Accepted Posters |
Category 'A'- Arrays' |
Poster A01 |
GEO EXPORTER : a tools to automate publishing of microarray data to Gene Expression Omnibus |
FRANCOIS MOREEWS- INRA |
FRANCOIS MOREEWS (INRA, SENAH); |
Short Abstract: The GEO exporter software allows validating, extraction and automatic publication of microarray data stored in BASE (BioArray Software Environment), a wildly used open source mi-croarray data management system, to Gene Expression Omnibus a reference microarray data repository. |
Long Abstract: Click Here |
Poster A02 |
Benchmarking genome-wide alternative splicing detection methods |
Raffaele Calogero- UniversitĂ di Torino |
Francesca Cordero (University of Torino, Dept. of Informatics); Cristina Della Beffa (University of Torino, Dept. of Clinical and Biological Sciences); |
Short Abstract: Exon 1.0 ST microarray platform allows to investigate changes in isoforms pattern of a transcript. Since very little is known on genome-wide methods for Alternative Splicing detection (ASd), the effects of data pre-processing and statistical methods on ASd sensitivity were investigated in a semi-synthetic experiment embedding 975 exon skipping events. |
Long Abstract: Click Here |
Poster A03 |
I/NI-Calls: : a novel latente variable model for unsupervised feature selection |
Djork Clevert- Johannes Kepler University Linz |
Willem Talloen (Johnson & Johnson Pharmaceutical Research & Development, ); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); Dhammika Amaratunga (Johnson & Johnson Pharmaceutical Research & Development, ); Luc Bijnens (Johnson & Johnson Pharmaceutical Research & Development, ); Stefan Kass (Johnson & Johnson Pharmaceutical Research & Development, ); Hinrich W.H. Göhlmann (Johnson & Johnson Pharmaceutical Research & Development, ); |
Short Abstract: None On File |
Long Abstract: Click Here |
Poster A04 |
Directed Search of Large Microarray Compendia |
Matthew Hibbs- Princeton University |
David Hess (Princeton University, Lewis-Sigler Institute for Integrative Genomics); Chad Myers (Princeton University, Lewis-Sigler Institute for Integrative Genomics); Curtis Huttenhower (Princeton University, Lewis-Sigler Institute for Integrative Genomics); Kai Li (Princeton University, Department of Computer Science); Olga Troyanskaya (Princeton University, Lewis-Sigler Institute for Integrative Genomics); |
Short Abstract: None On File |
Long Abstract: Click Here |
Poster A05 |
A Probe-Treatment-Reference (PTR) Model for the Analysis of Oligonucleotide Expression Microarray |
Huanying Ge- University of Southern California |
Chao Cheng (University of Southern California, Molecular and Computational Biology); Lei Li (University of Southern California, Molecular and Computational Biology); |
Short Abstract: We proposed a Probe-Treatment-Reference (PTR) model to streamline normalization and summarization by a strategy of reference selection in microarray pre-processing. It is a general framework to deal with the issue of reference selection and can readily be applied to existing normalization algorithms such as the invariant-set, sub-array and quantile method. |
Long Abstract: Click Here |
Poster A07 |
The Unique Probe Selector (Version 2.0): A Comprehensive Web Service of Oligonucleotide Design for Hybridization in Low‐ and High‐Throughput Experiments |
Chung-Yen Lin- Academia Sinica |
No additional authors |
Short Abstract: TheUPS 2.0 evaluates probe-to-target hybridization under a user-defined conditionin silico to ensure high-performance hybridization and minimizes the possibility ofnon-specific reactions.The three options will cover almost all kind of the background condition of a hybridization experiment. UPS is running for more than one year and freelyaccessible at http://array.iis.sinica.edu.tw/ups/. |
Long Abstract: Click Here |
Poster A08 |
ParaSAM: A parallelized version of SAM algorithm. |
Ashok Sharma- Medical College of Georgia |
Nikhil Garge (Medical College of Georgia, Center for Biotechnology and Genomic Medicine); Steven Whitfield (Medical College of Georgia, Center for Biotechnology and Genomic Medicine); Robert Podolsky (Medical College of Georgia, Center for Biotechnology and Genomic Medicine); Richard McIndoe (Medical College of Georgia, Center for Biotechnology and Genomic Medicine); |
Short Abstract: Significance Analysis of Microarrays (SAM) is one of the most popular methods for microarray data analysis. We have developed a Windows application “ParaSAM” that implements a parallelized version of SAM. ParaSAM is not only faster, but can also analyze larger datasets, which is currently not possible using existing implementations. |
Long Abstract: Click Here |
Poster A09 |
Signature Evaluation Tool (SET): a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures |
