A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies

J Parraga-Alava, M Dorn, M Inostroza-Ponta - BioData mining, 2018 - Springer
Background Biologists aim to understand the genetic background of diseases, metabolic
disorders or any other genetic condition. Microarrays are one of the main high-throughput …

A bi-objective model for gene clustering combining expression data and external biological knowledge

J Parraga-Alava… - 2016 XLII Latin American …, 2016 - ieeexplore.ieee.org
Clustering algorithms have been widely used by biologists to identify clusters of co-related
genes. Traditional approaches consider the gene clustering as an optimization problem …

Dynamic clustering of gene expression data using a fuzzy approach

AM Sîrbu, G Czibula, MI Bocicor - 2014 16th International …, 2014 - ieeexplore.ieee.org
The amount of gene expression data gathered in the last decade has increased
exponentially due to modern technologies like micro array and next-generation sequencing …

Dynamic machine learning for supervised and unsupervised classification

AM Sîrbu - 2016 - theses.hal.science
The research direction we are focusing on in the thesis is applying dynamic machine
learning models to salve supervised and unsupervised classification problems. We are …

A STUDY ON DYNAMIC CLUSTERING OF GENE EXPRESSION DATA.

A SÎRBU - Studia Universitatis Babes-Bolyai, Informatica, 2014 - search.ebscohost.com
Microarray and next-generation sequencing technologies allow measuring the levels of
expressions of thousands of genes simultaneously. One of the most popular procedures …

[PDF][PDF] LOODUS-JA TÄPPISTEADUSTE VALDKOND

R Tammela - core.ac.uk
Suurem osa rakutüüpidest vabastab ekstratsellulaarseid vesiikuleid‒membraaniga
ümbritsetud valkude, nukleiinhapete ja teiste biomolekulide kandjaid, mis osalevad nende …