An evolutionary scheme for decision tree construction
Classification is a central task in machine learning and data mining. Decision tree (DT) is
one of the most popular learning models in data mining. The performance of a DT in a …
one of the most popular learning models in data mining. The performance of a DT in a …
A Model for Manganese interaction with Deinococcus radiodurans proteome network involved in ROS response and defense
A complex network of regulatory proteins takes part in the mechanism underlying the
radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn (II) ions …
radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn (II) ions …
A closed frequent subgraph mining algorithm in unique edge label graphs
Problems such as closed frequent subset mining, itemset mining, and connected tree mining
can be solved in a polynomial delay. However, the problem of mining closed frequent …
can be solved in a polynomial delay. However, the problem of mining closed frequent …
Multiple instance learning for sequence data with across bag dependencies
Abstract In Multiple Instance Learning (MIL) problem for sequence data, the instances inside
the bags are sequences. In some real world applications such as bioinformatics, comparing …
the bags are sequences. In some real world applications such as bioinformatics, comparing …
Insights into ionizing-radiation-resistant bacteria S-layer proteins and nanobiotechnology for bioremediation of hazardous and radioactive waste
S-layers are crystalline arrays formed by proteinaceous subunits that cover the outer surface
of many different kinds of microorganisms. This “proteinaceous cover” is particularly …
of many different kinds of microorganisms. This “proteinaceous cover” is particularly …
Multiple instance learning for sequence data: Application on bacterial ionizing radiation resistance prediction
M Zoghlami - 2019 - theses.hal.science
In Multiple Instance Learning (MIL) problem for sequence data, the instances inside the
bags aresequences. In some real world applications such as bioinformatics, comparing a …
bags aresequences. In some real world applications such as bioinformatics, comparing a …
An overview of in silico methods for the prediction of ionizing radiation resistance in bacteria
Ionizing-radiation-resistant bacteria (IRRB) could be used for biore-mediation of radioactive
wastes and in the therapeutic industry. Limited computational works are available for the …
wastes and in the therapeutic industry. Limited computational works are available for the …
Découverte de connaissances à partir de grands graphes biologiques
S Aridhi - 2023 - hal.science
Les graphes sont utilisés dans de nombreux domaines différents, allant de la sécurité
informatique des réseaux sociaux, à la géographie et à la bioinformatique. Leur polyvalence …
informatique des réseaux sociaux, à la géographie et à la bioinformatique. Leur polyvalence …
A structure based multiple instance learning approach for bacterial ionizing radiation resistance prediction
Ionizing-radiation-resistant bacteria (IRRB) could be used for bioremediation of radioactive
wastes and in the therapeutic industry. Limited computational works are available for the …
wastes and in the therapeutic industry. Limited computational works are available for the …
[PDF][PDF] A multiple instance learning approach for sequence data with across bag dependencies
ABSTRACT In Multiple Instance Learning (MIL) problem for sequence data, the learning
data consist of a set of bags where each bag contains a set of instances/sequences. In many …
data consist of a set of bags where each bag contains a set of instances/sequences. In many …