Martínez Ríos, Félix Orlando

Main Affiliation

Facultad de Ingeniería - CampCM

Preferred name

Official Name

Martínez Ríos, Félix Orlando

ORCID

0000-0002-2346-5922

Researcher ID

N-7502-2018

Scopus Author ID

24339038500

Now showing 1 - 10 of 45

Some of the metrics are blocked by your
consent settings
StarPepWeb: an integrative, graph-based resource for bioactive peptides
(Oxford University Press, 2024)
López, Christian
;
Cárdenas, Roberto
;
Aguilera-Mendoza, Longendri
;
Agüero-Chapin, Guillermin
;
Martínez Ríos, Félix Orlando
Motivation: The rapid growth of bioactive peptide sequences presents challenges for organization and analysis. Existing repositories often specialize in functions, taxonomic origins, or structural classes, but most remain isolated, use heterogeneous metadata, and lack uniform descriptors or structural models. Few integrative web services exist, offering only partial coverage or depth. As a result, reproducible and comprehensive exploration of the bioactive peptide landscape remains limited, underscoring the need for a unified, source-tracked, extensible platform. Results: We present StarPepWeb, a freely accessible web application that democratizes access to StarPepDB, one of the largest curated repositories of bioactive peptides. The platform integrates 45 120 non-redundant sequences from 40 public databases into a source-tracked graph enriched with metadata, physicochemical features, and predicted 3D structures from ESMFold. Each peptide is represented with ESM-2 embeddings and iFeature descriptors, while the interface supports metadata-aware filtering, alignment-based similarity searches with single and multiple queries, and interactive visualization. A microservice-oriented architecture ensures scalability, maintainability, and reproducible versioned downloads, including Neo4j exports. StarPepWeb thus overcomes deployment and expertise barriers of the standalone database, providing an extensible, cloud-hosted framework for integrative bioactive peptide analysis. ©The authors ©Oxford University Press.
Some of the metrics are blocked by your
consent settings
A hybrid simulated annealing and threshold accepting for satisfiability problems using dynamically cooling schemes
(2007)
Martínez Ríos, Félix Orlando
;
Frausto-Solís, Juan
For Satisfiability (SAT) Problem there is not a deterministic algorithm able to solve it in a polynomial time. Simulated Annealing (SA) and similar algorithms like Threshold Accepting (TA) are able to find very good solutions of SAT instances only if their control parameters are correctly tuned. Classical TA usually uses the same Markov chain length for each temperature cycle but they spend a lot of time. In this paper a method based on the neighborhood structure to get the Markov chain length in a dynamical way for each temperature cycle is proposed. Three cooling schemes are also presented in the paper. The experimentation presented in the paper shows that the proposed method is more efficient than the classical one.
46 1
Some of the metrics are blocked by your
consent settings
A first-year design experience based on SAE Aero Design contest to support ABET learning outcomes and engineering vocation in freshmen student
(2017)
Martínez Ríos, Félix Orlando
The a-k outcomes established by Accreditation Board for Engineering and Technology (ABET) for Engineering students in their self-assessment framework, should be reflected in the different subjects that taught to the students of the first two years of the various engineering programs. On the other hand, in those first semesters, the vocation of the students about the different Engineering is not very well defined. This experiment shows a proposal that links the results of ABET with an international student competition such as Society of Automotive Engineers (SAE) Aero Design, to reinforce and guide the new students in their future choice of specialization in the School of Engineering. We also show the relationship between the challenges and problems in the SAE Aero Design competition for new students and ABET's a-k outcomes. We show the results obtained with nineteen students over three years. It is important to mention that none of the students involved in this experiment comes from Aeronautical Engineering (or similar to it).
21 1
Some of the metrics are blocked by your
consent settings
Unraveling the hemolytic toxicity tapestry of peptides using chemical space complex networks
(Oxford University Press, 2024)
Castillo-Mendieta, Kevin
;
