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Biomedical subjects

Guillaume Beslon

Publications and source records attributed to Guillaume Beslon.

5 recordsLinked to original sources

Evolutionary coupling between the deleteriousness of gene mutations and the amount of non-coding sequences.

The phenotypic effects of random mutations depend on both the architecture of the genome and the gene-trait relationships. Both levels thus play a key role in the mutational variability of the phenotype, and hence in the long-term evolutionary success of the lineage. Here, by simulating the evolution of organisms with flexible genomes, we show that the need for an appropriate phenotypic variability induces a relationship between the deleteriousness of gene mutations and the quantity of non-coding sequences maintained in the genome. The more deleterious the gene mutations, the shorter the intergenic sequences. Indeed, in a shorter genome, fewer genes are affected by rearrangements (duplications, deletions, inversions, translocations) at each replication, which compensates for the higher impact of each gene mutation. This spontaneous adjustment of genome structure allows the organisms to retain the same average fitness loss per replication, despite the higher impact of single gene mutations. These results show how evolution can generate unexpected couplings between distinct organization levels.

Animals↗

Guidelines: From artificial evolution to computational evolution: a research agenda.

Computational scientists have developed algorithms inspired by natural evolution for at least 50 years. These algorithms solve optimization and design problems by building solutions that are 'more fit' relative to desired properties. However, the basic assumptions of this approach are outdated. We propose a research programme to develop a new field: computational evolution. This approach will produce algorithms that are based on current understanding of molecular and evolutionary biology and could solve previously unimaginable or intractable computational and biological problems.

Algorithms↗

Spontaneous dynamics of asymmetric random recurrent spiking neural networks.

In this letter, we study the effect of a unique initial stimulation on random recurrent networks of leaky integrate-and-fire neurons. Indeed, given a stochastic connectivity, this so-called spontaneous mode exhibits various nontrivial dynamics. This study is based on a mathematical formalism that allows us to examine the variability of the afterward dynamics according to the parameters of the weight distribution. Under the independence hypothesis (e.g., in the case of very large networks), we are able to compute the average number of neurons that fire at a given time-the spiking activity. In accordance with numerical simulations, we prove that this spiking activity reaches a steady state. We characterize this steady state and explore the transients.

Action Potentials↗

Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software.

BACKGROUND: There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal. RESULTS: We have created 3DSpi, a multi-agent based software that we used to explore the generation of multi-protein dynamic structures. Being based on a very restricted set of parameters, it is perfectly suited for exploring the minimal set of rules needed to generate large multi-protein structures. It can therefore be used to test the hypothesis that such structures are formed and maintained by principles of self-organization. We observed that multi-protein structures emerge and that the system behavior is very robust, in terms of the number and size of the structures generated. Furthermore, the generated structures very closely mimic spatial organization of real life multi-protein structures. CONCLUSION: The behavior of 3DSpi confirms the considerable potential of MAS for modeling subcellular structures. It demonstrates that robust multi-protein structures can emerge using a restricted set of parameters and allows the exploration of the dynamics of such structures. A number of easy-to-implement modifications should make 3DSpi the virtual simulator of choice for scientists wishing to explore how topology interacts with time, to regulate the function of interacting proteins in living cells.

Cellular Structures↗

ROSO: optimizing oligonucleotide probes for microarrays.

UNLABELLED: ROSO is software to design optimal oligonucleotide probe sets for microarrays. Selected probes show no significant cross-hybridization, no stable secondary structures and their Tm are chosen to minimize the Tm variability of the probe set. AVAILABILITY: The program is available on the internet. Sources are freely available, for non-profit use, on request to the authors. SUPPLEMENTARY INFORMATION: http://pbil.univ-lyon1.fr/roso

Algorithms↗