Alfonso Marquez-Chamorro

• Computer Science, Ph.D.
• Professor at University of Seville

La enseñanza de arquitectura del software supone todo un reto. Los conceptos teóricos son a menudo muy abstractos y los problemas arquitectónicos sólo son claramente visibles en aplicaciones de cierta envergadura. El reto es aún mayor cuando estos conceptos se enseñan en las primeras etapas del grado cuando los conocimientos de diseño y programació...

Predictive monitoring is a key activity in some Process-Aware Information Systems (PAIS) such as information systems for operational management support. Unforeseen circumstances like COVID can introduce changes in human behaviour, processes, or computing resources, which lead the owner of the process or information system to consider whether the qu...

Contribution: This article presents an experience report on the application of flipped classroom (FC) to the laboratory sessions (henceforth lab sessions) of an undergraduate computer science course. Background: Hands-on work in computer science lab sessions is typically preceded by technical instructions on how to install, configure, and use the s...

This paper reports our experience in flipping a second-year undergraduate course on software architecture and integration, taught in the second course of a Software Engineering degree. We compare the application of the flipped-classroom methodology with a traditional methodology. Our study encompasses two academic courses, in the years 2017 and 201...

It is well-known that context impacts running instances of a process. Thus, defining and using contextual information may help to improve the predictive monitoring of business processes, which is one of the main challenges in process mining. However, identifying this contextual information is not an easy task because it might change depending on th...

En este artículo describimos nuestra experiencia al aplicar la metodología de clase invertida en la asignatura Arquitectura e Integración de Sistemas Software, de segundo curso del grado de Ingeniería del Software. Varios aspectos caracterizan este estudio frente a los trabajos relacionados. En primer lugar, la metodología fue aplicada en las clase...

The evaluation of business process predictive monitoring models usually focuses on accuracy of predictions. While accuracy aggregates performance across a set of process cases, in many practical scenarios decision makers are interested in the reliability of an individual prediction, that is, an indication of how likely is a given prediction to be e...

Modern SLA management includes SLA prediction based on data collected during service operations. Besides overall accuracy of a prediction model, decision makers should be able to measure the reliability of individual predictions before taking important decisions, such as whether to renegotiate an SLA. Measures of reliability of individual predictio...

Predictive monitoring of business processes is a challenging topic of process mining which is concerned with the prediction of process indicators of running process instances. The main value of predictive monitoring is to provide information in order to take proactive and corrective actions to improve process performance and mitigate risks in real...

Nowadays, process mining is becoming a growing area of interest in business process management (BPM). Process mining consists in the extraction of information from the event logs of a business process. From this information, we can discover process models, monitor and improve our processes. One of the applications of process mining, is the predicti...

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be c...

The Regression Network plugin for Cytoscape (RegNetC) implements the RegNet algorithm for the inference of transcriptional association network from gene expression profiles. This algorithm is a model tree-based method to detect the relationship between each gene and the remaining genes simultaneously instead of analyzing individually each pair of g...

A variety of approaches for protein inter-residue contact prediction have been developed in recent years. However, this problem is far from being solved yet. In this article, we present an efficient nearest neighbor (NN) approach, called PKK-PCP, and an application for the protein inter-residue contact prediction. The great strength of using this a...

This work proposes an improvement of the multi-objective evolutionary method for the protein residue-residue contact prediction called MECoMaP. This method bases its prediction on physico- chemical properties of amino acids, structural features and evolutionary information of the proteins. The evolutionary algorithm produces a set of decision rules...

Protein structure prediction remains one of the most important challenges in molecular biology. Contact maps have been extensively used as a simplified representation of protein structures. In this work, we propose a multi-objective evolutionary approach for contact map prediction. The proposed method bases the prediction on a set of physico-chemic...

The problem of Protein Structure Prediction (PSP) is one of the principal topics in Bioinformatics. Multiple approaches have been developed in order to predict the protein structure of a protein. Determining the three dimensional structure of proteins is necessary to understand the functions of molecular protein level. An useful, and commonly used,...

