Tomás Arredondo

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OBJECTIVE The present study is concerned with the need that exists in bioinformatics to identify and delineate overlapping codon and noncodon structures in a deoxyribonucleic acid (DNA) complex so as to ascertain the boundary of separation between them. Codons refer to those parts in a DNA complex encoded towards forming a desired set of proteins. Also(More)
In this paper we describe a fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. Takagi-Sugeno-Kang (TSK) fuzzy logic is used to motivate a small mobile robot to acquire complex behaviors and to perform environment recognition. This method is implemented and tested in behavior based(More)
A vast amount of bioinformatics information is continuously being introduced to different databases around the world. Handling the various applications used to study this information present a major data management and analysis challenge to researchers. The present work investigates the problem of integrating heterogeneous applications and databases towards(More)
Fuzzy based models have been used in many areas of research. One issue with these models is that rule bases have the potential for indiscriminant growth. Inference systems with large number of rules can be overspecified, have model comprehension issues and suffer from bad performance. In this research we investigate the use of a genetic algorithm towards(More)
In general, a complex system consists of a large number of interacting units, which when viewed in an information-theoretic perspective, could be seen to possess gross redundant features. Further, a complex system is inherently stochastical in its extensive spatiotemporal universe and hence, some of its statistical features could manifest as patterns(More)
This paper describes a neural network based inference system developed as part of a bioinformatic application in order to help implement a systematic search scheme for the identification of genes which encode enzymes of metabolic pathways. The inference system uses BLAST sequence alignment values as inputs and generates a classification of the best(More)
In this paper we utilize information theory to study the impact in learning performance of various motivation and environmental configurations. This study is done within the context of an evolutionary fuzzy motivation based approach used for acquiring behaviors in mobile robot exploration of complex environments. Our robot makes use of a neural network to(More)
This paper describes the development of an inference system used for the identification of genes that encode enzymes of metabolic pathways. Input sequence alignment values are used to classify the best candidate genes for inclusion in a metabolic pathway map. The system workflow allows the user to provide feedback, which is stored in conjunction with(More)