Chih-Hung Jen- Yang-Ming University |
Tsun-Po Yang (Mr, Institute of Microbiology and Immunology, National Yang-Ming University); Chien-Yi Tung (Ph.D, Institute of Microbiology and Immunology, National Yang-Ming University); Shu-Han Su (Mrs, Institute of Microbiology and Immunology, National Yang-Ming University); Chi-Hung Lin (Prof, Institute of Microbiology and Immunology, National Yang-Ming University); Ming-Ta Hsu (Prof, Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center); Hsei-Wei Wang (Prof, Institute of Microbiology and Immunology, National Yang-Ming University); |
Short Abstract: Many feature selection and classification tools have been developed for acquiring optimal gene expression signatures for distinguishing sample groups. However, a flexibility tool assisting evaluation of user-defined signature is in high demand by clinical researchers. We present SET to evaluate and visualize the sample-discrimination ability of a given expression signature. |
Long Abstract: Click Here |
Poster A10 |
ESTIMATION OF CELL CYCLE REGULATED GENES USING ANCHOR GENES AND NON-METRIC MULTIDIMENSIONAL SCALING |
Y-h. Taguchi- Chuo University |
No additional authors |
Short Abstract: We have applied non-metric multidimensional scaling (nMDS) to cell division cycle microarray experiments of fission yeast to decide cell cycle regulated genes without sinusoidal fittings. Selected set of genes is substantially different from those by sinusoidal fittings when consistency with known cell cycle regulated genes is assumed. |
Long Abstract: Click Here |
Poster A11 |
Analysis of DNA copy number alterations with non-metric multidimensional scaling method |
Fumiaki Kataoka- Chuo University |
Y-h Taguchi (Chuo University, Department of Physics); |
Short Abstract: DNA copy number alterations are the cause of many genetic diseases. However, there are much noise in the observation. Thus, it is not easy to estimate how many number of copies are in each genome. In this paper, we apply non-metric multidimensional scaling method to estimate DNA copy number alterations. |
Long Abstract: Click Here |
Poster A12 |
Exon level integration of proteomics and microarray data |
Danny Bitton- Paterson Institute for Cancer Research |
Michal Okoniewski (Paterson Institute for Cancer Research , Applied Computational Biology and Bioinformatics Group ); Yvonne Connolly (Paterson Institute for Cancer Research , Cancer Research UK, Proteomics Service); Crispin Miller (Paterson Institute for Cancer Research , Applied Computational Biology and Bioinformatics Group); |
Short Abstract: Previous studies have generally reported low correlation between mRNA expression level and protein abundance. Using the genome as a reference, we integrated iTRAQ quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. Using this approach, high correspondence was found between the genome and proteome (r=0.808). |
Long Abstract: Click Here |
Poster A13 |
Chipster – user friendly analysis tool for DNA microarray data |
Eija Korpelainen- CSC - the Finnish IT Center for Science |
Aleksi Kallio (CSC - the Finnish IT Center for Science, Software engineering); Taavi Hupponen (CSC - the Finnish IT Center for Science, Software engineering); Jarno Tuimala (CSC - the Finnish IT Center for Science, Software engineering); Petri Klemelä (CSC - the Finnish IT Center for Science, Software engineering); |
Short Abstract: Chipster (http://chipster.csc.fi/) enables more researchers to benefit from the method develop¬ment in the R/Bioconductor project. This open source software offers an intuitive graphical user interface to a comprehensive collec¬tion of up-to-date analysis methods. Chipster supports Affymetrix, Illumina, Agilent and cDNA arrays and runs on Windows, Linux and Mac. |
Long Abstract: Click Here |
Poster A14 |
A comparison of microarray differential expression detection methods based on consistency with functional annotations |
François Lefebvre- Université de Montréal |
Sebastien Lemieux (Institute for Research in Immunology and Cancer, Functional and Structural Bioinformatics); |
Short Abstract: In microarray data analysis, many preprocessing methods and statistical procedures are available to assess differential expression. We compared them based on their ability to produce rankings consistent with sets of related genes. Surprisingly, results on the Affymetrix platform indicates that the fold-change criterion performs best in terms of this consistency. |
Long Abstract: Click Here |
Poster A15 |
FARMS: a probabilistic latent variable model for summarizing Affymetrix array data at probe level |
Djork Clevert- Johannes Kepler University Linz |
Djork-Arné Clevert (Johannes Kepler University Linz, Institute of Bioinformatics); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); |
