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Diego A. Hartasánchez

dblp:55/8285 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0003-2596-6883ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular evolution
molecular evolution simulation
0.212016
SeDuS: segmental duplication simulator · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

forward-in-time simulation · 0.2
YearPublicationVenuePosition
2016 SeDuS: segmental duplication simulator
abstract
SUMMARY: SeDuS is the first flexible and user-friendly forward-in-time simulator of patterns of molecular evolution within segmental duplications undergoing interlocus gene conversion and crossover. SeDuS introduces known features of interlocus gene conversion such as biased directionality and dependence on local sequence identity. Additionally, it includes aspects such as different selective pressures acting upon copy number and flexible crossover distributions. A graphical user interface allows fast fine-tuning of relevant parameters and straightforward real-time analysis of the evolution of duplicates. AVAILABILITY AND IMPLEMENTATION: SeDuS is implemented in C++ and can be run via command line or through a graphical user interface developed using Qt C++. Source code and binary executables for Linux, OS X and Windows are freely available at www.biologiaevolutiva.org/sedus/. A tutorial with a detailed description of implementation, parameters and output files is available online. CONTACT: [email protected].
Diego A. Hartasánchez, Marina Brasó-Vives, Juanma Fuentes-Díaz, Oriol Vallès-Codina, Arcadi Navarro
Bioinform.1
2010 Why recombination should be adaptive
abstract
Crossover is the most complicated of the standard genetic operators as well as one of the main operators in genetic algorithms. The role of the crossover operator has not been satisfactorily explained. It has not been easy to show if it is essential for the construction and exploitation of building blocks during evolution. In this paper we introduce an adaptive crossover operator for two test functions. The results show that there is a clear increase in the rate of evolution when information on the state of the population is used to select the crossover point, compared to random selection of the crossover point.
Patricia Ortegon-Cano, Diego A. Hartasánchez, Christopher R. Stephens
GECCO2