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48 results on '"Díaz, Fernando"'

1. Contributors

Author

Amodio, Piero, primary, Amor, Michael, additional, Bo, Qikang, additional, Borges, Francisco, additional, Bower, John R., additional, Caamal-Monsreal, Claudia, additional, Caldwell, Roy L., additional, Carrasco, Sergio A., additional, Castellanos-Martínez, Sheila, additional, Che, Leo J., additional, Cisneros, Rosario, additional, Court, Melanie, additional, Dantas, Renato J.S., additional, Di Cosmo, Anna, additional, Díaz, Fernando, additional, Díaz-Santana-Iturrios, Mariana, additional, Farías, Ana, additional, Fiorito, Graziano, additional, Galindo-Sánchez, Clara E., additional, Gallardo, Pedro, additional, Gestal, Camino, additional, Gleadall, Ian G., additional, González, Ángel F., additional, González-Gómez, Roberto, additional, Guerra, Ángel, additional, Haimovici, Manuel, additional, Hall, Karina C., additional, Hanlon, Roger T., additional, Hofmeister, Jennifer K.K., additional, Hutchinson, Neil, additional, Ibáñez, Christian M., additional, Ikeda, Yuzuru, additional, Imperadore, Pamela, additional, Ivaylova, Silvina, additional, Juárez, Oscar E., additional, Kommritz, Juergen G., additional, Kuba, Michael, additional, Lajbner, Zdenek, additional, Leite, Tatiana S., additional, Lima, Françoise D., additional, Lishchenko, Fedor, additional, Lopes, Vanessa M., additional, López-Galindo, Laura L., additional, López-Rocha, Jorge, additional, Lourenço, Silvia, additional, Markaida, Unai, additional, Matos, Fábio L., additional, Moltschaniwskyj, Natalie A., additional, Monteiro, Silvia S., additional, Morillo-Velarde, Piedad S., additional, Nabhitabhata, Jaruwat, additional, Narvarte, Maite Andrea, additional, Noro, Kyosei, additional, Ortiz, Nicolas, additional, Otjacques, Eve, additional, Pardo-Gandarillas, María Cecilia, additional, Pascual, Cristina, additional, Pereira, João, additional, Petchkamnerd, Jinda, additional, Pierce, Graham J., additional, Pissarra, Vasco, additional, Pizzulli, Federica, additional, Polese, Gianluca, additional, Ponte, Giovanna, additional, Raffini, Francesca, additional, Re, Denisse, additional, Ren, Jing, additional, Rosa, Rui, additional, Rosas, Carlos, additional, Roumbedakis, Katina, additional, Roura, Álvaro, additional, Sakurai, Yasunori, additional, Sampaio, Eduardo, additional, Santos, Catarina P., additional, Scheel, David, additional, Segawa, Susumu, additional, Shau Hwai, Aileen Tan, additional, Simakov, Oleg, additional, Sobrino, Ignacio, additional, Storero, Lorena Pia, additional, Tang, Yan, additional, Tongtherm, Kittichai, additional, Tuanapaya, Surangkana, additional, Uriarte, Iker, additional, Ventura-López, Claudia, additional, Villanueva, Roger, additional, Voight, Janet R., additional, Voss, Kelley M., additional, Wang, Jinhai, additional, Williams, Becky L., additional, Xing, De, additional, Yamrungrueng, Anyanee, additional, and Zheng, Xiaodong, additional

Published
2024
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3. Genes Involved in Pharmacoresistant Epilepsy

Author

Martínez-Juárez, Iris E., primary, Barrios-González, Diego A., additional, Prado, Aurelio Jara, additional, Sotelo-Díaz, Fernando, additional, Calderón Martínez, Juan A., additional, Mejía del Castillo, Georgina J., additional, Morales Chinga, Patricia J., additional, Ochoa, Adriana, additional, and Delgado-Escueta, Antonio V., additional

Published
2023
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11. Los bosques de Extremadura : evolución, ecología y conservación

