ISMB 2008 ISCB

16th Annual
International Conference
Intelligent Systems
for Molecular Biology


Metro Toronto Convention Centre (South Building)
Toronto, Canada


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

















Accepted Posters
Category 'O'- Regulation'
Poster O01
Combined Analysis Reveals a Core Set of Cycling Genes
Yong Lu- Carnegie Mellon University
Shaun Mahony (Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory); Panayiotis Benos (University of Pittsburgh Medical School, Department of Computational Biology); Roni Rosenfeld (Carnegie Mellon University, Machine Learning Department); Itamar Simon (Hebrew University Medical School, Department of Molecular Biology); Linda Breeden (Fred Hutchinson Cancer Center, Basic Sciences Division); Ziv Bar-Joseph (Carnegie Mellon University, Computer Science Department);
Short Abstract: None On File
Long Abstract: Click Here

Poster O02
A Semi-Supervised Method for Predicting Transcription Factor-Gene Interactions in Escherichia coli.
Jason Ernst- Carnegie Mellon University
Qasim Beg (University of Pittsburgh, Pathology); Krin Kay (University of Pittsburgh, Pathology); Gábor Balázsi (University of Texas M. D. Anderson Cancer Center, Systems Biology); Zoltán Oltvai (University of Pittsburgh, Pathology); Ziv Bar-Joseph (Carnegie Mellon University, Machine Learning);
Short Abstract: None On File
Long Abstract: Click Here

Poster O03
MTAP: The Motif Tool Assessment Platform
Daniel Quest- University of Nebraska Medical Center
Kathryn Dempsey (University of Nebraska Omaha, Computer Science); Mohammad Shafiullah (University of Nebraska at Omaha, Computer Science); Dhundy Bastola (University of Nebraska at Omaha, Information Science and Technology); Hesham Ali (University of Nebraska at Omaha, Information Science and Technology);
Short Abstract: None On File
Long Abstract: Click Here

Poster O04
A Nucleosome-Guided Map of Transcription Factor Binding Sites in Yeast
Raluca Gordan- Duke University
Leelavati Narlikar (Duke University, Computer Science); Alexander Hartemink (Duke University, Computer Science);
Short Abstract: None On File
Long Abstract: Click Here

Poster O05
Effects of disease-related mutations on transcription factor binding
Kirsti Laurila- Tampere University of Technology
Harri Lähdesmäki (Tampere University of Technology, Department of Signal Processing);
Short Abstract: We have studied computationally the effect of disease-related regulatory mutations on
transcription factor binding affinity. The results have been
compared with experimentally verified results.
We have also investigated the
statistical properties of the transcription factor binding affinity changes
according to mutation types. Valuable results have been obtained for
laboratory tests.
Long Abstract: Click Here

Poster O06
A Bayesian approach to multi-organism phylogenetic footprinting
Elizabeth Hellen- Bsms
No additional authors
Short Abstract: Predicting functional transcription factors in-silico is an important and difficult task,
it will enable us to predict regulatory and functional information about genes. By tracking a transcription factor, predicted in humans, through a number of other species
we can infer whether the motif is likely to be functional.
Long Abstract: Click Here

Poster O07
Combinatorial influence of environmental parameters on transcription factor activity
Theo Knijnenburg- Delft University of Technology
Lodewyk Wessels (The Netherlands Cancer Institute, Department of Molecular Biology); Marcel Reinders (Delft University of Technology, Department of Mediamatics);
Short Abstract: We propose an inference algorithm that models the influence of environmental parameters on gene expression. The approach is based on chemostat steady-state experiments, where cultivation parameters are accurately controlled and measured. The observed transcript levels are explained by inferring the activity of TFs in response to combinations of cultivation parameters.
Long Abstract: Click Here

Poster O08
Analysis of potential RNA antiterminator sites in operons encoding phosphoenol-dependent phosphotransferase systems
Anna Lyubetskaya- Lomonosov Moscow State University
Mikhail Gelfand (Institute for Information Transmission Problems of the Russian Academy of Sciences, Research and Training Center on Bioinfirmatics);
Short Abstract: BglG-like regulatory proteins regulate phosphoenol-dependent
phosphotransferase systems (PTS) performing sugar import in bacteria. They
act via antiterminator-terminator sites located in 5'-untranslated regions
of PTS operons. A comparative genomic analysis of all bacterial genomes
encoding PTS systems revealed new instances of the regulatory sites in
several diverse species.
Long Abstract: Click Here

Poster O09
Computational Analysis of the Regulation of Co-expressed Gene Sets Across Fungal Species
Robert Gross- Dartmouth College
Viktor Martyanov (Dartmouth College, Biology); Amy Gladfelter (Dartmouth College, Biology); Dhanalakshmi Nair (Dartmouth College, Biology);
Short Abstract: We used our ensemble motif finding program, SCOPE, to analyze gene regulation in 25 fungal species. For a regulatory motif, its position distribution upstream of the gene set, its sequence degeneracy and its juxtaposition with neighboring motifs are important to gene regulation. The results are consistent with fungal phylogeny.
Long Abstract: Click Here

Poster O10
Graph-based clustering of heterogeneous genome-wide datasets for the prediction of regulatory networks
Kozo Nishida- Nara Institute of Science and Technology
Md. Altaf-Ul-Amin (Nara Institute of Science and Technology, Information Science); Hirokazu Kobayashi (Nara Institute of Science and Technology, Information Science); Hiroko Asahi (Nara Institute of Science and Technology, Information Science); Shigehiko Kanaya (Nara Institute of Science and Technology, Information Science);
Short Abstract: To clarify comprehensive gene regulation networks, we have developed a graph-based clustering algorithm involving differential expression analysis of transcription factor deletion mutant and correlation analysis of DNA microarray datasets in different time-series growth conditions. The present study predicts regulatory networks linking transcription factors to their targets in Bacillus subtilis genome.
Long Abstract: Click Here

