Institution / Department:
Awadalla Lab
CHU Ste-Justine / Université de Montréal

Description:
The Awadalla Lab at the CHU Ste-Justine centre de recherche and Université de Montréal is looking for a full time bioinformatician. The work will concern processing genotype and next-generation sequencing data for SNP detection, genomics, and transcriptomics for studies in the genetics of cancer, malaria, immunodeficiency and metabolic health. The appropriate candidate will have strong programming skills and a basic knowledge of genomics. A bachelors or a masters degree in bioinformatics or closely related field is required.
Please send a CV, coverletter, and the names and emails of three references at the contact email below

Application deadline :
Applications will be reviewed immediately and continue until the job is filled

Contact :
philip.awadalla(at)umontreal.ca
Awadalla Lab

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Synopsis :
Ribonucleic acids (RNAs) have emerged as one of the most important biomolecules, playing key roles in various aspects of the gene transcription and regulation processes. To achieve their functions, RNAs use sophisticated structures which are determined by their sequences. The development of sound theoretical models is required to analyze and predict these structures. The talks of this seminar series aim to provide a fresh and comprehensive overview of the most recent and innovative frameworks developed in this field.

Date / Time / Location:
Date : September 1, 2010
Time : 2 :30 – 6 :00 pm
Place : Room 1100 and 3120, Trottier Building, 3680 University street.
Contact : Jérôme Waldispühl (jeromew@cs.mcgill.ca)
Official Web Site

Audience :
This symposium is intended for mathematics, physics and computer science researchers, grad students and senior undergrads interested in the developement and application of mathematical and computational methods to structural biology. Biologists and biochemists interested in the most recent theoretical frameworks developed for RNA structures are also encouraged to attend. The biological background necessary for the understanding of the talks will be provided during the seminars.

Program

• Alain Denise, LRI, University of Paris Sud 11, Orsay, France.
  ”Counting RNA pseudoknotted structures”
• Francois Major, IRIC & DIRO, University of Montreal, Montreal, Canada.
  ”Changes in topological isomeric space correlate with microRNA maturation efficiency”
• Henri Orland, ITP, CEA, Saclay, France.
  ”A topological classification of RNA folds”
• Yann Ponty, LIX, Ecole Polytechnique, Palaiseau, France.
  ”Extending the hypergraphs analogy for RNA dynamic programming”

The MonBUG development team would like to thank everyone (speakers and attendees) who participated to it’s second season’s activities.

We are already hard at work preparing our next season which will launch with another Distinguished Speaker event featuring Scripps’ Samuel Levy.

As such, feel free to suggest speakers you feel would give interesting and insightful talks.

So stay tuned and see you in september !

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Talk Title :
Meat and Potatoes: Two Genomic Tales from Agriculture

Date / Time / Location:
Thursday, May 6^th 2010 – 4:00 PM
McGill University
Room 232, Leacock Building.

Affiliation :
Broad Institute

URL
Mike Zody

Abstract :
Domestication of plants and animals marked a major turning point in human development, allowing sedentary societies to achieve tremendous growth through the maintenance of reliable sources of food. Growth of agricultural societies was accompanied by human-directed growth and evolution of domesticated species and, along with them, the pathogens that infected these species. I will present results from analysis of two very different genomic models: Phytophthora infestans, an oomycete plant pathogen that causes late blight of potatoes and tomatoes, and the domestic chicken, the largest source of animal protein for human consumption.

P. infestans was discovered in the 19th century and shown to be the cause of late blight, the disease responsible for the Great Irish Famine and other widespread potato crop failures throughout Europe. The pathogen spreads rapidly and is highly destructive on susceptible plant strains. Despite over a century of efforts at control through breeding resistant plants, late blight remains a major threat to world’s food supply, destroying over $6 billion of potatoes every year. Widespread outbreaks have occurred in both America and Europe in the past two years. Our analysis of the genome of P. infestans suggests that its ability to overcome control efforts may result from a highly dynamic genome that is undergoing rapid gene turnover, allowing it to diversify easily in the face of new selective pressures.

