Dealing with dimensionality: the application of machine learning to multi-omics data
D Feldner-Busztin, P Firbas Nisantzis… - …, 2023 - academic.oup.com
Motivation Machine learning (ML) methods are motivated by the need to automate
information extraction from large datasets in order to support human users in data-driven …
information extraction from large datasets in order to support human users in data-driven …
Transformer architecture and attention mechanisms in genome data analysis: a comprehensive review
SR Choi, M Lee - Biology, 2023 - mdpi.com
Simple Summary The rapidly advancing field of deep learning, specifically transformer-
based architectures and attention mechanisms, has found substantial applicability in …
based architectures and attention mechanisms, has found substantial applicability in …
Unbiased curriculum learning enhanced global-local graph neural network for protein thermodynamic stability prediction
Motivation Proteins play crucial roles in biological processes, with their functions being
closely tied to thermodynamic stability. However, measuring stability changes upon point …
closely tied to thermodynamic stability. However, measuring stability changes upon point …
Diagnosis of glioblastoma multiforme progression via interpretable structure-constrained graph neural networks
Glioblastoma multiforme (GBM) is the most common type of brain tumors with high
recurrence and mortality rates. After chemotherapy treatment, GBM patients still show a high …
recurrence and mortality rates. After chemotherapy treatment, GBM patients still show a high …
MHADTI: predicting drug–target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms
Motivation Discovering the drug–target interactions (DTIs) is a crucial step in drug
development such as the identification of drug side effects and drug repositioning. Since …
development such as the identification of drug side effects and drug repositioning. Since …
Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis
M Duan, Y Wang, D Zhao, H Liu, G Zhang… - Briefings in …, 2023 - academic.oup.com
Survival analysis is critical to cancer prognosis estimation. High-throughput technologies
facilitate the increase in the dimension of genic features, but the number of clinical samples …
facilitate the increase in the dimension of genic features, but the number of clinical samples …
Multi-scale characterisation of homologous recombination deficiency in breast cancer
Background Homologous recombination is a robust, broadly error-free mechanism of double-
strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying …
strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying …
A systematic review of graph neural network in healthcare-based applications: Recent advances, trends, and future directions
Graph neural network (GNN) is a formidable deep learning framework that enables the
analysis and modeling of intricate relationships present in data structured as graphs. In …
analysis and modeling of intricate relationships present in data structured as graphs. In …
Deep Learning‐Based Multiomics Data Integration Methods for Biomedical Application
Y Wen, L Zheng, D Leng, C Dai, J Lu… - Advanced Intelligent …, 2023 - Wiley Online Library
The innovation of high‐throughput technologies and medical radiomics allows biomedical
data to accumulate at an astonishing rate. Several promising deep learning (DL) methods …
data to accumulate at an astonishing rate. Several promising deep learning (DL) methods …
TEMINET: A Co-Informative and Trustworthy Multi-Omics Integration Network for Diagnostic Prediction
H Luo, H Liang, H Liu, Z Fan, Y Wei, X Yao… - International Journal of …, 2024 - mdpi.com
Advancing the domain of biomedical investigation, integrated multi-omics data have shown
exceptional performance in elucidating complex human diseases. However, as the variety of …
exceptional performance in elucidating complex human diseases. However, as the variety of …