AIMC Topic: Humans

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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...

Convolutional Neural Network With Graphical Lasso to Extract Sparse Topological Features for Brain Disease Classification.

IEEE/ACM transactions on computational biology and bioinformatics
The functional connectivity provides new insights into the mechanisms of the human brain at network-level, which has been proved to be an effective biomarker for brain disease classification. Recently, machine learning methods have played an importan...

A Convolutional Deep Clustering Framework for Gene Expression Time Series.

IEEE/ACM transactions on computational biology and bioinformatics
The functional or regulatory processes within the cell are explicitly governed by the expression levels of a subset of its genes. Gene expression time series captures activities of individual genes over time and aids revealing underlying cellular dyn...

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...

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
A growing amount of evidence suggests that long non-coding RNAs (lncRNAs) play important roles in the regulation of biological processes in many human diseases. However, the number of experimentally verified lncRNA-disease associations is very limite...

Improved Predicting of The Sequence Specificities of RNA Binding Proteins by Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
RNA-binding proteins (RBPs) have a significant role in various regulatory tasks. However, the mechanism by which RBPs identify the subsequence target RNAs is still not clear. In recent years, several machine and deep learning-based computational mode...

Multi-Label Classification Scheme Based on Local Regression for Retinal Vessel Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Segmenting small retinal vessels with width less than 2 pixels in fundus images is a challenging task. In this paper, in order to effectively segment the vessels, especially the narrow parts, we propose a local regression scheme to enhance the narrow...

Lesion Segmentation in Ultrasound Using Semi-Pixel-Wise Cycle Generative Adversarial Nets.

IEEE/ACM transactions on computational biology and bioinformatics
Breast cancer is the most common invasive cancer with the highest cancer occurrence in females. Handheld ultrasound is one of the most efficient ways to identify and diagnose the breast cancer. The area and the shape information of a lesion is very h...