Protein structure prediction is currently one of the main open challenges in Bioinformatics. The protein contact map is an useful, and commonly used, representation for protein 3D structure and represents binary proximities (contact or non-contact) between each pair of amino acids of a protein. In this work, we propose a multi-objective evolutionar...

The prediction of a protein's contact map has become in recent years, a crucial stepping stone for the prediction of the complete 3D structure of a protein. In this article, we describe a methodology for this problem that was shown to be successful in CASP8 and CASP9. The methodology is based on (i) the fusion of the prediction of a variety of stru...

We present a multi-objective evolutionary approach to predict protein contact maps. The algorithm provides a set of rules, inferring whether there is contact between a pair of residues or not. Such rules are based on a set of specific amino acid properties. These properties determine the particular features of each amino acid represented in the rul...

Protein structure prediction consists in determining the thre-e-dimensional conformation of a protein based only on its amino acid sequence. This is currently a difficult and significant challenge in structural bioinformatics because these structures are necessary for drug designing. This work proposes a method that reconstructs protein structures...

In this paper, we focus on protein contact map prediction, one of the most important intermediate steps of the protein folding problem. The objective of this research is to know how short-range interactions can contribute to a system based on decision trees to learn about the correlation among the covalent structures of a protein residues. We propo...

In this paper we propose an approach based on evolutionary computation for the prediction of secondary protein structure motifs. The prediction model consists of a set of rules that predict both the beginning and the end of the regions corresponding to a secondary structure state conformation (α-helix or β-strand). The prediction is based on a set...

The Protein Structure Prediction (PSP) problem consists of predicting the structure of a protein from its amino acids sequence, and have received much attention lately. In fact, being able to predict the structure of a protein, would allow to know the function of the protein. In this paper, we propose a multi-objective evolutionary algorithm for th...

Protein structure prediction is one of the main challenges in Bioinformatics. An useful representation for protein D structure is the protein contact map. In this work, we propose an evolutionary approach for contact map prediction based on amino acids physicochemical properties. The evolutionary algorithm produces a set of rules that identifies c...

In this study, we present a residue-residue contact prediction approach based on evolutionary computation. Some amino acid properties are employed according to their importance in the folding process: hydrophobicity, polarity, charge and residue size. Our evolutionary algorithm provides a set of rules which determine different cases where two amino...

Protein tertiary structure prediction consists of determining the three-dimensional conformation of a protein based solely on its amino acid sequence. This study proposes a method in which protein fragments are assembled according to their physicochemical similarities, using information extracted from known protein structures. Several existing prot...

In this paper, we focus on protein contact map prediction. We describe a method where contact maps are predicted using decision tree-based model. The algorithm includes the subsequence information between the couple of analyzed amino acids. In order to evaluate the method generalization capabilities, we carry out an experiment using 173 non-homolog...

We have developed an evolutionary computation approach to predict secondary structure motifs using some main amino acid physical-chemical properties. The prediction model will consist of rules that predict both the beginning and the end of the regions corresponding to a secondary structure state conformation (α-helix or β-strand). A study about pro...

In this study, a novel residue-residue contacts prediction approach based on evolutionary computation is presented. The prediction is based on four amino acids properties. In particular, we consider the hydrophobicity, the polarity, the charge and residues size. The prediction model consists of a set of rules that identifies contacts between amino...

The prediction of protein structures is a current issue of great significance in structural bioinformatics. More specifically, the prediction of the tertiary structure of a protein consists of determining its three-dimensional conformation based solely on its amino acid sequence. This study proposes a method in which protein fragments are assembled...

Multiple approaches have been developed in order to predict the protein secondary structure. In this paper, we propose an approach to such a problem based on evolutionary computation. The proposed approach considers various amino acids properties in order to predict the secondary structure of a protein. In particular, we will consider the hydrophob...