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BMC BIOINFORMATICS 2007年第s1期8卷 1-10页

作者： Splendiani, Andrea Brandizi, Marco Even, Gael Beretta, Ottavio Pavelka, Norman Pelizzola, Mattia Mayhaus, Manuel Foti, Maria Mauri, Giancarlo Ricciardi-Castagnoli, Paola Univ Milan Dept Informat Systemist & Commun I-20122 Milan Italy Univ Milano Bicocca Dept Biotechnol & Biosci I-20126 Milan Italy

Background: Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood. Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions. Results: The Genopolis database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip (R) platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users. Conclusion: The Genopolis database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local d

关键词： Control Vocabulary Public Repository Experiment Description Laboratory Information Management System microarray database

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StressDB: A locally installable web-based relational microarray database designed for small user communities

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COMPARATIVE AND FUNCTIONAL GENOMICS 2002年第2期3卷 91-96页

作者： Mitra, M Shah, N Mueller, L Pin, S Fedoroff, N Penn State Univ Wartik Lab 519 University Pk PA 16802 USA Carnegie Inst Dept Plant Biol Stanford CA 94305 USA

We have built a microarray database, StressDB, for management of microarray data from our studies on stress-modulated genes in Arabidopsis. StressDB provides small user groups with a locally installable web-based relational microarray database. It has a simple and intuitive architecture and has been designed for cDNA microarray technology users. StressDB uses Windows(TM) 2000 as the centralized database server with Oracle(TM) 8i as the relational database management system. It allows users to manage microarray data and data-related biological information over the Internet using a web browser. The source-code is currently available on request from the authors and will soon be made freely available for downloading from our website athttp://***. Copyright (C) 2002 John Wiley Sons, Ltd.

关键词： microarray database gene expression Arahidopsis plant stress

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TOXICOLOGY LETTERS 2009年第1期186卷 52-57页

作者： Toyoshiba, Hiroyoshi Sawada, Hiroshi Naeshiro, Ichiro Horinouchi, Akira Takeda Pharmaceut Co Ltd Res Dev Ctr Div Pharmaceut Res Yodogawa Ku Osaka 5328686 Japan

Numbers of microarrays have been examined and several public and commercial databases have been developed. However, it is not easy to compare in-house microarray data with those in a database because of insufficient reproducibility due to differences in the experimental conditions. As one of the approach to use these databases, we developed the similar compounds searching system (SCSS) on a toxicogenomics database. The datasets of 55 compounds administered to Fats in the Toxicogenomics Project (TGP) database in Japan were used in this Study. Using the fold-change ranking method developed by Lamb et al. [Lamb, J.. Crawford, E.D., Peck, D.. Modell, J.W., Blat, I.C., Wrobel, M.J., Lerner, J., Brunet, J.P., Subramanian, A., Ross, K.N., Reich, M., Hieronymus, H., Wei, G., Armstrong, S.A., Haggarty, S.J., Clemons, P.A., Wei, R., Carr, S.A., Lander. E.S., Golub, T.R., 2006. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929-1935] and criteria called hit ratio, the system let us compare in-house microarray data and those in the database. In-house generated data for clofibrate, phenobarbital, and a proprietary compound were tested to evaluate the performance of the SCSS method. Phenobarbital and clofibrate, which Were included in the TGP database, scored highest by the SCSS method. Other high scoring compounds had effects similar to either phenobarbital (a cytochrome P450s inducer) Or clofibrate (a peroxisome proliferator). Some of high scoring compounds identified using the Proprietary compound-administered rats have been known to cause similar toxicological changes in different species. Our results suggest that the SCSS method could be used in drug discovery and development. Moreover, this method may be a powerful tool to understand the mechanisms by which biological systems respond to various chemical compounds and may also predict adverse effects of new Compounds. (C) 2008 Elsevier Ireland Ltd. All rig

关键词： microarray database Gene expression Fold-change ranking Similar compounds searching system

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The Longhorn Array database (LAD): An open-source, MIAME compliant implementation of the Stanford microarray database (SMD)

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BMC BIOINFORMATICS 2003年第1期4卷 32-32页

作者： Killion, PJ Sherlock, G Iyer, VR Univ Texas Inst Mol & Cellular Biol Sect Mol Genet & Microbiol Austin TX 78712 USA Stanford Univ Sch Med Dept Genet Stanford CA 94305 USA

Background: The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description: The Longhorn Array database ( LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford microarray database (SMD), one of the largest microarray databases. LAD is available at http:// *** Conclusions: Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data.

