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IEEE EMBS International Conference on information Technology Applications in Biomedicine (ITAB)

作者： Georgia Tsiliki Marina Ioannou Dimitris Kafetzopoulos Michalis Zervakis Elias Sanidas Eustathios Stathopoulos Manolis Tsiknakis FORTH Molecular Biology and Biotechnology IMBB Crete Greece Department of Electronic and Computer Engineering University Campus Crete Greece Medical School University of Crete Crete Greece Biomedical Informatics Laboratory Institute of Computer Science ICS Foundation for Research and Technology Hellas FORTH Crete Greece

An increasing number of studies have profiled gene expressions in tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most challenging tasks is to develop robust statistical models to integrate their findings. We compare some recent methodologies on the field, with respect to ER status, and focus on a unified among platforms scale suggested by Parmigiani et al.(2002) and Shen et al.(2004), which is based on a Bayesian mixture model. Under this unified scale, we study the intensity similarities between four breast cancer data sets derived from various platforms. We evaluate our results with an independent data set in terms of ER sample clustering given the derived gene ER signatures of the integrated data. We found that intensity and fold-change variability similarities between different platform measurements can greatly assist the statistical analysis of independent microarray data sets.

关键词： Biomedical measurements Erbium Breast cancer Sequences information analysis Gene expression Statistical analysis DNA Statistics information technology

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Redundant Gene Selection Based on Particle Swarm Optimization

Redundant Gene Selection Based on Particle Swarm Optimizatio...

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International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS

作者： Su-Fen Chen Xue-Qiang Zeng Guo-Zheng Li Jack Y. Yang Mary Qu Yang Department of Computer Science and Technology Nanchang Institute of Technology Nanchang China School of Information and Engineering University of Nanchang Nanchang China School of Computer Engineering & Science Shanghai University Shanghai China Department of Control Science & Engineering University of Tongji Shanghai China Harvard Medical School Harvard University Cambridge MA USA National Human Genome Research Institute U.S. Department of Health and Human Services National Institutes of Health DHHS Bethesda MD USA

Redundant gene selection is an important topic in the field of bioinformatics. This paper proposes a novel algorithm on Redundant Gene Selection by Particle Swarm Optimization (RGS-PSO), which tries to find a compact gene subset with great predictive ability. Compared with the previous works, RGS-PSO measures the redundancy of feature set by the maximum feature inter-correlation, which is more reasonable than those by the averaged inter-correlation. The outstanding performance of RGS-PSO has been examined by the experiments on several real world microarray data sets.

关键词： Particle swarm optimization Bioinformatics Filters Biology computing Humans Diseases Systems biology Intelligent systems computer science Genomics

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Hybrid robust observers for locally Lipschitz systems

Hybrid robust observers for locally Lipschitz systems

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European Control Conference (ECC)

作者： Alexey A. Bobtsov Denis V. Efimov Department of Control Systems and Informatics Saint-Petersburg State University of Information Technologies Mechanics and Optics St. Petersburg Russia Systems and Control @ Systems and Modeling Department Electrical Engineering and Computer Science Belgium CCS Lab. Institute for Problems of Mechanical Engineering St. Petersburg Russia

State observer design procedure is proposed for nonlinear locally Lipschitz systems. Possible presence of disturbances is taken into account. The solution is based on logic-based control approach applicable to nonline... 详细信息

关键词： Decision support systems Europe

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A sample identification and tracking system for biobanks

A sample identification and tracking system for biobanks

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Annual IEEE Symposium on computer-Based medical Systems

作者： Atieh Zarabzadeh Farzad Hayati R. William G. Watson Geoff Bradley Jane Grimson Centre of Health Informatics Department of Computer Science Trinity College Dublin Ireland Department of Electronic Electrical & Computer Engineering University of Binningham UK UCD School of Medicine and Medical Science UCD Conway Institute of Biomolecular & Biomedical Research University College Dublin Ireland Trinity Centre of High Performance Computing Trinity College Dublin Ireland

The discovery of biomarkers and the underlying causes of diseases are enabled through the analysis of biological samples and data stored in biobanks. Biological samples and their associated data are expensive to collect and maintain, and it is important to store and manage them efficiently. During processing, samples and data go through a number of procedures and techniques, which are often in different locations and by individuals with different access permissions. It is essential to maintain the link between the samples and their associated data throughout the processes they undergo. This paper presents a novel system of tracking samples and data from collection through processing to storage and retrieval, which is based on Radio Frequency Identification (RFID) technology. This system ensures the security and reliability of sample data as well as location-independent recording and updating of sample data, as they move along the workflow.

关键词： Diseases Radiofrequency identification Educational institutions information retrieval High performance computing User centered design Biomarkers Prostate cancer Biomedical informatics computer science

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Performance Analysis of OLSR and BATMAN Protocols Considering Link Quality Parameter

Performance Analysis of OLSR and BATMAN Protocols Considerin...