Author

Abel Schaad, Daniel, Ezquerra Boticario, Francisco J., González Bornay, Guillermo, Hernández Carretero, Ana María, Moreno Marcos, Gerardo, Pérez González, Juan José, Pulido Díaz, Fernando Javier, Sanz Redondo, Rubén, Vázquez Pardo, Francisco María, Biblioteca Digital del Real Jardin Botanico de Madrid, Abel Schaad, Daniel, Ezquerra Boticario, Francisco J., González Bornay, Guillermo, Hernández Carretero, Ana María, Moreno Marcos, Gerardo, Pérez González, Juan José, Pulido Díaz, Fernando Javier, Sanz Redondo, Rubén, and Vázquez Pardo, Francisco María

Subjects
Angiospermas, Conservación, Península Ibérica, Vegetación
Published
2007

13. Chapter 7 - Octopus maya, the Mayan octopus

Author

Rosas, Carlos, Markaida, Unai, López-Rocha, Jorge, Díaz, Fernando, Re, Denisse, Caamal-Monsreal, Claudia, Gallardo, Pedro, Pascual, Cristina, Galindo-Sánchez, Clara E., Juárez, Oscar E., López-Galindo, Laura L., and Ventura-López, Claudia

Published
2024
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41. Fuzzy Patterns and GCS Networks to Clustering Gene Expression Data.

Author

Glez-Peña, Daniel, Díaz, Fernando, Fdez-Riverola, Florentino, Méndez, José R., and Corchado, Juan M.

Abstract

The advent of DNA microarray technology has supplied a large volume of data to many fields like machine learning and data mining. Gene expression profiles are composed of thousands of genes at the same time, representing complex relationships between them. In this context, intelligent support is essential for managing and interpreting this great amount of information. One of the well-known constraints specifically related to microarray data is the large number of genes in comparison with the small number of available experiments. In this situation, the ability of design methods capable of overcoming current limitations of state-of-the-art algorithms is crucial to the development of successful applications. In this chapter we present a flexible framework for the task of feature selection and classification of microarray data. Dimensionality reduction is achieved by the application of a supervised fuzzy pattern algorithm able to reduce and discretize existing gene expression profiles. An informed growing cell structures network is proposed for clustering biological homogeneous experiments starting from the previous simplified microarray data. Experimental results over different data sets containing acute myeloid leukemia profiles show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Published
2009
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42. An Evolutionary Approach for Sample-Based Clustering on Microarray Data.

Author

Glez-Peña, Daniel, Díaz, Fernando, Méndez, José R., Corchado, Juan M., and Fdez-Riverola, Florentino

Abstract

Sample-based clustering is one of the most common methods for discovering disease subtypes as well as unknown taxonomies. By revealing hidden structures in microarray data, cluster analysis can potentially lead to more tailored therapies for patients as well as better diagnostic procedures. In this work, we present a novel method for automatically discovering clusters of samples which are coherent from a genetic point of view. Each possible cluster is characterized by a fuzzy pattern which maintains a fuzzy discretization of relevant gene expression values. Noise genes are identified and removed from the fuzzy pattern based on their probability of appearance. Possible clusters are randomly constructed and iteratively refined by following a probabilistic search and an optimization schema. Experimental results over publicly available microarray data show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Published
2009
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43. Assessing Classification Accuracy in the Revision Stage of a CBR Spam Filtering System.

Author

Carbonell, Jaime G., Siekmann, Jörg, Weber, Rosina O., Richter, Michael M., Méndez, José Ramón, González, Carlos, Glez-Peña, Daniel, Fdez-Riverola, Florentino, Díaz, Fernando, and Corchado, Juan Manuel

Abstract

In this paper we introduce a quality metric for characterizing the solutions generated by a successful CBR spam filtering system called SpamHunting. The proposal is denoted as relevant information amount rate and it is based on combining estimations about relevance and amount of information recovered during the retrieve stage of a CBR system. The results obtained from experimentation show how this measure can successfully be used as a suitable complement for the classifications computed by our SpamHunting system. In order to evaluate the performance of the quality estimation index, we have designed a formal benchmark procedure that can be used to evaluate any accuracy metric. Finally, following the designed test procedure, we show the behaviour of the proposed measure using two well-known publicly available corpus. [ABSTRACT FROM AUTHOR]

Published
2007
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44. Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data.

Author

Corchado, Emilio, Yin, Hujun, Botti, Vicente, Fyfe, Colin, Díaz, Fernando, Fdez-Riverola, Florentino, Glez-Peña, Daniel, and Corchado, Juan M.

