics and Life Sciences Buffalo USA Department of Cellular and Molecular Biology Roswell Park Division of Graduate School State University of New York at Buffalo Buffalo USA University of Pennsylvania Cardiovascular Institute Philadelphia USA Department of Biological Sciences Brock University St. Catharines Canada Institute of Biosciences and Technologies Texas A&M University Houston USA Institute of Genetics and Biophysics National Research Council Naples Italy

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Predicting helix-helix interactions from residue contacts in membrane proteins

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bioinformatics 2009年第8期25卷 996-1003页

作者： Lo, Allan Chiu, Yi-Yuan Rødland, Einar Andreas Lyu, Ping-Chiang Sung, Ting-Yi Hsu, Wen-Lian Bioinformatics Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Bioinformatics and Structural Biology Department of Life Sciences National Tsing Hua University Hsinchu Taiwan Bioinformatics Laboratory Institute of Information Science Academia Sinica Taipei Taiwan Centre for Cancer Biomedicine University of Oslo NO-0027 Oslo Norway SAMBA Norwegian Computing Center Blindern NO-0314 Oslo P.O. Box 114 Norway

Motivation: Helix-helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. On the molecular level, the interactions are mediated by one or more residue contacts. Although previous studies focused on helix-packing patterns and sequence motifs, few of them developed methods specifically for contact prediction. Results: We present a new hierarchical framework for contact prediction, with an application in membrane proteins. The hierarchical scheme consists of two levels: in the first level, contact residues are predicted from the sequence and their pairing relationships are further predicted in the second level. Statistical analyses on contact propensities are combined with other sequence and structural information for training the support vector machine classifiers. Evaluated on 52 protein chains using leave-one-out cross validation (LOOCV) and an independent test set of 14 protein chains, the two-level approach consistently improves the conventional direct approach in prediction accuracy, with 80% reduction of input for prediction. Furthermore, the predicted contacts are then used to infer interactions between pairs of helices. When at least three predicted contacts are required for an inferred interaction, the accuracy, sensitivity and specificity are 56%, 40% and 89%, respectively. Our results demonstrate that a hierarchical framework can be applied to eliminate false positives (FP) while reducing computational complexity in predicting contacts. Together with the estimated contact propensities, this method can be used to gain insights into helix-packing in membrane proteins. © 2009 The Author(s).

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Redesign of high-affinity nonspecific nucleases with altered sequence preference

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Journal of the American Chemical Society 2009年第47期131卷 17345-17353页

作者： Wang, Yi-Ting Wright, Jon D. Doudeva, Lyudmila G. Jhang, Hua-Ci Lim, Carmay Yuan, Hanna S. Institute of Molecular Biology Academia Sinica Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Institute of Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Bioinformatics and Structural Biology Department of Chemistry National Tsing Hua University HsinChu Taiwan Institute of Biochemistry and Molecular Biology National Taiwan University Taipei Taiwan

It is of crucial importance to elucidate the underlying principles that govern the binding affinity and selectivity between proteins and DNA. Here we use the nuclease domain of Colicin E7 (nColE7) as a model system to generate redesigned nucleases with improved DNA-binding affinities. ColE7 is a bacterial toxin, bearing a nonspecific endonuclease domain with a preference for hydrolyzing DNA phosphodiester bonds at the 3O-side after thymine and adenine;i.e., it prefers Thy and Ade at the -1 site. Using systematic computational screening, six nColE7 mutants were predicted to bind DNA with high affinity. Five of the redesigned single-point mutants were constructed and purified, and four mutants had a 3- to 5-fold higher DNA binding affinity than wild-type nColE7 as measured by fluorescence kinetic assays. Moreover, three of the designed mutants, D493N, D493Q, and D493R, digested DNA with an increased preference for guanine at +3 sites compared to the wild-type enzyme, as shown by DNA footprint assays. X-ray structure determination of the ColE7 mutant D493Q-DNA complex in conjunction with structural and free energy decomposition analyses provides a physical basis for the improved protein-DNA interactions: Replacing D493 at the protein-DNA interface with an amino acid residue that can maintain the native hydrogen bonds removes the unfavorable electrostatic repulsion between the negatively charged carboxylate and DNA phosphate groups. These results show that computational screening combined with biochemical, structural, and free energy analyses provide a useful means for generating redesigned nucleases with a higher DNA-binding affinity and altered sequence preferences in DNA cleavage. © 2009 American Chemical Society.

