Evidence After Imputation for a Role of MICA Variants in Nonprogression and Elite Control of HIV Type 1 Infection

Past genome-wide association studies (GWAS) involving individuals with AIDS have mainly identified associations in the HLA region. Using the latest software, we imputed 7 million single-nucleotide polymorphisms (SNPs)/indels of the 1000 Genomes Project from the GWAS-determined genotypes of individuals in the Genomics of Resistance to Immunodeficiency Virus AIDS nonprogression cohort and compared them with those of control cohorts. The strongest signals were in MICA, the gene encoding major histocompatibility class I polypeptide-related sequence A (P = 3.31 × 10−12), with a particular exonic deletion (P = 1.59 × 10−8) in full linkage disequilibrium with the reference HCP5 rs2395029 SNP. Haplotype analysis also revealed an additive effect between HLA-C, HLA-B, and MICA variants. These data suggest a role for MICA in progression and elite control of human immunodeficiency virus type 1 infectio

A complete collection of single-gene deletion mutants of Acinetobacter baylyi ADP1

We have constructed a collection of single-gene deletion mutants for all dispensable genes of the soil bacterium Acinetobacter baylyi ADP1. A total of 2594 deletion mutants were obtained, whereas 499 (16%) were not, and are therefore candidate essential genes for life on minimal medium. This essentiality data set is 88% consistent with the Escherichia coli data set inferred from the Keio mutant collection profiled for growth on minimal medium, while 80% of the orthologous genes described as essential in Pseudomonas aeruginosa are also essential in ADP1. Several strategies were undertaken to investigate ADP1 metabolism by (1) searching for discrepancies between our essentiality data and current metabolic knowledge, (2) comparing this essentiality data set to those from other organisms, (3) systematic phenotyping of the mutant collection on a variety of carbon sources (quinate, 2-3 butanediol, glucose, etc.). This collection provides a new resource for the study of gene function by forward and reverse genetic approaches and constitutes a robust experimental data source for systems biology approaches

Cc And Task-Intervals

A concurrent scheme for jobshop scheduling problem solving based on the task-interval idea is developed within the (potentially distributed) cc framework. A "total" model where agents are associated with each (t,T)( task/subset of tasks) pair is first investigated. Agents are parameterized by the type and strength of the redundant constraints that they propagate. Confluence and correctness are proved for two "pure" types of constraints, as well as their weakenings and combinations: maximum precedence constraint associated with each (t,T) pair and a strong constraint on time bounds. Refinements of the basic model are then investigated. "Local" simplification mechanism are introduced to dynamically eliminate useless or redundant agents, without need for central control. Finally, central control strategies issues are adressed. Completeness of a control strategy corresponding to the task-interval algorithm and some of its relaxations is proved. Chapter 1 Introduction Constraint Logic Pro..

Modeling of biological networks

International audienc

Modeling and Querying Biomolecular Interaction Networks

We introduce a formalism to represent and analyze protein-protein and protein-DNA interaction networks. We illustrate the expressivity of this language, by proposing a formal counterpart of Kohn's compilation on the mammalian cell cycle control. This e#ectively turns an otherwise static knowledge into a discrete transition system incorporating a qualitative description of the dynamics. We then propose to use the Computation Tree Logic CTL as a query language for querying the possible behaviours of the system. We provide examples of biologically relevant queries expressed in CTL about the mammalian cell cycle control and show the e#ectiveness of symbolic model checking tools to evaluate CTL queries in this context

CycSim - an online genome-scale metabolic model simulator and browser, integrated with pathways databases

International audienceCycSim is a web-based application dedicated to analyses with genome-scale metabolic models coupled to the exploration of knowledge from BioCyc and KEGG. Specifically, CycSim supports the design of knockout experiments: simulation of growth phenotypes of single or multiple gene deletions mutants on specified media, comparison of these predictions with experimental phenotypes, and direct visualization of both on metabolic maps. The web interface is designed for simplicity, putting constraint-based modeling techniques within easier reach of biologists. CycSim also functions as an online repository of constraint-based models devoted to metabolic networks and can be used to produce training data for metabolic network inference methods