The chicken, Gallus gallus, was domesticated around 8,000 years ago in south Asia and has spread worldwide. Extensive selection by humans has led to domestic birds that show a wide range of color, growth, and reproductive variation compared to their wild ancestors, the red junglefowl. We have used SOLiD technology to resequence pools of birds selected from multiple domestic lines maintained for different production purposes and from red junglefowl populations. These data reveal multiple loci that appear to have been under strong selection during development of the domestic chicken, including one potential early domestication gene with a role in reproductive control. We also identified a number of sites of gene deletion that are fixed in one or more domestic chicken breeds, two of which have striking growth phenotypes.

These two diverse studies, drawing on the selective pressures at work in the farm environment, illustrate basic principles of how organisms evolve at a molecular level and adapt to both natural and human selective pressures. They further provide some guidance for agricultural improvements. Our P. infestans results suggest new methods for monitoring and may lead to better deployment of resistant strains. Our chicken findings identify multiple sites likely to have been selected for important production traits, providing targets for future breeding improvement as well as advancing our understanding of the chicken as a model organism.

Talk Title :
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Searching for Signaling Balance through the Identification of Genetic Interactors of the Rab Guanine-nucleotide Dissociation Inhibitor gdi-1

Date / Time / Location:
Thursday April 8^th, 2010 – 6:00 pm
Room S1-151 at IRIC

Affiliation :
UQAM

Personal Page
Sarah Jenna

Abstract :
Background
The symptoms of numerous diseases result from genetic mutations that disrupt the homeostasis maintained by the appropriate integration of signaling gene activities. The relationships between signaling genes suggest avenues through which homeostasis can be restored and disease symptoms subsequently reduced. Specifically, disease symptoms caused by loss-of-function mutations in a particular gene may be reduced by concomitant perturbations in genes with antagonistic activities.

Methodology/Principle Findings
Here we use network-neighborhood analyses to predict genetic interactions in Caenorhabditis elegans towards mapping antagonisms and synergisms between genes in an animal model. Most of the predicted interactions are novel, and the experimental validation establishes that our approach provides a gain in accuracy compared to previous efforts. In particular, we identified genetic interactors of gdi-1, the orthologue of GDI1, a gene associated with mental retardation in human. Interestingly, some gdi-1 interactors have human orthologues with known neurological functions, and upon validation of the interactions in mammalian systems, these orthologues would be potential therapeutic targets for GDI1-associated neurological disorders. We also observed the conservation of a gdi-1 interaction between different cellular systems in C. elegans, suggesting the involvement of GDI1 in human muscle degeneration.

Conclusions/Significance
We developed a novel predictor of genetic interactions that may have the ability to significantly streamline the identification of therapeutic targets for monogenic disorders involving genes conserved between human and C. elegans.

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Talk Title :
Deriving Executable Models of Biochemical Network Dynamics from
Qualitative and Semi-Quantitative Data.

Date / Time / Location:
Thursday March 11^th, 2010 – 6:00 pm
Room S1-151 at IRIC

Affiliation :
McGill’s MCB

Personal Page
Ruths Research

Abstract :
Progress in advancing our understanding of biological systems is limited by their sheer complexity, the cost of laboratory materials and equipment, and limitations of current laboratory technology. Computational and mathematical modeling provides ways to address these limitations through hypothesis generation and testing without experimentation – allowing researchers to analyze system structure and dynamics in silico and, then, design lab experiments that yield desired information about phenomena of interest.
These models, however, are only as accurate and complete as the data used to build them. Currently most models are constructed from quantitative experimental data. However, since accurate quantitative measurements are hard to obtain and difficult to adapt from literature and online databases, new sources of data for building models need to be explored. In my research, I design methods for building and executing computational models of cellular networks based on qualitative experimental data, which is more abundant, easier to obtain, and reliably reproducible. Such executable models allow for in silico perturbation, simulation, and exploration of biological systems.
In this talk, I will present two general strategies for building and executing Petri net-based models of biochemical networks. Both have been successfully used to model and predict the dynamics of signaling networks in normal and cancer cell lines, rivaling the accuracy of existing methods trained on quantitative data.