关键词： DNA

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Identification of microRNA in the protist Trichomonas vaginalis

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Genomics 2009年第5期93卷 487-493页

作者： Lin, Wei-Chen Li, Sung-Chou Lin, Wen-Chang Shin, Jyh-Wei Hu, Song-Nian Yu, Xiao-Min Huang, Ting-Yun Chen, Shih-Chieh Chen, Hua-Chien Chen, Shu-Jen Huang, Po-Jung Ruei-Chi Gan, Richie Chiu, Cheng-Hsun Tang, Petrus Molecular Regulation and Bioinformatics Laboratory Chang Gung University Taoyuan 333 Taiwan Division of Microbiology Graduate Institute of Biomedical Sciences Chang Gung University Taoyuan 333 Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei 112 Taiwan Taiwan International Graduate Program in Bioinformatics Academia Sinica Taipei 115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei 115 Taiwan Department of Parasitology National Cheng Kung University Tainan 701 Taiwan Key Laboratory of Genome Sciences and Information Beijing Institute of Genomics Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Department of Life Sciences Chang Gung University Taoyuan 333 Taiwan Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Bioinformatics Center Chang Gung University Tao-Yuan 333 Taiwan Chang Gung Molecular Infectious Diseases Research Center Chang Gung Memorial Hospital Taoyuan 333 Taiwan

MicroRNAs (miRNAs) are a class of small noncoding RNAs that have important regulatory roles in multicellular organisms. However, miRNA has never been identified experimentally in protist. Direct cloning of 438 expressed miRNA tags by microRNA serial analysis of gene expression from the parasitic protist Trichomonas vaginalis identified nine candidate miRNAs. bioinformatics analysis of the corresponding genomic region revealed that these miRNA candidates contain a classical stem-loop-stem structure of pre-microRNAs. Analysis of the 20 nt long mature tva-miR-001 showed that it is an intergenic miRNA located at the scaffold DS113596. Tva-miR-001 was differentially expressed in the trophozoite, pseudocyst and amoeboid stages. Based on the experimental results of the present study, we provided solid evidence that protist possesses a miRNA regulating network comparable with multicellular organisms for the first time. © 2009 Elsevier Inc. All rights reserved.

关键词： MicroRNA Protist Trichomonas vaginalis

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Classification of Multiple Time-Series via Boosting

Classification of Multiple Time-Series via Boosting

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IEEE Digital Signal Processing Workshop

作者： Patrick L. Harrington Arvind Rao Alfred O., Hero Bioinformatics Graduate Program University of Michigan Ann Arbor MI USA Lane Center of Computational Biology Carnegie Mellon University Pittsburgh PA USA Department of Statistics University of Michigan Ann Arbor MI USA

Much of modern machine learning and statistics research consists of extracting information from high-dimensional patterns. Often times, the large number of features that comprise this high-dimensional pattern are themselves vector valued, corresponding to sampled values in a time-series. Here, we present a classification methodology to accommodate multiple time-series using boosting. This method constructs an additive model by adaptively selecting basis functions consisting of a discriminating feature's full time-series. We present the necessary modifications to fisher linear discriminant analysis and least-squares, as base learners, to accommodate the weighted data in the proposed boosting procedure. We conclude by presenting the performance of our proposed method against a synthetic stochastic differential equation data set and a real world data set involving prediction of cancer patient susceptibility for a particular chemoradiotherapy.

关键词： Boosting Statistics Vectors Linear discriminant analysis Gene expression bioinformatics Computational biology Machine learning Data mining Stochastic processes

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