ISMB 2008 ISCB

16th Annual
International Conference
Intelligent Systems
for Molecular Biology


Metro Toronto Convention Centre (South Building)
Toronto, Canada


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

















Accepted Posters
Category 'M'- Population Genetics and Variation'
Poster M01
RAPD Analysis of Iranian Pomegranate (Punica granatum L.) Cultivars
ZAHRA NOURMOHAMMADI- Tarbiat Modares university
MASOUD SHEIDAI (professor of Genetics, Biology);
Short Abstract: None On File
Long Abstract: Click Here

Poster M02
Discovering Common Sequence Variation in Arabidopsis thaliana
Ratsch Gunnar- Friedrich Miescher Laboratory, Max Planck Society
Richard Clark (Max Planck Institute for Developmental Biology, Molecular Biology); Gabriele Schweikert (Friedrich Miescher Laboratory, Max Planck Society, Machine Learning in Biology); Christopher Toomajian (University of Southern California, Biological Sciences); Stephan Ossowski (Max Planck Institute for Developmental Biology, Molecular Biology); Georg Zeller (Friedrich Miescher Laboratory, Max Planck Society, Machine Learning in Biology); Paul Shinn (NIH, Chemical Genomics); Norman Warthmann (Max Planck Institute for Developmental Biology, Molecular Biology); Tina Hu (University of Southern California, Biological Sciences); Glenn Fu (Perlegen Sciences, n/a); David Hinds (Perlegen Sciences, n/a); Huaming Cheng (Salk Institute, Biology); Kelly Frazer (Perlegen Sciences, n/a); Daniel Huson (University of Tübingen, Bioinformatics); Bernhard Schölkopf (Max Planck Institute for Biological Cybernetics, Empirical Inference); Magnus Nordborg (University of Southern California, Biological Sciences); Joseph Ecker (Salk Institute, Biology); Detlef Weigel (Max Planck Institute for Developmental Biology, Molecular Biology); Korbinian Schneeberger (Max Planck Institute for Developmental Biology, Molecular Biology); Anja Bohlen (Friedrich Miescher Laboratory, Max Planck Society, Machine Learning in Biology);
Short Abstract: None On File
Long Abstract: Click Here

Poster M03
Bayesian Networks meet Gaussian processes in modelling genetical genomics
Christoph Dieterich- Max-Planck-Society
Markus Franz (Max-Planck-Society, MPI for Developmental Biology);
Short Abstract: Genetic variation determines phenotypic outcomes to a considerable degree. Genotype and phenotype are dynamically linked by an intimidating complexity of biological processes. We propose Bayesian networks to model the relations between genotype, QTLs in intermediate levels and phenotype. We extend Bayesian Networks with Gaussian processes to capture non-linear dependencies.
Long Abstract: Click Here

Poster M04
KAREdb – Korea Association Resource Database
Jee Yeon Heo- Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention
Hyo-Jeong Ban (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Bio-Medical Informatics); Young Jin Kim (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Min Jin Go (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Dankyu Yoon (Seoul National University, Interdisciplinary program in Bioinformatics); Taesung Park (College of National Science, Seoul National University, Department of Statistics); Bermseok Oh (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Yoon Shin Cho (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Hyung-Lae Kim (National Institute of Health, Korea Center for Disease Control and Prevention, Center for Genome Science);
Short Abstract: We developed KAREdb to integrate results obtained from Korea Association Resource (KARE) project. The result of quantitative trait (QT) association analyses and several databases are integrated into KAREdb. It is a useful web-accessible resource for researchers and clinicians who are interested in the integrated information regarding genetic factors resulted from GWA study.
Long Abstract: Click Here

Poster M05
Dynamics of spread of the HbS gene in Sudanese village populations
Niven Salih- Institute of endemic diseases, University of Khartoum
Muntasir Ibrahim (Institute of Endemic Diseases,University of khartoum, Molecular biology); Dominic Kwiatkowski (Wellcome trust centre for human genetics, malaria research); Hiba Salaheldein (Institute of Endemic Diseases, Molecular biology); Hani Ishag (Institute of endemic diseases, Molecular biology);
Short Abstract: We investigate role of HbS in protection from clinical malaria in different populations. HbS Frequencies within HWE. The HbS trait shown significant protection from clinical malaria as seen from Odd ratios. HbS frequencies simulation for fifty generations shows decrease in frequency in Hausa, while reaching balancing polymorphim state in massalit
Long Abstract: Click Here

Poster M06
Error Tolerant Sibship Reconstruction
Tanya Berger-Wolf- University of Illinois at Chicago
Saad Sheikh (University of Illinois at Chicago, Computer Science); Mary Ashley (University of Illinois at Chicago, Biological Science); Isabel Caballero (University of Illinois at Chicago, Biological Science); Wanpracha Chaovalitwongse (Rutgers University, Industrial and Systems Engineering); Bhaskar Dasgupta (University of Illinoi at Chicago, Computer Science);
Short Abstract: Kinship analysis using genetic data is important for many biological applications, form evolutionary to
conservation biology. We present an error-tolerant method for reconstructing sibling relationships based on consensus techniques. Our method achieves over 90% in most cases in our tests on simulated and biological data.
Long Abstract: Click Here