Agüero-Chapin, Guillermin
;
Mora, José R.
;
Pérez, Noel
;
Contreras-Torres, Ernesto
Peptides have emerged as promising therapeutic agents. However, their potential is hindered by hemotoxicity. Understanding the hemotoxicity of peptides is crucial for developing safe and effective peptide-based therapeutics. Here, we employed chemical space complex networks (CSNs) to unravel the hemotoxicity tapestry of peptides. CSNs are powerful tools for visualizing and analyzing the relationships between peptides based on their physicochemical properties and structural features. We constructed CSNs from the StarPepDB database, encompassing 2,004 hemolytic peptides, and explored the impact of seven different (dis)similarity measures on network topology and cluster (communities) distribution. Our findings revealed that each CSN extracts orthogonal information, enhancing the motif discovery and enrichment process. We identified 12 consensus hemolytic motifs, whose amino acid composition unveiled a high abundance of lysine, leucine, and valine residues, whereas aspartic acid, methionine, histidine, asparagine, and glutamine were depleted. Additionally, physicochemical properties were used to characterize clusters/communities of hemolytic peptides. To predict hemolytic activity directly from peptide sequences, we constructed multi-query similarity searching models, which outperformed cutting-edge machine learning-based models, demonstrating robust hemotoxicity prediction capabilities. Overall, this novel in silico approach uses complex network science as its central strategy to develop robust model classifiers, characterize the chemical space, and discover new motifs from hemolytic peptides. This will help to enhance the design/selection of peptides with potential therapeutic activity and low toxicity. ©2024 Toxicological Sciences ©2024 The authors.
18
Some of the metrics are blocked by your
consent settings
An efficient method to compare latencies in order to obtain the best route for SDN
(2017)
Elguea, Lorenzo M.
;
Martínez Ríos, Félix Orlando
Comparing two or more routes on Internet is difficult owing to the variability of the measurements resulting from the different routes or use conditions. With current tools such as SDN[1], it is important to determine with certainty which the best route between a user and an internet service. This will be achieved with fast measurements which do not affect the operation of the network. With trends such as IoT, the best routes can be identified based on latency and not just on the jumps between autonomous systems, fact that optimizes data traffic in a specific way whether it is IPv4 or IPv6. As time elapses, it becomes more important to have a perfect setting for the LAN, which means optimal DNS, LDAP Servers appropriate number, etc. Thats why we propose a precise method that contemplates every possible variation of data, thus making a comparison by means of the use of confidence limits.
Scopus© Citations 6 11 1
Some of the metrics are blocked by your
consent settings
Golden Ratio Annealing for Satisfiability Problems Using Dynamically Cooling Schemes
(2008)
Frausto-Solís, Juan
;
Martínez Ríos, Félix Orlando
Abstract Satisfiability (SAT) Problem is an NP-Complete problem which means no deterministic algorithm is able to solve it in a polynomial time. Simulated Annealing (SA) can find very good solutions of SAT instances if its control parameters are correctly tuned. SA can be tuned experimentally or by using a Markov approach; the latter has been shown to be the most efficient one. Moreover Golden Ratio (GR) is an unconventional technique used to solve many problems. In this paper a new algorithm named Golden Ratio for Simulated Annealing (GRSA) is presented; it is tuned for three different cooling schemes. GRSA uses GR to dynamically decrease the SA temperature and a Markov Model to tune its parameters. Two SA tuned versions are compared in this paper: GRSA and a classical SA. Experimentation shows that the former is much more efficient than the latter. © Springer Nature
Scopus© Citations 3 34 2
Some of the metrics are blocked by your
consent settings
A new swarm algorithm for global optimization of multimodal functions over multi-threading architecture hybridized with simulating annealing
(2018)
Martínez Ríos, Félix Orlando
;
Murillo-Suarez, Alfonso