Short Abstract: High-density oligonucleotide microarrays, and in particular Affymetrix GeneChip arrays, are successfully applied in many areas of biomedical research. We propose a new summarization method called "Factor Analysis for Robust Microarray Summarization" (FARMS). FARMS automatically models the probe-specific measurement error and is optimized by Bayesian maximum a posteriori estimation. |
Long Abstract: Click Here |
Poster A16 |
A customized class of functions for modeling and clustering gene expression profiles in embryonic stem cells |
Shenggang Li- University of Ottawa |
Miguel Andrade-Navarro (Max Delbruck Center for Molecular Medicine, Berlin-Buch); David Sankoff (University of Ottawa, Mathematics and Statistics); |
Short Abstract: We cluster time course gene expression data for differentiating mouse embryonic stem cells, based on a hyperbolic function model. We take into account the genetic function profile induced or controlled by other regulators, unobservable random effects producing heterogeneity within gene clusters, and autoregressive components defining the stochastic and autocorrelation structures. |
Long Abstract: Click Here |
Poster A17 |
Segmentation of Tiling Array Data |
Georg Zeller- Max Planck Society |
Timo Sachsenberg (Max Planck Institute for Developmental Biology, Molecular Biology); Sascha Laubinger (Max Planck Institute for Developmental Biology, Molecular Biology); Detlef Weigel (Max Planck Institute for Developmental Biology, Molecular Biology); Gunnar Raetsch (Max Planck Society, Friedrich Miescher Laboratory); |
Short Abstract: Transcriptome studies using tiling microarrays have uncovered a wealth of transcription beyond current genome annotations. For the central task of identifying novel transcripts, we developed mSTAD, a novel machine learning method. Evaluation on Arabidopsis tiling array data and annotated transcripts indicates markedly higher accuracy than e.g. Affymetrix' transfrag method. |
Long Abstract: Click Here |
Poster A18 |
Fishing for seasonal gene expression patterns in neuroendocrine brain from multiple microarray datasets |
Dapeng Zhang- University of Ottawa |
Dapeng Zhang (University of Ottawa, Biology); Huiling Xiong (University of Ottawa, Biology); Jason Popesku (University of Ottawa, Biology); Jan Mennigen (University of Ottawa, Biology); Christopher Martyniuk (University of Ottawa, Biology); Kate Crump (University of Ottawa, Biology); Xuhua Xia (University of Ottawa, Biology); Vance Trudeau (University of Ottawa, Biology); |
Short Abstract: We define for the first time global expression characters in the brain during a seasonal reproductive cycle of a vertebrate model species. Data was extracted from multiple goldfish microarray experiments utilizing comprehensive normalization, differential gene identification, multivariate, and gene ontology analysis. |
Long Abstract: Click Here |
Poster A19 |
Clustering of genome-wide histone K79 methylation profiles distinguishes MLL-AF4 acute lymphoblastic leukemias from both normal lymphoblasts and MLL-germline ALLs. |
Madeleine Lemieux- Dana-Farber Cancer Institute |
Andrei Krivtsov (Children's Hospital, Harvard Medical School, Boston, Hematology/Oncology); Zhaohui Feng (Children's Hospital, Harvard Medical School, Boston, Hematology/Oncology); Sridar Vempati (Dana-Farber Cancer Institute, Harvard Medical School, Boston, Pediatric Oncology); Scott Armstrong (Children's Hospital & Dana-Farber Cancer Institute, Harvard Medical School, Boston, Hematology/Oncology & Pediatric Oncology); Andrew Kung (Dana-Farber Cancer Institute & Children's Hospital, Harvard Medical School, Boston, Pediatric Oncology & Hematology/Oncology); |
Short Abstract: Murine and human MLL-rearranged leukemias consistently clustered away from phenotypically similar normal or MLL-germline leukemic lymphoblasts based on their genome-wide histone K79 methylation profiles as assessed by ChIP-chip on Affymetrix promoter tiling arrays. This consistenly aberrant methylation suggests that MLL-rearranged leukemias might be sensitive to drugs targeting H3K79 methyltransferases. |
Long Abstract: Click Here |
Poster A20 |
Investigating the Mechanism of Adipose Tissue Reaccumulation Following Suction Lipectomy Using Exon Array Analysis. |
Tzu Lip Phang- University of Colorado Denver |
Nicole Stob (University of Colorado Denver, Endocrinology); Robert Eckel (University of Colorado Denver, General Clinical Research Center); |
Short Abstract: Alternative Splicing (AS) is an important regulatory mechanism in gene expression. We examine the phenomena of post-liposuction adipose tissue reaccumulation using exon array analysis. Our study found significant AS between the non-surgical and suction lipectomy groups, which provide a prospective model to explain the observation. |