关键词： Relational database microarray database Biological Annotation Stanford microarray database Open Source Version

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Storing, linking, and mining microarray databases using SRS

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BMC BIOINFORMATICS 2005年第1期6卷 192-192页

作者： Veldhoven, A de Lange, D Smid, M de Jager, V Kors, JA Jenster, G Erasmus MC Josephine Nefkens Inst Dept Urol NL-3000 DR Rotterdam Netherlands

Background: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS. Results: We devised an Auto-Upload Tool by which microarray data can be automatically imported into SRS. The dataset can be linked to other databases and user access can be set. The linkage comprehensiveness of microarray platforms to other platforms and biological databases was examined in a network of scientific databases. The stored microarray data can also be made accessible to external programs for further processing. For example, we built an interface to a program called Venn Mapper, which collects its microarray data from SRS, processes the data by creating Venn diagrams, and saves the data for interpretation. Conclusion: SRS is a useful database system to store, link and query various scientific datasets, including microarray data. The user-friendly Auto-Upload Tool makes SRS accessible to biologists for linking and mining user-owned databases.

关键词： microarray Data microarray Dataset Scientific database Biological database microarray database

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An antibody against SSEA-5 glycan on human pluripotent stem cells enables removal of teratoma-forming cells

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NATURE BIOTECHNOLOGY 2011年第9期29卷 829-U86页

作者： Tang, Chad Lee, Andrew S. Volkmer, Jens-Peter Sahoo, Debashis Nag, Divya Mosley, Adriane R. Inlay, Matthew A. Ardehali, Reza Chavez, Shawn L. Pera, Renee Reijo Behr, Barry Wu, Joseph C. Weissman, Irving L. Drukker, Micha Stanford Univ Sch Med Inst Stem Cell Biol & Regenerat Med Stanford CA USA Stanford Univ Sch Med Dept Radiol Div Cardiol Stanford CA USA Stanford Univ Sch Med Dept Med Div Cardiol Stanford CA USA Univ Duesseldorf Dept Urol Dusseldorf Germany Stanford Univ Sch Med Dept Gynecol & Obstet Stanford CA USA

An important risk in the clinical application of human pluripotent stem cells (hPSCs), including human embryonic and induced pluripotent stem cells (hESCs and hiPSCs), is teratoma formation by residual undifferentiated cells. We raised a monoclonal antibody against hESCs, designated anti-stage-specific embryonic antigen (SSEA)-5, which binds a previously unidentified antigen highly and specifically expressed on hPSCs-the H type-1 glycan. Separation based on SSEA-5 expression through fluorescence-activated cell sorting (FACS) greatly reduced teratoma-formation potential of heterogeneously differentiated cultures. To ensure complete removal of teratoma-forming cells, we identified additional pluripotency surface markers (PSMs) exhibiting a large dynamic expression range during differentiation: CD9, CD30, CD50, CD90 and CD200. Immunohistochemistry studies of human fetal tissues and bioinformatics analysis of a microarray database revealed that concurrent expression of these markers is both common and specific to hPSCs. Immunodepletion with antibodies against SSEA-5 and two additional PSMs completely removed teratoma-formation potential from incompletely differentiated hESC cultures.

关键词： monoclonal antibody CD200: expression CD30: expression CD50: expression CD90: expression CD9: expression anti-stage-specific embryonic antigen-5: SSEA-5 expression H type-1 glycan pluripotency surface marker: PSM microarray database immunodepletion mechanism Pluripotent Stem Cells Polysaccharides Monoclonal Antibodies Induced Pluripotent Stem Cells

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A statistical and learning based oncogene detection and classification scheme using human cDNA expressions for ovarian carcinoma

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第8期38卷 10066-10074页

作者： Tsai, Meng-Hsiun Lai, Ching-Hao Yu, Shyr-Shen Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung 402 Taiwan Inst Informat Ind Emerging Smart Technol Inst Taipei 105 Taiwan Natl Chung Hsing Univ Dept Management Informat Syst Taichung 402 Taiwan Natl Chung Hsing Univ Inst Genom & Bioinformat Taichung 402 Taiwan

In this paper, a human ovarian cDNA expression database is analyzed for detecting oncogenes and then selected oncogenes are used to identify pathological stages of ovarian carcinoma. This human ovarian cDNA expression database collects 41 patient samples which includes 13 samples of normal ovarian tumors (OVT), six samples of borderline of cancers (ROT), seven samples of ovarian cancer at stage I (OVCA-I) and 15 samples of ovarian cancer at stage Ill (OVCA-III). Each pathological sample contains a large number of genes (9600 genes). Hence oncogene analyzing and discovering is difficult. For this reason, a statistical testing method, t-test, is used to cull most of unconcerned genes in five different pathological stage classification cases. Then, these selected oncogenes are further used by artificial neural network (ANN) with five different classifications according to their gene expressions of pathological stages to set up a recognition system. This recognition system is used to show the efficiency of the proposed classification scheme. From the experimental results, the highest and lowest accuracy of five classification experiments is 100% and 89.47%. Moreover, this paper also proposed a novel t-test strategy to select more important oncogenes and increase lowest classification accuracy to 94.74%. The proposed scheme also can be used to develop a graphical user interface (GUI) bio-statistical or automatic diagnosis system for gene expression analysis to assist doctors and pathologists to analyze and diagnose ovarian cancer. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Ovarian cancer cDNA Oncogenes Gene expression analysis microarray database t-Test Artificial neural network (ANN)