This paper presents a new algorithm, PCLPSO, based on particle swarm optimization, which uses comprehensive learning particle swarm optimizer. Our algorithm executes C parallel CLPSO algorithms. We adopted as a criterion of completion a maximum value of evaluations of the objective function. During the execution of the CLPSO algorithms, when a certain evaluation value of the functions is reached, the best k are selected, and different initialization criteria are applied to continue the execution of the CLPSO algorithms: restarting the worst ones for the best solution or restores the worst ones to a random solution. For this restart, we use the Boltzmann criterion in a similar way as Simulating Annealing (SA) does. In this work, the experimental results obtained for the search of the minimum of 16 multimodal test functions such as Rosenbrock, Griewank, Rastrigin, Brannin, Schwefel, and others. Our algorithm proved to be more efficient than the traditional CLPSO in its experimental results, and the nonparametric Wilcoxon test confirmed this.
Scopus© Citations 7 18 1
Some of the metrics are blocked by your
consent settings
A multiprocess Salp swarm optimization with a heuristic based on crossing partial solutions
(2021)
Martínez Ríos, Félix Orlando
;
Murillo-Suarez, Alfonso
The Salp swarm algorithm (SSA) is one of the most recent metaheuristic optimization algorithms. SSA has been used succesfully to solve optimization problems in different research areas such as machine learning, engineering design, wireless networks, image processing, mobile robotics, and energy. In this article, we present a multi-threaded implementation of the SSA algorithm. Each thread executes an SSA algorithm that shares information among the swarms to get a better solution. The best partial solutions of each swarm intersect in a similar way of genetic algorithms. The experiments with nineteen benchmark functions (unimodal, multimodal, and composite) show the results obtained with this new algorithm are better than those achieved with the original algorithm. © 2020 The Authors. Published by Elsevier B.V.
Scopus© Citations 2 26 1
Some of the metrics are blocked by your
consent settings
A new heuristic with a multi-threaded implementation of a modified Firefly Algorithm
(2018)
Murillo-Suárez, Alfonso
;
Martínez Ríos, Félix Orlando
In this article, we present a modified version of the Firefly Algorithm implemented in a multi-threaded model to improve the results obtained by the original algorithm significantly. This multi-threaded algorithm allows the threads to obtain different results by the independent execution of the heuristic method in each of them, although for keeping all the threads with significant executions, the algorithm performs some crossover techniques, explained in detail in this article, for the threads to learn between them while maintaining its independence. For testing the new algorithm, we use the six benchmark functions used in the literature for testing the original Firefly Algorithm, and to prove that the improved results are significant, we perform the Wilcoxon test to the results obtained. The results obtained with this new heuristic proved to be significantly better while taking advantage of today's commercial processors. © 2020 Alfonso Murillo-Suarez et al., licensed to EAI.
28 1
Some of the metrics are blocked by your
consent settings
A new hybridized algorithm based on Population-Based Simulated Annealing with an experimental study of phase transition in 3-SAT
(2017)
Martínez Ríos, Félix Orlando
This paper is about experiments for satisfiability problem using a new algorithm (GR-MM-PBSA) that improves the algorithm Population-Based Simulated Annealing (PBSA). GR-MM-PBSA runs in a parallel way Simulated Annealing (SA) and Threshold Annealing (TA) algorithms with a Golden Ratio space search strategy and Markovian Model to select initial and final temperature. In this paper we execute differents hybridized Simulated Annealing (or Threshold Accepting) algorithms and compares the efficiency of these, using a metric based on transition phase effect. Simulated Annealing Algorithms (SAA) theoretically can reach the optimum if the control parameters and cooling scheme are chosen correctly. All algorithms are compared with a metric based on transition phase obtained for 3-SAT instances. This paper shows the results of SAA hybridizations are more efficient than the original algorithm, without increasing their computational complexity. We also show the experimental data about runs with 820 3-SAT instances with ratio clauses-variables between 2.0 to 6.0.
Scopus© Citations 7 28 1

Martínez Ríos, Félix Orlando

Filters

Settings

Sort By

Results per page