| Accepted Posters |
| Category 'K'- Interactions' |
| Poster K01 |
| Determination of Enriched Histone Modifications in Non-Genic Portions of the Human Genome |
| Jeffrey Rosenfeld- Cold Spring Harbor Laboratory |
| Zhibin Wang (NHLBI, 4. Laboratory of Molecular Immunology); Dustin Schones (NHLBI, 4. Laboratory of Molecular Immunology); Keji Zhao (NHLBI, 4. Laboratory of Molecular Immunology); Rob DeSalle (American Museum of Natural History, Invertebrate Zoology); Michael Zhang (Cold Spring Harbor Laboratory, Biology); |
| Short Abstract: We have analyzed the histone modifications enriched in non-genic portions of the human genome including centromeres, telomeres and gene deserts using CHip-seq data |
| Long Abstract: Click Here |
| Poster K02 |
| Investigation of atomic level patterns in protein-ligand interactions |
| Ke Chen- University of Alberta |
| Lukasz Kurgan (University of Alberta, Electrical & Computer Engineering); |
| Short Abstract: We investigate the role of covalent and non-covalent bonds in protein-ligand interactions using 3,354 representative protein-ligand complexes where ligands include chemical compounds (excluding proteins/nucleotides). While non-covalent bonds cover majority of the interactions, the covalent bonds were also found important. Several strong, atomic-level patterns concerning formation of specific bonds were found. |
| Long Abstract: Click Here |
| Poster K03 |
| Interactive Visualization and Shape Analysis of the Hippocampus in a VR Environment |
| Soo-Mi Choi- Sejong University |
| Jeong-Sik Kim (Sejong University, Dept. of Computer Engineering); Hyun-Joong Kim (Sejong University, Dept. of Computer Engineering); |
| Short Abstract: This paper presents a method for shape analysis of the hippocampus in a VR environment combining an auto-stereoscopic display and a haptic device. To analyze the shape difference between two groups, we extract shape features from input images and perform statistical shape analysis using parametric representation and SVMs learning algorithm. |
| Long Abstract: Click Here |
| Poster K04 |
| InteroPORC: an automatic tool to predict highly conserved protein interaction networks |
| Magali Michaut- CEA |
| Samuel Kerrien (EMBL-EBI, PANDA); Luisa Montecchi-Palazzi (EMBL-EBI, PANDA); Corinne Cassier-Chauvat (CEA, iBiTec-S); Franck Chauvat (CEA, iBiTec-S); Jean-Christophe Aude (CEA, iBiTec-S); Pierre Legrain (CEA, iBiTec-S); Henning Hermjakob (EMBL-EBI, PANDA); |
| Short Abstract: We present here an automatic tool, InteroPorc, to predict protein-protein interactions, of use for all sequenced organisms. Based on the interolog concept, this tool combines source interactions with clusters of orthologous proteins (PORC). This open-source Java application can either be run online through a web interface or downloaded at http://biodev.extra.cea.fr/interoporc. |
| Long Abstract: Click Here |
| Poster K05 |
| A statistical analysis of protein-RNA interface prediction |
| Shreyartha Mukherjee- Iowa State University |
| No additional authors |
| Short Abstract: It is of biological significance to determine what types of protein or RNA readily bind to each other and what factors influence this binding. Knowledge gained through this study has many real life applications, which includes designing drug-inhibitors for viruses and down-regulation of unwanted gene activity in debilitating diseases. |
| Long Abstract: Click Here |
| Poster K06 |
| Electric moments of RNA-binding proteins |
| Akinori Sarai- Kyushu Institute of Technology |
| Shandar Ahmad (National Institute of Biomedical Innovation, Bioinformatics); |
| Short Abstract: We have made analyses of electric moments amongst RNA-binding proteins (RBPs). Dipole moments of rRNA- and mRNA-binding proteins and quadrupole moments of all RBPs are higher than other control proteins. These results will be used for detecting new RBPs from their structures and for understanding their action. |
| Long Abstract: Click Here |
| Poster K07 |
| An Integrated Protein-Protein Interaction System for Analysis of Cellular Proteome |
| Pan-Gyu Kim- Smallsoft Co. Ltd. |
| Hwajung Seo (SmallSoft Co., Ltd., Information Technology Institute); Kiejung Park (SmallSoft Co., Ltd., Information Technology Institute); |
| Short Abstract: We have developed an integrated system for protein-protein interactions which has three major features, to display protein-protein interaction diagrams by graphical mode, to show information for protein localization, and to provide the protein functions in a cell. It is organized by two major parts, the database and the application. |
| Long Abstract: Click Here |
| Poster K08 |
| Computational Identification and Analysis of Domain-Domain Interactions Using the In Vitro Virus Method |
| Rintaro Saito- Keio University |
| Yosuke Ozawa (Keio University, Graduate School of Media and Governance); Shigeo Fujimori (Keio University, Graduate School of Science and Technology); Motomu Matsui (Keio University, Graduate School of Media and Governance); Shota Ushiama (Keio University, Faculty of Environment and Information Studies); Hiroshi Yanagawa (Keio University, Graduate School of Science and Technology); Etsuko Miyamoto-Sato (Keio University, Graduate School of Science and Technology); Masaru Tomita (Keio University, Faculty of Environment and Information Studies); |
