AIMC Topic: Neural Networks, Computer

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Computer Vision Positioning and Local Obstacle Avoidance Optimization Based on Neural Network Algorithm.

Computational intelligence and neuroscience
Due to the rapid development of social computerization and smart devices, there is an increasing demand for indoor positioning of mobile robots in the robotics field, so it is very important to realize the autonomous navigation of mobile robots. Howe...

Integrating Molecular Graph Data of Drugs and Multiple -Omic Data of Cell Lines for Drug Response Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Previous studies have either learned drug's features from their string or numeric representations, which are not natural forms of drugs, or only used genomic data of cell lines for the drug response prediction problem. Here, we proposed a deep learni...

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA)problem. However, previous deep learning-based methods ignore modeling the dire...

Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, cancer patients survival prediction holds important significance for worldwide health problems, and has gained many researchers attention in medical information communities. Cancer patients survival prediction can be seen the classif...

Identifying Protein Subcellular Locations With Embeddings-Based node2loc.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PP...

Predicting Biomedical Interactions With Higher-Order Graph Convolutional Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical interaction networks have incredible potential to be useful in the prediction of biologically meaningful interactions, identification of network biomarkers of disease, and the discovery of putative drug targets. Recently, graph neural netw...

Unit-Vise: Deep Shallow Unit-Vise Residual Neural Networks With Transition Layer For Expert Level Skin Cancer Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Many modern neural network architectures with over parameterized regime have been used for identification of skin cancer. Recent work showed that network, where the hidden units are polynomially smaller in size, showed better performance than overpar...

Ab-Initio Membrane Protein Amphipathic Helix Structure Prediction Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Amphipathic helix (AH)features the segregation of polar and nonpolar residues and plays important roles in many membrane-associated biological processes through interacting with both the lipid and the soluble phases. Although the AH structure has bee...

Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model.

IEEE/ACM transactions on computational biology and bioinformatics
Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the breast. Despite significant advances in the treatment of primary breast cancer in the last decade, there is a dire need to attempt of an accurate predictive mode...

DNA Privacy: Analyzing Malicious DNA Sequences Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Recent advances in next-generation sequencing technologies have led to the successful insertion of video information into DNA using synthesized oligonucleotides. Several attempts have been made to embed larger data into living organisms. This process...