Feature selection methods for big data bioinformatics: A survey from the search perspective
L Wang, Y Wang, Q Chang - Methods, 2016 - Elsevier
This paper surveys main principles of feature selection and their recent applications in big
data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and …
data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and …
Predicting novel microRNA: a comprehensive comparison of machine learning approaches
Motivation The importance of microRNAs (miRNAs) is widely recognized in the community
nowadays because these short segments of RNA can play several roles in almost all …
nowadays because these short segments of RNA can play several roles in almost all …
GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides
Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA)
sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is …
sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is …
Deep neural architectures for highly imbalanced data in bioinformatics
In the postgenome era, many problems in bioinformatics have arisen due to the generation
of large amounts of imbalanced data. In particular, the computational classification of …
of large amounts of imbalanced data. In particular, the computational classification of …
[PDF][PDF] MEvA-X: a hybrid multiobjective evolutionary tool using an XGBoost classifier for biomarkers discovery on biomedical datasets
Motivation Biomarker discovery is one of the most frequent pursuits in bioinformatics and is
crucial for precision medicine, disease prognosis, and drug discovery. A common challenge …
crucial for precision medicine, disease prognosis, and drug discovery. A common challenge …
Overcoming the main challenges of knowledge discovery through tendency to the intelligent data analysis
S Al-Janabi - 2021 International Conference on Data Analytics …, 2021 - ieeexplore.ieee.org
Intelligent Data Analysis (IDA) approach proves its ability to deal with small and huge data
sets; this ability can be done by generating and developing new methodologies. While; …
sets; this ability can be done by generating and developing new methodologies. While; …
Hybrid deep neural network for handling data imbalance in precursor MicroRNA
Over the last decade, the field of bioinformatics has been increasing rapidly. Robust
bioinformatics tools are going to play a vital role in future progress. Scientists working in the …
bioinformatics tools are going to play a vital role in future progress. Scientists working in the …
Intuitionistic fuzzy multi-view support vector machines with universum data
C Lou, X Xie - Applied Intelligence, 2024 - Springer
As an energizing direction in machine learning, multi-view learning (MVL) is aimed at
exploiting the information among different views for improving the generalization …
exploiting the information among different views for improving the generalization …
High class-imbalance in pre-miRNA prediction: a novel approach based on deepSOM
G Stegmayer, C Yones, L Kamenetzky… - … /ACM transactions on …, 2016 - ieeexplore.ieee.org
The computational prediction of novel microRNA within a full genome involves identifying
sequences having the highest chance of being a miRNA precursor (pre-miRNA). These …
sequences having the highest chance of being a miRNA precursor (pre-miRNA). These …
An early intestinal cancer prediction algorithm based on deep belief network
The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in
recent years, and its mortality rate has become one of the highest among all cancers. CRC …
recent years, and its mortality rate has become one of the highest among all cancers. CRC …