A new master-slave binary grey wolf optimizer (MSBGWO) is introduced. A master-slave learning scheme is introduced to the grey wolf optimizer (GWO) to improve its ability to explore and get better solutions in a search space. Five high-dimensional bi...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
In the past few years, the prediction models have shown remarkable performance in most biological correlation prediction tasks. These tasks traditionally use a fixed dataset, and the model, once trained, is deployed as is. These models often encounte...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Identification of lncRNA-disease associations is not only important for exploring the disease mechanism, but will also facilitate the molecular targeting drug discovery. Fusing multiple biological information is able to generate a more comprehensive ...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Mammalian Target of Rapamycin (mTOR) is a Ser/Thr protein kinase, and its role is integral to the autophagy pathway in cancer. Targeting mTOR for therapeutic interventions in cancer through autophagy pathway is challenging due to the dual roles of au...
Medical & biological engineering & computing
Oct 5, 2021
Computational classification of cancers is an important research problem. Gene expression data has 1000s of features, very few samples, and a class imbalance problem. In this paper, we have proposed a framework for the classification of cancer gene e...
IEEE journal of biomedical and health informatics
Oct 5, 2021
Biophysical protein-protein interactions perform dominant roles in the initiation and progression of many cancer-related pathways. A protein-protein interaction might play different roles in diverse cancer types. Hence, prioritizing the PPIs in each ...
Computational intelligence and neuroscience
Oct 5, 2021
The correct classification of cancer subtypes is of great significance for the in-depth study of cancer pathogenesis and the realization of accurate treatment for cancer patients. In recent years, the classification of cancer subtypes using deep neur...
BMC medical informatics and decision making
Oct 2, 2021
BACKGROUND: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their im...
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across health...
BACKGROUND: With the rapid advancement of genomic sequencing techniques, massive production of gene expression data is becoming possible, which prompts the development of precision medicine. Deep learning is a promising approach for phenotype predict...
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