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Systems Biology & Networks

Systems Biology & Networks
The QTL-Shielding Test (QST): a Novel Technique for Genetic Network Discovery in a Microarray/Marker Dataset
Christine Duarte, Zhao-Bang Zeng
Nature Source Genetics, United States

We present a technique for inferring genetic relationships from the analysis of an e-QTL or Expression-Quantitative Trait Loci dataset in which marker and microarray data are collected in an experimental cross. The QST has been applied to yeast and eucalyptus datasets to find key regulators involved in a number of important pathways.

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Systems Biology & Networks
Automatic design of functional genetic networks
Javier Carrera, Guillermo Rodrigo, Alfonso Jaramillo
Departamento Matematica Aplicada, Universidad Politecnica Valencia, Spain

The use of forward-engineering techniques allows generating new protein networks with targeted behaviours. Using an automated evolutionary design procedure, we explore the space of all possible transcriptional regulation networks to find the optimal circuit with specified behaviour (e.g. Boolean logic functions or oscillators) and to study the evolution of genetic networks

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Systems Biology & Networks
MetabolomeExplorer: Inferring Metabolic Networks From High Resolution Mass Spectrometry Data
Richard Scheltema, Frans Stellaard, Ritsert Jansen, Michael Barrett
University of Groningen, Netherlands

The new generation mass spectrometers, separating complex mixtures at high resolution and mass accuracy, gave metabolomics a powerful tool. To harness the overwhelming information abundance generated, novel bioinformatics solutions are needed. As a showcase the MetabolomeExplorer was developed, implementing new concepts for normalizing and analyzing ultra-high resolution mass spectrometry data.

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Systems Biology & Networks
PRISM: A Web Server for Prediction and Visualization of Protein-Protein Interactions
Nurcan Tuncbag, Emre Guney, Mehmet Cengiz Ulubas, Ozlem Keskin, Attila Gursoy
Koc University, Turkey

PRISM is a web server for the querying, visualization and analysis of the protein interfaces and putative protein-protein interactions derived from known PDB structures. Interactions are predicted by considering shape complementarities and evolutionary conservation of protein interfaces. PRISM, with its graphical features, is a valuable resource for analyzing protein-protein interactions.

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Systems Biology & Networks
Finding genes involved in plants response to drought
Maital Ashkenazi, Menachem Moshelion
The Hebrew University of Jerusalem, Israel

We create networks of genes with correlated expression patterns in response to various water deficit situations. By intersecting these networks we can locate cliques enriched with water stress specific genes. We try to suggest a role in plants response to drought for the unknown genes in these cliques.

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Systems Biology & Networks
Logical Modelling and Analysis of the Budding Yeast Cell cycle
Adrien Fauré,Claudine Chaouiya, Andrea Ciliberto, Denis Thieffry
INSERM , France

Leaning on a logical framework, we are developing a modular modelling approach of the budding Yeast cell cycle, building upon a model of the core cell cycle engine and progressively aggregating specific regulatory modules. The present communication focuses on the integration of the morphogenesis control checkpoint.

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Systems Biology & Networks
Non-Genetic Individuality in the Host-Phage Interaction
Sivan Pearl, Chana Gabay, Nathalie Balaban, Amos Oppenheim
Hebrew University, Israel

Persistent bacteria are protected from stresses such as antibiotics, due to non-genetic heterogeneity of growth rates. As phages represent a common stress bacteria encounter, we studied the effect of persistence on the interaction between E.coli and phage lambda. We observed non-genetic individuality in bacterial response to phages, which might alter population dynamics.

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Systems Biology & Networks
Analysis of gene expression data on metabolic networks
Anna-Lena Kranz, Thorsten Bonato, Marcus Oswald, Hanna Seitz, Gerhard Reinelt, Heiko Runz, Johannes Zschocke, Roland Eils, Rainer Koenig
University of Heidelberg/Institute for Pharmacy and Molecular Biotechnology, Germany

When analysing microarray expression data, it is often not enough to examine single genes but rather groups of genes. We invented a novel method that determines significant expression patterns of topologically associated genes and thereby identifies functionally relevant central components in the network with respect to different conditions of interest.

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Systems Biology & Networks
Mining expression-dependent modules in the human interaction network
Elisabeth Georgii, Sabine Dietmann, Koji Tsuda
MPI for Biological Cybernetics, Friedrich Miescher Laboratory of the Max Planck Society, Germany

We present a novel approach for detecting functional modules by integrating static information from protein interaction networks with gene expression data. Our method discovers sets of interacting proteins that occur specifically in subsets of cellular conditions. The enumerative algorithm based on itemset mining allows to integrate several heterogeneous data sets.

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Systems Biology & Networks
Gene- and pathway-centric approaches to the measurement of similarities between different cell states
Martina Koeva
University of California, Santa Cruz, United States

We are interested in the comparison between different stem cell populations, as well as tissues, based on gene expression data. I have developed several measures for the assessment of similarities between cell states, using both a gene- and pathway-centric approaches and have applied them to several publicly available datasets.

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Systems Biology & Networks
RegAlign: An Algorithm for the Alignment of Gene Regulatory Networks
George Davidescu
University of New Brunswick, Canada

RegAlign is a new tool which produces a global alignment of two given regulatory networks while taking into account the similarity of both the networks’ nodes and their structures. The project also aims to propose a standardized system of representing regulatory network data.

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