Cristina Bianca Pop

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Ribosome profiling data report on the distribution of translating ribosomes, at steady-state, with codon-level resolution. We present a robust method to extract codon translation rates and protein synthesis rates from these data, and identify causal features associated with elongation and translation efficiency in physiological conditions in yeast. We show(More)
Accurate prediction of RNA pseudoknotted secondary structures from the base sequence is a challenging computational problem. Since prediction algorithms rely on thermodynamic energy models to identify low-energy structures, prediction accuracy relies in large part on the quality of free energy change parameters. In this work, we use our earlier constraint(More)
This paper presents a technique for semantic Web service composition inspired by the behavior of ants. The proposed technique combines a service composition graph model with the ant colony optimization met heuristic to select the optimal composition solution. In our approach, we have considered as selection criteria the QoS attributes of the services and(More)
In this paper we present a bee-inspired method for selecting the optimal composition solution. The proposed method uses a <i>composition graph model</i> and a <i>matrix of semantic links</i> to search for the optimal composition solution. For improving the performance of the traditional bee colony optimization algorithm a 1-OPT heuristic is defined. This(More)
This paper proposes a swarm-inspired data center consolidation methodology which aims at reducing the power consumption in data centers while ensuring the workload execution within the pre-established performance parameters. Each data center server is managed by an intelligent agent that deals with its power efficiency by implementing a bird's(More)