Classification of lung cancer using ensemble-based feature selection and machine learning methods
Lung cancer is one of the leading causes of death worldwide. There are three major types of
lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and …
lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and …
[HTML][HTML] A topological approach for protein classification
Protein function and dynamics are closely related to its sequence and structure. However,
prediction of protein function and dynamics from its sequence and structure is still a …
prediction of protein function and dynamics from its sequence and structure is still a …
[HTML][HTML] Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
Screening and in silico modeling are critical activities for the reduction of experimental costs.
They also speed up research notably and strengthen the theoretical framework, thus …
They also speed up research notably and strengthen the theoretical framework, thus …
FS–GBDT: identification multicancer-risk module via a feature selection algorithm by integrating Fisher score and GBDT
J Zhang, D Xu, K Hao, Y Zhang, W Chen… - Briefings in …, 2021 - academic.oup.com
Cancer is a highly heterogeneous disease caused by dysregulation in different cell types
and tissues. However, different cancers may share common mechanisms. It is critical to …
and tissues. However, different cancers may share common mechanisms. It is critical to …
Prediction of bacterial protein subcellular localization by incorporating various features into Chou's PseAAC and a backward feature selection approach
L Li, S Yu, W Xiao, Y Li, M Li, L Huang, X Zheng… - Biochimie, 2014 - Elsevier
Abstract Information on the subcellular localization of bacterial proteins is essential for
protein function prediction, genome annotation and drug design. Here we proposed a novel …
protein function prediction, genome annotation and drug design. Here we proposed a novel …
Classification of mild cognitive impairment and Alzheimer's Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
Several magnetic resonance techniques have been proposed as non-invasive imaging
biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer's …
biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer's …
Texture classification using feature selection and kernel-based techniques
The interpretation of the results in a classification problem can be enhanced, specially in
image texture analysis problems, by feature selection techniques, knowing which features …
image texture analysis problems, by feature selection techniques, knowing which features …
[HTML][HTML] Effects of brain atlases and machine learning methods on the discrimination of schizophrenia patients: a multimodal MRI study
J Zang, Y Huang, L Kong, B Lei, P Ke, H Li… - Frontiers in …, 2021 - frontiersin.org
Recently, machine learning techniques have been widely applied in discriminative studies
of schizophrenia (SZ) patients with multimodal magnetic resonance imaging (MRI); however …
of schizophrenia (SZ) patients with multimodal magnetic resonance imaging (MRI); however …
Solvent accessible surface area-based hot-spot detection methods for protein–protein and protein–nucleic acid interfaces
CR Munteanu, AC Pimenta… - Journal of chemical …, 2015 - ACS Publications
Due to the importance of hot-spots (HS) detection and the efficiency of computational
methodologies, several HS detecting approaches have been developed. The current paper …
methodologies, several HS detecting approaches have been developed. The current paper …
[HTML][HTML] Sequence-based identification of recombination spots using pseudo nucleic acid representation and recursive feature extraction by linear kernel SVM
L Li, S Yu, W Xiao, Y Li, L Huang, X Zheng, S Zhou… - BMC …, 2014 - Springer
Background Identification of the recombination hot/cold spots is critical for understanding the
mechanism of recombination as well as the genome evolution process. However …
mechanism of recombination as well as the genome evolution process. However …