Poster M07
Polymorphism due to multiple nucleotide substitutions at a codon site in Ciona savignyi
Nilgun Donmez- University of Toronto
Georgii Bazykin (Institute for Information Transmission Problems of the Russian Academy of Sciences, -); Michael Brudno (University of Toronto, Department of Computer Science); Alexey Kondrashov (University of Michigan, Life Sciences Institute and Department of Ecology and Evolutionary Biology);
Short Abstract: Comparing two haploid genotypes of a Ciona savignyi individual, we identify codons that differ by two non-synonymous substitutions. Using Ciona intestinalis as outgroup reveals that both substitutions happen within the same lineage more than expected by chance, indicating that a fraction of non-synonymous differences between C. savignyi individuals are adaptive.
Long Abstract: Click Here

Poster M08
Copy number variation Analysis in Korean population
Gil-Mi Ryu- National Institute of Health, Korea
Young-Jin Kim (National Institute of Health, Korea, Division of Functional Genomics); Kyung-So Oh (National Institute of Health, Korea, Division of Bio-Medical Informatics); Hyung-Lae Kim (National Institute of Health, Korea, Division of Functional Genomics); Bermseok Oh (National Institute of Health, Korea, Division of Functional Genomics); Kyu-Won Kim (Seoul National University, College of Pharmacy); Young-Youl Kim (National Institute of Health, Korea, Division of Bio-Medical Informatics);
Short Abstract: We detected copy number variations (CNVs) in 104 normal samples in Korean population. For reporting the ethnic difference of CNVs, we compared with CEU, CHB, JPT, YRI and Korean. In this study, we could investigate genome-wide characteristics of CNV in various populations and disease susceptibility of Korean specific population.
Long Abstract: Click Here

Poster M09
Machine Learning for Polymorphism Detection in Rice
Regina Bohnert- Friedrich Miescher Laboratory Of The Max Planck Society
Georg Zeller (Max Planck Society, Friedrich Miescher Laboratory); Richard M. Clark (Max Planck Institute for Developmental Biology, Department of Molecular Biology); Kevin L. Childs (Michigan State University, Department of Plant Biology); Victor Ulat (International Rice Research Institute, Metro Manila 1301); Renee Stokowski (Perlegen Sciences, Inc., 2021 Stierlin Court, Mountain View, CA 94043); Dennis Ballinger (Perlegen Sciences, Inc., 2021 Stierlin Court, Mountain View, CA 94043); Kelly Frazer (Perlegen Sciences, Inc., 2021 Stierlin Court, Mountain View, CA 94043); David Cox (Perlegen Sciences, Inc., 2021 Stierlin Court, Mountain View, CA 94043); Richard Bruskiewich (International Rice Research Institute, Metro Manila 1301); C. Robin Buell (Michigan State University, Department of Plant Biology); Jan Leach (Colorado State University, Bioagricultural Sciences and Pest Management); Hei Leung (International Rice Research Institute, Metro Manila 1301); Kenneth L. McNally (International Rice Research Institute, Metro Manila 1301); Detlef Weigel (Max Planck Institute for Developmental Biology, Department of Molecular Biology); Gunnar Rätsch (Max Planck Society, Friedrich Miescher Laboratory);
Short Abstract: Analysing a huge set of hybridisation data from resequencing arrays with machine learning methods, we revealed hundreds of thousands polymorphisms in 20 diverse cultivars of rice on a genome-wide scale. This inventory of sequence variation constitutes an unprecedented resource for further functional studies and modern breeding of rice.
Long Abstract: Click Here

Poster M10
Reconstructability Analysis Detects Genetic Variation Associated with Gene Expression
Beth Wilmot- Oregon Health Science Univ
Martin Zwick (Portland State University, Systems Science Graduate Program); Shannon McWeeney (Oregon Health & Science Univ, Division of Biostatistics, Department of Public Health and Preventive Medicine);
Short Abstract: Reconstructability analysis (RA) is an information-theoretic methodology for multivariate categorical data that overlaps log-linear modeling and Bayesian networks. Using the simplest RA analysis, we detected associations between SNPs and binned gene expression values in a publicly available data set. Both main effects and epistatic interactions were identified.
Long Abstract: Click Here

Poster M11
Transposable Elements as Drivers of Malaria Resistance
Isabel Holmquist- Imperial College London
Michael Stumpf (Imperial College London, Division of Molecular Biosciences);
Short Abstract: Using comprehensive simulations of transposable element (TE) population dynamics allow us to disentangle the molecular and population level factors influencing TE spread through natural populations. Coupled with a bioinformatic analysis of Anopheles TEs we can gain insights into the feasibility of creating non-malaria-transmitting mosquito populations in the wild.
Long Abstract: Click Here

Poster M12
Mapping potential regulatory SNPs in ENCODE region
Grace Huang- Joint CMU-Pitt Computational Biology Program
Grace T. Huang (Joint CMU-Pitt Computational Biology Program, Department of Computational Biology); Panayiotis V. Benos (University of Pittsburgh Medical School, Department of Computational Biology);
Short Abstract: We attempt to map gene expression variances among individuals to Single Nucleotide Polymorphisms (SNPs) that reside within promoter regions. Significant associations between genotype and expression were found for 13% of the genes in the ENCODE region. A non-linear predictor was also developed to identify potential cis-acting SNPs.
Long Abstract: Click Here



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