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International Conference on Advanced information Networking and Applications (AINA)

作者： Leonard Barolli Makoto Ikeda Giuseppe De Marco Arjan Durresi Fatos Xhafa Department of Information and Communication Engineering Fukuoka Institute of Technology (FIT) Higashi-Ku Fukuoka Japan Graduate School of Engineering FIT Higashi-Ku Fukuoka Japan Toyota Kogyo Daigaku Nagoya Aichi JP Department of Computer and Information Science Indiana University Purdue University at Indianapolis (IUPUI) Indianapolis IN USA Department of Languages and Informatics Systems Polytechnic University of Catalonia Barcelona Spain

ISBN: (纸本)9781424440009

In this paper, we present the implementation and analysis of our testbed considering the link quality window size (LQWS) parameter of optimized link state routing (OLSR) and better approach to mobile ad-hoc networking (B.A.T.M.A.N.) protocols. We investigate the effect of mobility in the throughput of a mobile ad-hoc network (MANET). The mobile nodes move toward the destination at a regular speed. When the mobile nodes arrive at the corner, they stop for about three seconds. In our experiments, we consider two cases: only one node is moving (mobile node)and two nodes (intermediate nodes) are moving at the same time. We assess the performance of our testbed in terms of throughput, round trip time, jitter and packet loss. From our experiments, we found that throughput of TCP was improved by reducing LQWS.

关键词： Performance analysis Routing protocols Throughput Mobile ad hoc networks System testing Ad hoc networks Performance loss computer networks information science USA Councils

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Naturally occurring data as research instrument: Analyzing examination responses to study the novice programmer

SIGCSE Bulletin Inroads

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SIGCSE Bulletin Inroads 2009年第4期41卷

作者： Clear, Tony Bouvier, Dennis J. Jacková, Jana Robbins, Phil Lister, Raymond Carter, Paul Lopez, Mike Seppälä, Otto Simon Eckerdal, Anna McCartney, Robert Thompson, Errol School of Comp. and Math. Sciences AUT University New Zealand Department of Computer Science Southern Illinois Univ. Edwardsville United States Faculty of Manag. Sci. and Informatics University of Zilina Slovakia Department of Computer Science University of British Columbia Canada Manukau Institute of Technology New Zealand Dept. of Computer Science and Engineering Helsinki University of Technology Finland Faculty of Science and IT University of Newcastle Australia Dept of Information Technology Uppsala University Sweden Dept Comp. Sci. and Engineering University of Connecticut United States United Kingdom

In New Zealand and Australia, the BRACElet project has been investigating students' acquisition of programming skills in introductory programming courses. The project has explored students' skills in basic syntax, tracing code, understanding code, and writing code, seeking to establish the relationships between these skills. This ITiCSE working group report presents the most recent step in the BRACElet project, which includes replication of earlier analysis using a far broader pool of naturally occurring data, refinement of the SOLO taxonomy in code-explaining questions, extension of the taxonomy to code-writing questions, extension of some earlier studies on students' 'doodling' while answering exam questions, and exploration of a further theoretical basis for work that until now has been primarily empirical.

关键词： Students

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Beyond p-values: Averaged and reproducible evidence in fMRI experiments

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Psychophysiology 2009年第2期46卷 367-378页

作者： Liou, Michelle Su, Hong-Ren Savostyanov, Alexander N. Lee, Juin-Der Aston, John A. D. Chuang, Cheng-Hung Cheng, Philip E. Institute of Statistical Science Academia Sinica Taipei 115 Taiwan Institute of Statistical Science Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan State Research Institute of Physiology Siberian Branch of Russian Academy of Medical Sciences Novosibirsk Russian Federation Department of Statistics University of Warwick Coventry United Kingdom Department of Computer Science and Information Engineering Asia University Taichung County Taiwan

In functional magnetic resonance imaging studies, there might exist activation regions routinely involved in experimental sessions, but modest in response magnitude. These regions may not be easily detectable by the conventional p-value approach using a rigid threshold. With particular reference to the reproducibility analysis method proposed in Liou and colleagues, this study presents some within- and between-subject brain-activation patterns that are replicable between experimental modalities, and robust to the method used for generating the patterns. There is a neurophysiological basis behind these reproducible patterns, and the conventional p-value approach using averaged data across subjects might not suggest the complete patterns. For example, recent studies based on the group-averaged data showed a task-induced deactivation in the precuneus and posterior cingulate, but our reproducibility analysis suggests both increased and decreased responses in the two regions. The increased responses localize in these regions with differentially distributed patterns for individual subjects and for different experimental tasks. In this study, we discuss the neurophysiological basis of the reproducible patterns and propose some applications of our research findings to scientific and clinical studies. Copyright © 2009 Society for Psychophysiological Research.

