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 |
- A) Arrays
- B) Bioinformatics of Health and Disease
- C) Chemical and Pharmaceutical Informatics
- D) Comparative Genomics
- E) Databases
- F) Evolution
- G) Functional Genomics
- H) Gene Prediction
- I) Genome Annotation
- J) Genomics
- K) Interactions
- L) Machine Learning
- M) Population Genetics and Variation
- N) Proteomics
- O) Regulation
- P) Sequence Analysis
- Q) Structure and Function Prediction
- R) Systems Biology and Networks
- S) text mining
- T) Other (includes posters with fewer than 10 submissions)
Search Posters: |