Abstract

The advent of DNA microarray technology has supplied a large volume of data to many fields like machine learning and data mining. Intelligent support is essential for managing and interpreting this great amount of information. One of the well-known constraints specifically related to microarray data is the large number of genes in comparison with the small number of available experiments. In this context, the ability of design methods capable of overcoming current limitations of state-of-the-art algorithms is crucial to the development of successful applications. In this paper we demonstrate how a supervised fuzzy pattern algorithm can be used to perform DNA microarray data reduction over real data. The benefits of our method can be employed to find biologically significant insights relating to meaningful genes in order to improve previous successful techniques. Experimental results on acute myeloid leukemia diagnosis show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Published
2006
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45. Applying GCS Networks to Fuzzy Discretized Microarray Data for Tumour Diagnosis.

Author

Corchado, Emilio, Yin, Hujun, Botti, Vicente, Fyfe, Colin, Díaz, Fernando, Fdez-Riverola, Florentino, Glez-Peña, Daniel, and Corchado, J. M.

Abstract

Gene expression profiles belonging to DNA microarrays are composed of thousands of genes at the same time, representing the complex relationships between them. In this context, the ability of designing methods capable of overcoming current limitations is crucial to reduce the generalization error of state-of-the-art algorithms. This paper presents the application of a self-organised growing cell structures network in an attempt to cluster biological homogeneous patients. This technique makes use of a previous successful supervised fuzzy pattern algorithm capable of performing DNA microarray data reduction. The proposed model has been tested with microarray data belonging to bone marrow samples from 43 adult patients with cancer plus a group of six cases corresponding to healthy persons. The results of this work demonstrate that classical artificial intelligence techniques can be effectively used for tumour diagnosis working with high-dimensional microarray data. [ABSTRACT FROM AUTHOR]

Published
2006
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46. Improving Gene Selection in Microarray Data Analysis Using Fuzzy Patterns Inside a CBR System.

Author

Muñoz-Avila, Héctor, Ricci, Francesco, Fdez-Riverola, Florentino, Díaz, Fernando, Borrajo, M. Lourdes, Yáñez, J. Carlos, and Corchado, Juan M.

Abstract

In recent years, machine learning and data mining fields have found a successful application area in the field of DNA microarray technology. Gene expression profiles are composed of thousands of genes at the same time, representing complex relationships between them. One of the well-known constraints specifically related to microarray data is the large number of genes in comparison with the small number of available experiments or cases. In this context, the ability to identify an accurate gene selection strategy is crucial to reduce the generalization error (false positives) of state-of-the-art classification algorithms. This paper presents a reduction algorithm based on the notion of fuzzy gene expression, where similar (co-expressed) genes belonging to different patients are selected in order to construct a supervised prototype-based retrieval model. This technique is employed to implement the retrieval step in our new gene-CBR system. The proposed method is illustrated with the analysis of microarray data belonging to bone marrow cases from 43 adult patients with cancer plus a group of three cases corresponding to healthy persons. [ABSTRACT FROM AUTHOR]

Published
2005
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47. Autonomous Internal Control System for Small to Medium Firms.

Author

Muñoz-Avila, Héctor, Ricci, Francesco, Borrajo, M. Lourdes, Corchado, Juan M., Yáñez, J. Carlos, Fdez-Riverola, Florentino, and Díaz, Fernando

Abstract

Small to medium enterprises require an internal control mechanism in order to monitor their modus operandi and to analyse whether they are achieving their goals. A tool for the decision support process has been developed based on a case-based reasoning system that automates the internal control process. The objective of the system is to facilitate the process of internal auditing. The system analyses the data that characterises each one of the activities carried out by the firm, then determines the state of each activity, calculates the associated risk, detects the erroneous processes, and generates recommendations to improve these processes. The developed model is composed of two case-based reasoning systems. One is used to identify the activities that may be improved and the other to determine how the activities could be improved. Each of the two subsystems uses a different problem solving method in each of the steps of the reasoning cycle. The system has been tested in 22 small and medium companies in the textile sector, located in the northwest of Spain during the last 29 months and the results obtained have been very encouraging. [ABSTRACT FROM AUTHOR]

Published
2005
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