AIMC Topic: Computational Biology

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Knowledge-Powered Deep Breast Tumor Classification With Multiple Medical Reports.

IEEE/ACM transactions on computational biology and bioinformatics
Breast tumor classification with multiple medical reports such as B-ultrasound, Mammography (X-ray) and Nuclear Magnetic Resonance Imaging (MRI) is crucial to the intelligent cancer diagnosis system. Unlike the other domain texts, the medical reports...

A Method of Information Protection for Collaborative Deep Learning under GAN Model Attack.

IEEE/ACM transactions on computational biology and bioinformatics
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...

Machine Learning to Support the Presentation of Complex Pathway Graphs.

IEEE/ACM transactions on computational biology and bioinformatics
Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult and time consuming process. Node duplication i...

MILAMP: Multiple Instance Prediction of Amyloid Proteins.

IEEE/ACM transactions on computational biology and bioinformatics
Amyloid proteins are implicated in several diseases such as Parkinson's, Alzheimer's, prion diseases, etc. In order to characterize the amyloidogenicity of a given protein, it is important to locate the amyloid forming hotspot regions within the prot...

ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion.

IEEE/ACM transactions on computational biology and bioinformatics
The dysregulation and mutation of long non-coding RNAs (lncRNAs) have been proved to result in a variety of human diseases. Identifying potential disease-related lncRNAs may benefit disease diagnosis, treatment and prognosis. A number of methods have...

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...

coupleCoC+: An information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data.

PLoS computational biology
Technological advances have enabled us to profile multiple molecular layers at unprecedented single-cell resolution and the available datasets from multiple samples or domains are growing. These datasets, including scRNA-seq data, scATAC-seq data and...

In silico drug repositioning using deep learning and comprehensive similarity measures.

BMC bioinformatics
BACKGROUND: Drug repositioning, meanings finding new uses for existing drugs, which can accelerate the processing of new drugs research and development. Various computational methods have been presented to predict novel drug-disease associations for ...

Galaxy-ML: An accessible, reproducible, and scalable machine learning toolkit for biomedicine.

PLoS computational biology
Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical scien...