A Novel Multi-objectivisation Approach for Optimising the Protein Inverse Folding Problem

in Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings (2015)

In biology, the subject of protein structure prediction is of continued interest, not only to chart the molecular map of the living cell, but also to design proteins of new functions. The Inverse Folding ... [more ▼]

In biology, the subject of protein structure prediction is of continued interest, not only to chart the molecular map of the living cell, but also to design proteins of new functions. The Inverse Folding Problem (IFP) is in itself an important research problem, but also at the heart of most rational protein design approaches. In brief, the IFP consists in finding sequences that will fold into a given structure, rather than determining the structure for a given sequence - as in conventional structure prediction. In this work we present a Multi Objective Genetic Algorithm (MOGA) using the diversity-as-objective (DAO) variant of multi-objectivisation, to optimise secondary structure similarity and sequence diversity at the same time, hence pushing the search farther into wide-spread areas of the sequence solution-space. To control the high diversity generated by the DAO approach, we add a novel Quantile Constraint (QC) mechanism to discard an adjustable worst quantile of the population. This DAO-QC approach can efficiently emphasise exploitation rather than exploration to a selectable degree achieving a trade-off producing both better and more diverse sequences than the standard Genetic Algorithm (GA). To validate the final results, a subset of the best sequences was selected for tertiary structure prediction. The super-positioning with the original protein structure demonstrated that meaningful sequences are generated underlining the potential of this work. [less ▲]

Exploiting the Hard-wired Vulnerabilities of Newscast via Connectivity-splitting Attack

in Proc. of the IEEE Intl. Conf. on Network and System Security (NSS 2014) (2014, October)

Newscast is a model for information dissemination and mem- bership management in large-scale, agent-based distributed systems. It deploys a simple, peer-to-peer data exchange protocol. The Newscast pro ... [more ▼]

Newscast is a model for information dissemination and mem- bership management in large-scale, agent-based distributed systems. It deploys a simple, peer-to-peer data exchange protocol. The Newscast pro- tocol forms an overlay network and keeps it connected by means of an epidemic algorithm, thus featuring a complex, spatially structured, and dynamically changing environment. It has recently become very popu- lar due to its inherent resilience to node volatility as it exhibits strong self-healing properties. In this paper, we analyze the robustness of the Newscast model when executed in a distributed environment subjected to malicious acts. More precisely, we evaluate the resilience of Newscast against cheating faults and demonstrate that even a few naive cheaters are able to defeat the protocol by breaking the network connectivity. Concrete experiments are performed using a framework that implements both the protocol and the cheating model considered in this work. [less ▲]

Evolutionary Multi-Objective Optimisation with Quantile Constraint for the Protein Structure Similarity Problem

Scientific Conference (2014)

Dynamic and Partially Connected Ring Topologies for Evolutionary Algorithms with Structured Populations

in The European Conference on the Applications of Evolutionary Computation (2014)

This paper investigates dynamic and partially connected ring topologies for cellular Evolutionary Algorithms (cEA). We hypothesize that these structures maintain population diversity at a higher level and ... [more ▼]

This paper investigates dynamic and partially connected ring topologies for cellular Evolutionary Algorithms (cEA). We hypothesize that these structures maintain population diversity at a higher level and reduce the risk of premature convergence to local optima on deceptive, multimodal and NP-hard fitness landscapes. A general framework for modelling partially connected topologies is proposed and three different schemes are tested. The results show that the structures improve the rate of convergence to global optima when compared to cEAs with standard topologies (ring, rectangular and square) on quasi-deceptive, deceptive and NP-hard problems. Optimal population size tests demonstrate that the proposed topologies require smaller populations when compared to traditional cEAs. [less ▲]

Cooperative Selection: Improving Tournament Selection via Altruism

in The 14th European Conference on Evolutionary Computation in Combinatorial Optimisation (2014)

This paper analyzes the dynamics of a new selection scheme based on altruistic cooperation between individuals. The scheme, which we refer to as cooperative selection, extends from tournament selection ... [more ▼]

This paper analyzes the dynamics of a new selection scheme based on altruistic cooperation between individuals. The scheme, which we refer to as cooperative selection, extends from tournament selection and imposes a stringent restriction on the mating chances of an individual during its lifespan: winning a tournament entails a depreciation of its fitness value. We show that altruism minimizes the loss of genetic diversity while increasing the selection frequency of the fittest individuals. An additional contribution of this paper is the formulation of a new combinatorial problem for maximizing the similarity of proteins based on their secondary structure. We conduct experiments on this problem in order to validate cooperative selection. The new selection scheme outperforms tournament selection for any setting of the parameters and is the best trade-off, maximizing genetic diversity and minimizing computational efforts. [less ▲]

Validating a Peer-to-Peer Evolutionary Algorithm

in European Conference on the Applications of Evolutionary Computation (2012)

Pool vs. island based evolutionary algorithms: an initial exploration

in 2012 Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (2012)

This paper explores the scalability and performance of pool and island based evolutionary algorithms, both of them using as a mean of interaction an object store; we call this family of algorithms SofEA ... [more ▼]

This paper explores the scalability and performance of pool and island based evolutionary algorithms, both of them using as a mean of interaction an object store; we call this family of algorithms SofEA. This object store allows the different clients to interact asynchronously; the point of the creation of this framework is to build a system for spontaneous and voluntary distributed evolutionary computation. The fact that each client is autonomous leads to a complex behavior that will be examined in the work, so that the design can be validated, rules of thumb can be extracted, and the limits of scalability can be found. In this paper we advance the design of an asynchronous, fault-tolerant and scalable distributed evolutionary algorithm based on the object store CouchDB. We test experimentally the different options and show the trade-offs that pool and island-based solutions offer. [less ▲]