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Talk Title :
Short RNAs and Organism-specific Aspects of Process Regulation

Date / Time / Location:
Thursday February 11^th, 2010 – 6:00 pm
Room S1-151 at IRIC

Affiliation :
IBM Research

Personal Page
Isidore Rigoutsos

Abstract :
In this talk, I will discuss the possibility that a potentially significant portion of cellular process regulation may be mediated by genomic sequences that need not be conserved across organisms. Evidence in support of this viewpoint comes from computational analyses as well as experimental work by us and by others. The ramifications of such findings for the onset and progression of disease will also be examined.

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Talk Title :
Blood‐based transcriptomics in breast cancer epidemiology

Date / Time / Location:
Thursday January 14^th, 2010 – 6:00 pm
Room S1-151 at IRIC

Affiliation :
University of Tromsø

URL
Vanessa Dumeaux

Abstract :
Given the number of factors that influence expression regulation, it is not surprising that often more than one strong signal is present in any given high-dimensional dataset. Peripheral blood is an ideal surrogate tissue as it has the potential to reflect responses to changes in the immediate and distant environments by alterations of gene expression levels. Thus, there is growing evidence that use of peripheral blood cells for transcriptome analysis is valuable to assess environmental- or disease- associated gene signatures.
During this talk, I will focus on altered gene expression in blood by inter-individual or lifestyle factors, breast cancer diagnosis and late-side effects related to breast cancer treatment (e.g. chronic fatigue). Significant results are obtained by examining the biological implications grouped into gene sets, rather than specific single genes tested for differential expression. Perturbed pathways were more or less numerous and distinct across variables with also some similarities emerging, perhaps unsurprisingly, in terms of immune response. Refined analysis identifying key genes specific to blood cell subtypes can also provide exciting functional information.
It is within the prospective cohort design that the most successful examples of biomarkers and disease outcome are found – this will be where the novel design of the Norwegian Women and Cancer (NOWAC) postgenome study can prove valuable.

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Talk Title :
How perfect can protein interactomes be?

Date / Time / Location:
Thursday, November 12^th 2009 – 6:00 pm
McGill University
Room 232, Leacock Building
855 Sherbrooke Street West

Affiliation :
Université Laval

URL
Christian Landry

Abstract :
Evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with “junk” DNA and spurious DNA binding sites. Here, I question whether such a notion should be applied to protein interactomes- that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions. I discuss evidence for the existence of these non-functional interactions in kinase-substrate networks from the analysis of the evolution of phosphoproteomes of mammals and fungi.

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Talk Title :
Reconstructing gene networks by epistatic analysis of phenotype and expression data

Date / Time / Location:
Thursday October 8^th, 2009 – 6:00 pm
McGill University
Room 232, Leacock Building
855 Sherbrooke Street West

Affiliation :
Ottawa Institute of Systems Biology

URL
Mads Kaern

Abstract :
One the most successful methods to map genetic networks and pathways predates modern genomics by nearly a century. This method, epistatic analysis, traditionally involves observing the phenotypic impact of mutating two different genes individually and in combination. This talk will introduce the basic concepts involved and discuss recent advances emphasizing the inference of transcriptional regulatory networks. In one study, we investigated if conventional epistatic analysis might be used to highlight interactions within the network regulating the transcriptional response of yeast to DNA damage, and developed a method to specifically identify dynamically modulated functional relationships. Somewhat surprisingly, the network derived from phenotypic data has only a modest overlap with that inferred from microarray data. In a second study, we directly compared epistatic analysis based on phenotypic data and marker gene expression. This analysis demonstrates that the two approaches provide complementary information. While conventional analysis correctly infers the order of genes in metabolic pathways, expression-based analysis specifically highlight regulatory hierarchies. Moreover, combining the two methods allows for a nearly complete network reconstruction with a negligible false discovery rate.