| Short Abstract: We developed a framework to predict novel domain-domain interactions by combining experimental and bioinformatics analyses. An in vitro display technology called in vitro virus which is capable of identifying protein fragments involved in protein bindings were used. We succeeded to predict 524 novel domain-domain interactions. |
| Long Abstract: Click Here |
| Poster K09 |
| In silico annotation of intermolecular interactions in Plasmodium falciparum |
| Claudia Harrison- University of Pretoria |
| Fourie Joubert (University of Pretoria, Bioinformatics); Ozlem Bishop (University of Pretoria, Bioinformatics); |
| Short Abstract: A web-based in silico system to annotate all malaria protein interactions is presented. The drug target potential of Plasmodium falciparum proteins are assessed based on ligand and protein-protein interactions, reaction types, functional importance and a comparison to the interactions of eight other species, including the human host and mosquito vector. |
| Long Abstract: Click Here |
| Poster K10 |
| Computational Prediction of Protein Domain-Peptide Interactions using Support Vector Machine |
| Shirley Hui- University of Toronto |
| Gary Bader (University of Toronto, Department of Molecular Genetics); |
| Short Abstract: We present a Support Vector Machine method to predict peptide-PDZ domain interactions from primary amino acid sequences. The predictor is built using thousands of experimentally determined positive and negative training examples and achieves a high level of accuracy when assessed through cross validation and blind test experiments. |
| Long Abstract: Click Here |
| Poster K11 |
| Inclusion of localised patterns in a large-scale agent-based model of the immune response to HIV infection |
| Dimitri Perrin- Dublin City University |
| Heather J. Ruskin (Dublin City University, School of Computing); Martin Crane (Dublin City University, School of Computing); |
| Short Abstract: To better understand linkage between known microscopic interactions at cell level and observed macroscopic progression of HIV infection, especially with regard to individual variations in latency period, an agent-based model is developed. Large-scale parallel implementation permits inclusion of localised, layered, effects, e.g. gastro-intestinal tract, detailed here. |
| Long Abstract: Click Here |
| Poster K12 |
| Assembling the interactome of human extracellular matrix to understand its role in health and disease |
| Graham Cromar- Hospital for Sick Children |
| John Parkinson (Hospital for Sick Children, Toronto, Molecular Structure and Function); |
| Short Abstract: The extracellular matrix (ECM) is a fibrous meshwork of proteins that self-assembles into a variety of biologically important structures. Understanding of network connectivity in this process is limited. We present a draft network of physical protein-protein interactions in human ECM to identify functionally important components relating to health and disease. |
| Long Abstract: Click Here |
| Poster K13 |
| An efficient coarse grained potential for unbound protein-protein docking |
| Venkata Ravikant Dintyala- Cornell University |
| Ron Elber (University of Texas Austin, Chemistry); |
| Short Abstract: We design an energy function to filter/rank candidate orientations generated by a docking algorithm. Data structures were designed to quickly compute residue contacts, vdw and change in surface area based features for each orientation. An optimal linear combination of these features was trained using linear programming. |
| Long Abstract: Click Here |
| Poster K14 |
| Global analysis of protein interaction networks in cancer-associated genes |
| Purnima Guda- University at Albany, State University of New York |
| Chittibabu Guda (University at Albany, State University of New York, GeNYSis Center for Excellence in Cancer Genomics); Sridar Chittur (University at Albany, State University of New York, Center for Functional Genomics); |
| Short Abstract: The goal of this work is to identify the pathways and functions that are common to various cancers, and also those that are specific to certain cancer type, using bioinformatics analyses. We used differentially expressed genes from microarray experiments of four different cancer types to carry out global analysis of protein-protein interactions. |
| Long Abstract: Click Here |
| Poster K15 |
| A Cytoscape Plugin to Access the MiMI Molecular Interactions |
| David States- University of Michigan |
| Jing Gao (University of Michigan, National Center for Integrative Biomedical Informatics); V. Glenn Tarcea (University of Michigan, National Center for Integrative Biomedical Informatics); Alex Ade (University of Michigan, National Center for Integrative Biomedical Informatics); Barbara Mirel (University of Michigan, National Center for Integrative Biomedical Informatics); James Cavalcoli (University of Michigan, National Center for Integrative Biomedical Informatics); Terry Weymouth (University of Michigan, National Center for Integrative Biomedical Informatics); H.V. Jagadish (University of Michigan, National Center for Integrative Biomedical Informatics); Brian Athey (University of Michigan, National Center for Integrative Biomedical Informatics); |