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Local coexpression domains of two to four genes in the genome of Arabidopsis

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PLANT PHYSIOLOGY 2005年第2期138卷 923-934页

作者： Ren, XY Fiers, MWEJ Stiekema, WJ Nap, JP Plant Res Int NL-6700 AA Wageningen Netherlands Univ Wageningen & Res Ctr Plant Sci Grp Lab Mol Biol NL-6703 HA Wageningen Netherlands Ctr BioSyst Genom NL-6708 PB Wageningen Netherlands

Expression of genes in eukaryotic genomes is known to cluster, but cluster size is generally loosely defined and highly variable. We have here taken a very strict definition of cluster as sets of physically adjacent genes that are highly coexpressed and form so-called local coexpression domains. The Arabidopsis ( Arabidopsis thaliana) genome was analyzed for the presence of such local coexpression domains to elucidate its functional characteristics. We used expression data sets that cover different experimental conditions, organs, tissues, and cells from the Massively Parallel Signature Sequencing repository and microarray data (Affymetrix) from a detailed root analysis. With these expression data, we identified 689 and 1,481 local coexpression domains, respectively, consisting of two to four genes with a pairwise Pearson's correlation coefficient larger than 0.7. This number is approximately 1- to 5-fold higher than the numbers expected by chance. A small (5%-10%) yet significant fraction of genes in the Arabidopsis genome is therefore organized into local coexpression domains. These local coexpression domains were distributed over the genome. Genes in such local domains were for the major part not categorized in the same functional category (GOslim). Neither tandemly duplicated genes nor shared promoter sequence nor gene distance explained the occurrence of coexpression of genes in such chromosomal domains. This indicates that other parameters in genes or gene positions are important to establish coexpression in local domains of Arabidopsis chromosomes.

关键词： HUMAN TRANSCRIPTOME MAP NEIGHBORING GENES EXPRESSED GENES CAENORHABDITIS-ELEGANS FUNCTIONAL ANNOTATION INFORMATION RESOURCE microarray database CHROMOSOMAL DOMAINS GLOBAL ANALYSIS THALIANA

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A two stage grading approach for feature selection and classification of microarray data using Pareto based feature ranking techniques: A case study

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2020年第2期32卷 232-247页

作者： Dash, Rasmita Siksha O Anusandhan Univ Dept Comp Sc & Informat Technol Bhubaneswar 751030 Odisha India

High dimensional search space in microarray data with large number of genes and few dozen of samples increases the complexity of analysis of such databases. All the genes are not significant and hence informative genes are required to be extracted. So dimension reduction is necessary for this process. It is often found in literature that the ranking approaches are used for feature selection. Different ranking techniques may assign different rank to the same gene and the selection made based on these ranks may not be suitable for different problems. So use of one ranking technique may lead to rejection of some important genes and possibly selection of some insignificant genes. Such selection may degrade the performance of the classifier. To overcome this problem, here a bi-objective ranked based Pareto front technique is proposed. In this technique using two ranked based technique the Pareto optimal solution is generated with a set of features. For the experimental work, 21 models based on 7 feature ranking strategies are considered. Eight different microarray data are taken to find the suitable ranking combination for the work. A grading method is used to rank the models and statistical test is performed to validate the findings. (C) 2017 The Author. Production and hosting by Elsevier B.V.

关键词： Feature ranking technique Statistical analysis Pareto front Multi-objective optimization Classification technique microarray database

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ArrayPlex: distributed, interactive and programmatic access to genome sequence, annotation, ontology, and analytical toolsets

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GENOME BIOLOGY 2008年第11期9卷 R159-R159页

作者： Killion, Patrick J. Iyer, Vishwanath R. Univ Texas Austin Ctr Syst & Synthet Biol Inst Cellular & Mol Biol Sect Mol Genet & Microbiol Austin TX 78712 USA

ArrayPlex is a software package that centrally provides a large number of flexible toolsets useful for functional genomics, including microarray data storage, quality assessments, data visualization, gene annotation retrieval, statistical tests, genomic sequence retrieval and motif analysis. It uses a client-server architecture based on open source components, provides graphical, command-line, and programmatic access to all needed resources, and is extensible by virtue of a documented application programming interface. ArrayPlex is available at http://***/projects/arrayplex/.

关键词： Gene Ontology Application Programming Interface microarray database Client Computer Apache Tomcat

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