Feature extraction approaches for biological sequences: a comparative study of mathematical features
RP Bonidia, LDH Sampaio… - Briefings in …, 2021 - academic.oup.com
As consequence of the various genomic sequencing projects, an increasing volume of
biological sequence data is being produced. Although machine learning algorithms have …
biological sequence data is being produced. Although machine learning algorithms have …
Clustering cancer gene expression data: a comparative study
Background The use of clustering methods for the discovery of cancer subtypes has drawn a
great deal of attention in the scientific community. While bioinformaticians have proposed …
great deal of attention in the scientific community. While bioinformaticians have proposed …
Analysis of similarity measures in times series clustering for the discovery of building energy patterns
F Iglesias, W Kastner - Energies, 2013 - mdpi.com
Forecasting and modeling building energy profiles require tools able to discover patterns
within large amounts of collected information. Clustering is the main technique used to …
within large amounts of collected information. Clustering is the main technique used to …
Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications
JA Howrylak, AL Fuhlbrigge, RC Strunk… - Journal of allergy and …, 2014 - Elsevier
Background Although recent studies have identified the presence of phenotypic clusters in
asthmatic patients, the clinical significance and temporal stability of these clusters have not …
asthmatic patients, the clinical significance and temporal stability of these clusters have not …
Green energy in central and eastern European (CEE) countries: new challenges on the path to sustainable development
T Pakulska - Energies, 2021 - mdpi.com
In the conditions of climate change and the scarcity of natural resources, the future of energy
is increasingly associated with the development of the so-called green energy. Its …
is increasingly associated with the development of the so-called green energy. Its …
A hybrid technique for EEG signals evaluation and classification as a step towards to neurological and cerebral disorders diagnosis
Electroencephalography (EEG) signals are commonly used to identify and diagnose brain
disorders. Each EEG normal waveform consists of the following waveforms: Gamma (γ) …
disorders. Each EEG normal waveform consists of the following waveforms: Gamma (γ) …
A structured view on pattern mining-based biclustering
Mining matrices to find relevant biclusters, subsets of rows exhibiting a coherent pattern over
a subset of columns, is a critical task for a wide-set of biomedical and social applications …
a subset of columns, is a critical task for a wide-set of biomedical and social applications …
Machine learning clustering for blood pressure variability applied to systolic blood pressure intervention trial (SPRINT) and the Hong Kong community cohort
Visit-to-visit blood pressure variability (BPV) has been shown to be a predictor of
cardiovascular disease. We aimed to classify the BPV levels using different machine …
cardiovascular disease. We aimed to classify the BPV levels using different machine …
BicPAM: Pattern-based biclustering for biomedical data analysis
R Henriques, SC Madeira - Algorithms for Molecular Biology, 2014 - Springer
Background Biclustering, the discovery of sets of objects with a coherent pattern across a
subset of conditions, is a critical task to study a wide-set of biomedical problems, where …
subset of conditions, is a critical task to study a wide-set of biomedical problems, where …