| Short Abstract: The Cytoscape plugin for MiMI retrieves molecular interactions from the National Center for Integrative Biomedical Informatics MiMI database and displays the interaction networks using Cytoscape. The plugin integrates nature language processing tools and a graph matching tool, and an interactive annotation editor. |
| Long Abstract: Click Here |
| Poster K16 |
| Domain-centric characterization and analysis of protein sequences. |
| Shreedhar Natarajan- University of Illinois, Urbana |
| Gloria Rendon (National Center for Supercomputing Applications, NCSA); Jeffrey Tilson (Renaissance Computing Institute, Renaissance Computing Institute); Mao-Feng Ger (UIUC, Center for Biophysics and Computational Biology); Eric Jakobsson (NCSA,UIUC, Center for Biophysics and Computational Biology); |
| Short Abstract: Protein domains largely define protein function and are clearly important evolutionary units. We describe our efforts in high throughput assignment of domain architectures to large numbers of proteins, searching for novel genes and drug targets, and inferring the domain-domain interactions that mediate protein-protein interactions. |
| Long Abstract: Click Here |
| Poster K17 |
| Predicting DNA-binding affinity of modularly designed zinc finger proteins |
| Peter Zaback- Iowa State University |
| Jeffry Sander (Iowa State University, Genetics, Development & Cell Biolgogy); J. Keith Joung (Harvard Medical School, Pathology); Daniel Voytas (University of Minnesota, Beckman Center for Transposon Research, Department of Genetics, Cell Biology, and Development); Drena Dobbs (Iowa State University, Genetics, Development & Cell Biology); |
| Short Abstract: Consisting of modular nucleic acid binding domains, C2H2 zinc finger proteins provide an excellent framework for engineering “customized” sequence-specific DNA binding proteins. We present new methods that accurately predict both in vivo and in vitro efficacies of zinc finger proteins engineered by modular design. |
| Long Abstract: Click Here |
| Poster K18 |
| RNAplex an fast interaction search t |
| Hakim Tafer- University of Vienna |
| Ivo Hofacker (University of Vienna, Institute for Theoretical Chemistry); |
| Short Abstract: We present a new version of RNAplex that allows to rapidly search for RNA interactions in large amount of genomic data, without neglecting the accessibility of potential target sites. This significantly improves performance compared to previous methods which neglects secondary structure. Nevertheless the runtime scales as O(NM) as in standard alignment programs. |
| Long Abstract: Click Here |
| Poster K19 |
| IntaRNA: Efficient Target Prediction Incorporating Accessibility of Target Sites |
| Anke Busch- Albert-Ludwigs-University Freiburg |
| Andreas S. Richter (Albert-Ludwigs-University Freiburg, Bioinformatics Group); Rolf Backofen (Albert-Ludwigs-University Freiburg, Bioinformatics Group); |
| Short Abstract: We present IntaRNA, a new approach to the prediction of RNA-RNA interactions, where a combined energy score of interaction is calculated as the sum of the hybridization energy and the energy required for making the interacting sites accessible. Additionally, the existence of a seed is enforced. |
| Long Abstract: Click Here |
| Poster K20 |
| Competition between protein aggreggation and protein complex formation |
| Sebastian Pechmann- University of Cambridge |
| Gian Gaetano Tartaglia (University of Cambridge, Department of Chemistry); Michele Vendruscolo (University of Cambridge, Department of Chemistry); Emmanuel Levy (MRC, Laboratory of Molecular Biology); |
| Short Abstract: We show that interface regions of protein complexes are more aggregation prone than other surface regions, and that aggregation propensity provides an effective way to identify protein complex interfaces. The competition between complex formation and protein aggregation is mediated by negative design principles that prevent interfaces from triggering uncontrolled aggregation. |
| Long Abstract: Click Here |
| Poster K21 |
| Alignment of Non-Covalent Interactions at Protein-Protein Interfaces |
| Hongbo Zhu- Max-Planck-Institut fĂĽr Informatik |
| Ingolf Sommer (Max-Planck-Institut fĂĽr Informatik, Computational Biology and Applied Algorithmics); Thomas Lengauer (Max-Planck-Institut fĂĽr Informatik, Computational Biology and Applied Algorithmics); Francisco Domingues (Max-Planck-Institut fĂĽr Informatik, Computational Biology and Applied Algorithmics); |
| Short Abstract: We present a method for aligning the vector representations of non-covalent interactions (van der Waals interactions and hydrogen bonds) between different protein-protein interfaces based on their geometry. It assists users in identifying local interface regions with similar patterns of non-covalent interactions, and investigating the molecular basis of interaction mimicry. |
| Long Abstract: Click Here |
| Poster K22 |
| Quasi-Identical Search in Protein Interaction Networks |
| Noppadon Khiripet- National Electronics And Computer Technology Center |
| No additional authors |
| Short Abstract: In postgenomic era, biological networks are increasingly important. The challenge is how to infer biological functions from them. A new method is proposed here and it consists of a search algorithm for quasi-identical subgraphs and a scoring function measuring mutual similarities between subgraphs using both topological features and functional relationships. |
| 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: |