关键词： Category-preferential regions Default network Reproducibility SPMs

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Small-world Network for Investigating Functional Connectivity in Bipolar Disorder: A Functional Magnetic Images (fMRI) Study

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13th International Conference on Biomedical engineering, ICBME 2008

作者： Teng, S. Wang, P.S. Liao, Y.L. Yeh, T.-C. Su, T.-P. Hsieh, J.C. Wu, Yu-Te Department of Biomedical Imaging and Radiological Sciences National Yang-Ming University No.155 Sec.2 Linong Street Taipei Taiwan Integrated Brain Research Laboratory Department of Medical Research and Education Taipei Veterans General Hospital Taipei Taiwan The Neurological Institute Taipei Veterans General Hospital Taipei Taiwan Department of Neurology National Yang-Ming University School of Medicine Taipei Taiwan The Neurological Institute Taipei Municipal Gan-Dau Hospital Taipei Taiwan Institute of Brain Science National Yang-Ming University Taipei Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Taipei Taiwan Division of Psychiatry School of Medicine National Yang-Ming University Taipei Taiwan Psychiatric Department Taipei Veterans General Hospital Taipei Taiwan

ISBN: (纸本)9783540928409

Small-world network is a highly clustered system but with small mean path length between networks which allow the information transferred with high efficiency. The human brain can be considered as a sparse, complex network modeled by the small-world properties. Once the brain network was disrupted by disease, the small-world properties would be altered to manifest that the information integration was inefficiency and the network was loosely organized. The aim of this study is to investigate the difference of small-world properties of brain functional network derived from resting-state functional magnetic resonance imaging (fMRI) between the healthy subjects and the patients with Bipolar disorder (BD). The functional MRI data was acquired from 5 healthy subjects and 5 patients with Bipolar disorder. All images of each subject were parcellated into 90 cortical and sub-cortical regions which were defined as the nodes of the network. The functional relations between the 90 regions were estimated by the frequency-based mutual information followed by thresholding to construct a set of undirected graphs. Small-world properties, such as the degree and strength of the connectivity, clustering coefficient of connections, mean path length among brain regions, global efficiency and local efficiency, are examined between any pair of functional areas. Our findings indicated that, in comparison with the control subjects, the BD patients presented smaller values of the degree, the strength of the connectivity and the clustering coefficient of connections, whereas larger values of mean path length among brain regions. This suggested the reduced global and local efficiency of the small-world properties for BD patients. In addition, the small-world properties of BD patients were altered significantly in some regions in the frontal lobes and limbic system which were in good agreement with the dysfunction connectivity reported by the previous literatures in the study of bipolar disorder

关键词： Small-world networks

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Extracting the Coronary Artery in Angiographic Image Based on à Trous Wavelet of Rotary Gaussian with Adaptive Space Coefficient

Extracting the Coronary Artery in Angiographic Image Based o...

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International Conference on Computational Intelligence and Security

作者： Qingzhu Wang Ke Wang Donghong An Bo Chen Miao Liu Yingying Ying College of Communication Engineering Jilin University Changchun China China China-Japan Union Hospital Jilin University Changchun China Department of Computer Science Daqing Petroleum Institute China Department of Pharmacy Changchun Medical College Changchun China College of Information and Communication Engineering Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781424454112

According to the matching differences cased by cardiac non-rigid motion between angiographic images before and after injected in subtract angiography which is most widely used in diagnosis, a new algorithm based on a¿ trous wavelet of rotary Gaussian with adaptive space coefficient and segmentation based on transition region is put forward to in this paper. The angiographic image is pretreated by an adaptive and multi-hierarchy method to obtain images of different levels, and all sub-images are obtained by extracting the coronary artery from image of every level, all sub-images are fused to obtain the final image in accordance by certain rules. Simulation results based on 200 actual coronary artery angiographic images indicate that comparing with traditional algorithms, SNR is improved 4.7%~8.8%, and positioning accuracy of centerline is improved 3.9%~37.5%.

关键词： Arteries Educational institutions Image segmentation Angiography Biomedical engineering Knowledge engineering Clinical diagnosis Heart Low pass filters Computational intelligence

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Newborn Screening System Based on Adaptive Feature Selection and Support Vector Machines

Newborn Screening System Based on Adaptive Feature Selection...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Sung-Huai Hsieh Yin-Hsiu Chien Chia-Ping Shen Wei-Hsin Chen Po-Hao Chen Sheau-Ling Hsieh Po-Hsun Cheng Feipei Lai Department of Computer Science and Information Engineering National Taiwan University Taiwan Information Systems Office National Taiwan University Hospital Taipei Taiwan Department of Medical Genetics National Taiwan University Hospital Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan Network and Computer Centre National Chiao Tung University Hsinchu Taiwan Department of Software Engineering National Kaohsiung Normal University Taiwan

The clinical symptoms of metabolic disorders during neonatal period are often not apparent, if not treated early irreversible damages such as mental retardation may occur, even death. Therefore, practicing newborn screening is very important to prevent neonatal from these damages. In this paper, the newborn screening system used support vector machines (SVM) classification technique is proposed in place of cut-off value decision to evaluate the metabolic substances concentration raw data obtained from tandem mass spectrometry (MS/MS) and determine whether the newborn has some kinds of metabolic disorder diseases. On the basis of the proposed features, new analytic combinations are identified with superior discriminatory performance compared with the best published combinations. Classifiers built with the feature selection to find C3/C2, C3 and C16 of three key point features achieved diagnostic sensitivities, specificities and accuracy approaching 100%.

关键词： Pediatrics Adaptive systems Support vector machines Support vector machine classification Biochemistry Testing Hospitals Diseases Machine learning Bioinformatics

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