AIMC Topic: Algorithms

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FexRNA: Exploratory Data Analysis and Feature Selection of Non-Coding RNA.

IEEE/ACM transactions on computational biology and bioinformatics
Non-coding RNA (ncRNA) is involved in many biological processes and diseases in all species. Many ncRNA datasets exist that provide ncRNA data in FASTA format which is well suited for biomedical purposes. However, for ncRNA analysis and classificatio...

An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Myocardial infarctions and heart failure are the cause of more than 17 million deaths annually worldwide. ST-segment elevation myocardial infarctions (STEMI) require timely treatment, because delays of minutes have serious clinical impacts. Machine l...

Protein Fold Recognition From Sequences Using Convolutional and Recurrent Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of a protein fold type from its amino acid sequence provides important insights about the protein 3D structure. In this paper, we propose a deep learning architecture that can process protein residue-level features to address the p...

Protein Fold Recognition Based on Auto-Weighted Multi-View Graph Embedding Learning Model.

IEEE/ACM transactions on computational biology and bioinformatics
Protein fold recognition is critical for studies of the protein structure prediction and drug design. Several methods have been proposed to obtain discriminative features from the protein sequences for fold recognition. However, the ensemble methods ...

Prediction of Drug-Target Interactions Based on Network Representation Learning and Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying interactions between drugs and target proteins is a critical step in the drug development process, as it helps identify new targets for drugs and accelerate drug development. The number of known drug-protein interactions (positive samples...

A Novel Feature Selection Method for Uncertain Features: An Application to the Prediction of Pro-/Anti-Longevity Genes.

IEEE/ACM transactions on computational biology and bioinformatics
Understanding the ageing process is a very challenging problem for biologists. To help in this task, there has been a growing use of classification methods (from machine learning) to learn models that predict whether a gene influences the process of ...

Identifying Microbe-Disease Association Based on a Novel Back-Propagation Neural Network Model.

IEEE/ACM transactions on computational biology and bioinformatics
Over the years, numerous evidences have demonstrated that microbes living in the human body are closely related to human life activities and human diseases. However, traditional biological experiments are time-consuming and expensive, so it has becom...

Identifying Molecular Biomarkers for Diseases With Machine Learning Based on Integrative Omics.

IEEE/ACM transactions on computational biology and bioinformatics
Molecular biomarkers are certain molecules or set of molecules that can be of help for diagnosis or prognosis of diseases or disorders. In the past decades, thanks to the advances in high-throughput technologies, a huge amount of molecular 'omics' da...

Multi-Neighborhood Learning for Global Alignment in Biological Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The global alignment of biological networks (GABN) aims to find an optimal alignment between proteins across species, such that both the biological structures and the topological structures of the proteins are maximally conserved. The research on GAB...

Categorical Matrix Completion With Active Learning for High-Throughput Screening.

IEEE/ACM transactions on computational biology and bioinformatics
The recent advances in wet-lab automation enable high-throughput experiments to be conducted seamlessly. In particular, the exhaustive enumeration of all possible conditions is always involved in high-throughput screening. Nonetheless, such a screeni...