Long Abstract: Click Here |
Poster A21 |
Tissue specificity measured by differences in information content between target tissue and whole tissue |
Yoichi Takenaka- Graduate School of Information Science and Technology, Osaka University |
Hideo Matsuda (Graduate School of Information Science and Technology, Osaka University, Department of Bioinformatics Engineering); |
Short Abstract: The important goals of gene expression analyses are to reveal gene functions and the features of tissues. We propose a method for measuring tissue-specificity of gene ontology terms by utilizing addable gene expression profiles. The validity of our measurement was confirmed through and tissue-specific enzymes and cell junctions. |
Long Abstract: Click Here |
Poster A22 |
A preamble to a novel tiling array probe scoring system |
Olof Emanuelsson- Stockholm University |
No additional authors |
Short Abstract: We present a preamble to a novel tiling array probe scoring system, investigating ENCODE transcriptional array data with respect to a number of probe-sequence features including melting temperature and free energy. We conclude that many of these features may be useful as part of the novel scoring system. |
Long Abstract: Click Here |
Poster A23 |
A Computational Framework for the Detection of Alternative Exon Usage using Affymetrix Exon Arrays |
Ted Laderas- Oregon Health & Science University |
Michael Mooney (OHSU, Medical Informatics and Outcomes Research); Nikki Walter (OHSU, Portland Alcohol Research Center); John Belknap (OHSU, Portland Alcohol Research Center); Robert Hitzemann (OHSU, Portland Alcohol Research Center); Shannon McWeeney (OHSU, OHSU Cancer Institute); |
Short Abstract: Alternative splicing is a relatively prevalent phenomenon, with an estimated 3.5 alternative transcripts per gene. We present a software framework implemented in R/Bioconductor for the analysis of Affymetrix Exon Array data. This transcript model-based framework enables the user to detect alternative splice variants based on the Ensembl Transcript structure. |
Long Abstract: Click Here |
Poster A24 |
Cross-species, cross-platform meta-analysis of acute lung injury microarrays and validation of injury expression profiles in human models of lung transplantation |
Xinchen Wang- University of Toronto / St. Michael's Hospital |
Claudia dos Santos (University of Toronto / St. Michael's Hospital, Critical Care Medicine); Pingzhao Hu (Hospital for Sick Children / The Centre for Applied Genomics, Genetics and Genomics Biology); Celia Greenwood (Hospital for Sick Children / The Centre for Applied Genomics, Genetics and Genomics Biology); Joseph Beyene (Hospital for Sick Children, Child Health Evaluative Sciences); Shaf Keshavjee (University Health Network, Thoracic Surgery Research); Masaki Anraku (University Health Network, Thoracic Surgery Research); Arthur Slutsky (St. Michael's Hospital, Critical Care Medicine); Mark Cameron (University Health Network, Experimental Therapeutics); David Kelvin (University Health Network, Experimental Therapeutics); Marcelo Cypel (University Health Network, Thoracic Surgery Research); Josef Penninger (Austrian Academy of Sciences, Institute of Molecular Biotechnology); Yumiko Imai (The Global Center of Excellence program, Akita University Graduate School of Medicine); |
Short Abstract: We conducted a novel meta-analysis of ventilator-induced lung injury-related microarray studies carried across multiple platforms, species and injury models. Sets of significantly altered genes were identified, including those not reported by constituent studies alone. Validity of this method was confirmed through classification and prediction of animal and human injury phenotypes. |
Long Abstract: Click Here |
Poster A25 |
cn.FARMS - a probabilistic model to detect DNA copy numbers |
Djork Clevert- Johannes Kepler University Linz |
Marianne Tuefferd (University Paris XI, Clinical Genomic Epidemiology); An De Bondt (Johnson & Johnson Pharmaceutical Research & Development, Functional genomics); Willem Talloen (Johnson & Johnson Pharmaceutical Research & Development, Functional genomics); Hinrich W.H. Göhlmann (Johnson & Johnson Pharmaceutical Research & Development, Functional genomics); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); |
Short Abstract: High-density oligonucleotide microarrays, and in particular Affymetrix Mapping or SNP arrays offer the opportunity to get a genome-wide view on copy number alterations and are increasingly used in oncology. We present a probabilistic latent variable model, called cn.FARMS, that takes probe level information to model the the correlation in the observed data. |
Long Abstract: Click Here |
Accepted Posters |
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