Poster O11
Computational Prediction of Gene Regulation Components in Brain Cells
Lakshmanan Iyer- Tufts University
Christopher Parkin (Center for Neuroscience Research, Department of Neuroscience); Rob Jackson (Center for Neuroscience Research, Department of Neuroscience);
Short Abstract: Investigating transcription regulatory mechanisms is important for understanding the development and function of the brain. Transcriptome databases for various neural cell types have been made available very recently. We have used motif discovery methods to identify novel transcriptional regulators and propose their roles in the gene regulation program.
Long Abstract: Click Here

Poster O12
Identification of Transcription Factor Interacting Pairs by Mining ChIP-chip Data
Mei-Ju Chen- National Taiwan University
Chien-Yu Chen (National Taiwan University, Dept. of Bio-Industrial Mechatronics Engineering);
Short Abstract: This poster presents a study that uses the mining results of a recently published paper titled "Discovering Gapped Binding Sites of Yeast Transcription Factors" (PNAS, Vol. 105(7), pp. 2527-2532, 2008) to identify potential TF-TF interactions directly from ChIP-chip data.
Long Abstract: Click Here

Poster O13
SplicingModeler: A computational model for cis-acting RNA element prediction
Xin Wang- Indiana University
Jeremy Sanford (Indiana University, Biochemistry and Molecular Biology); Yunlong Liu (Indiana University, Medicine);
Short Abstract: A computational model is designed to predict cis-acting RNA elements which contribute to the complexity of splice variants in different conditions. This model is implemented using Exon Array, Exon Junction Microarray and SpliceArray to identify putative regulatory motifs responsible for the splicing regulation in tissue-specific, stage-specific and drug-specific alternative splicing.
Long Abstract: Click Here

Poster O14
Analysis of cis regulation of gene expression across different regions of human brain.
Viktoriya Strumba- University of Michigan
Margit Burmeister (University of Michigan, MBNI); Tom Blackwell (University of Michigan, CCMB);
Short Abstract: We tested association between gene expression and SNPs near 89 candidate genes for psychiatric disorders in 9 brain regions. While no result was experiment-wide significant, we identified several associations that were consistent in more than one brain region.
Long Abstract: Click Here

Poster O15
Model-based prediction of transcription factor and microRNA regulation in prostate cancer after androgen ablation therapy
Guohua Wang- Indiana University
Yunlong Liu (Indiana University, Medicine);
Short Abstract: Based on global gene expression patterns, a model-based computational approach is designed to indentify the transcription factors and microRNAs that potentially cause gene expression change. The model predicted 5 transcription factors and 7 microRNAs to be potentially responsible for hormone dependency in androgen-dependent and –independent prostate tumors.
Long Abstract: Click Here

Poster O16
Use of Normalized Compression Distance (NCD) Metrics to Classify Drosophila Core Promoters
Hollis Wright- OHSU
Shannon McWeeney (OHSU, DMICE/OCTRI/Divison of Biostatistics);
Short Abstract: Normalized Compression Distance (NCD) metrics have been explored as measures of similarity for classification of biological sequences such as proteins. We report the first use of NCD for classification of Drosophila core promoters based on content of particular motifs. Classification accuracy varies dependent upon the compressor and parameters used.
Long Abstract: Click Here

Poster O17
Use of Normalized Compression Distance (NCD) Metrics to Classify Drosophila Core Promoters
Hollis Wright- OHSU
Shannon McWeeney (OHSU, DMICE/OCTRI/Divison of Biostatistics);
Short Abstract: Normalized Compression Distance (NCD) metrics have been explored as measures of similarity for classification of biological sequences such as proteins. We report the first use of NCD for classification of Drosophila core promoters based on content of particular motifs. Classification accuracy varies dependent upon the compressor and parameters used.
Long Abstract: Click Here

Poster O18
MetaProm: a neural network based meta-predictor for alternative human promoter prediction
Junwen Wang- The University of Hong Kong
Junwen Wang (University of Hong Kong, Biochemistry); Lyle Ungar (University of Pennsylvania, Computer and Information Science); Hung Tseng (University of Pennsylvania, Dermatology); Sridhar Hannenhalli (University of Pennsylvania, Genetics);
Short Abstract: We evaluated the performances of current major promoter prediction programs on a genome-wide scale, with emphasis on alternative promoters. We developed an ANN based meta-predictor program that improved accuracy of promoter prediction. We further discovered that the 5' alternative promoters are more likely to be associated with a CpG island.
Long Abstract: Click Here

Poster O19
Gene networks involved in desiccation-tolerance acquisition and the osmotic stress response
Maital Ashkenazi- The Hebrew University of Jerusalem
No additional authors
Short Abstract: Acquisition of seed-desiccation tolerance is accompanied by water loss. Some of the genes expressed at this developmental stage are known to be involved in the response to osmotic stress. Using co-expression networks, we detected conserved sub-networks of genes that are co-regulated under these developmental and environmental water-deficit conditions, suggesting a common regulation mechanism.
Long Abstract: Click Here



Accepted Posters
View Posters By Category
Search Posters:
Poster Number Matches
Last Name
Co-Authors Contains
Title
Abstract Contains