AIMC Topic: Computational Biology
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AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data.
Scientific reports
Dec 5, 2024
AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement in next-generation sequencing, an enormous amount of AD-associated genomics data is available. However, the information about the involvement of these...
Geometric Molecular Graph Representation Learning Model for Drug-Drug Interactions Prediction.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Drug-drug interaction (DDI) can trigger many adverse effects in patients and has emerged as a threat to medicine and public health. Therefore, it is important to predict potential drug interactions since it can provide combination strategies of drugs...
Multi-View Multiattention Graph Learning With Stack Deep Matrix Factorization for circRNA-Drug Sensitivity Association Identification.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Identifying circular RNA (circRNA)-drug sensitivity association (CDsA) is crucial for advancing drug development. As conducting traditional wet experiments for determining CDsA is costly and inefficient, calculation methods have already proven to be ...
Predicting miRNA-Disease Associations Based on Spectral Graph Transformer With Dynamic Attention and Regularization.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Extensive research indicates that microRNAs (miRNAs) play a crucial role in the analysis of complex human diseases. Recently, numerous methods utilizing graph neural networks have been developed to investigate the complex relationships between miRNAs...
Identifying Associations Between Small Nucleolar RNAs and Diseases via Graph Convolutional Network and Attention Mechanism.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Research has shown that small nucleolar RNAs (snoRNAs) play crucial roles in various biological processes, and understanding disease pathogenesis by studying their relationship with diseases is beneficial. Currently, known associations are insufficie...
Self-Supervised Pre-Training via Multi-View Graph Information Bottleneck for Molecular Property Prediction.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Molecular representation learning has remarkably accelerated the development of drug analysis and discovery. It implements machine learning methods to encode molecule embeddings for diverse downstream drug-related tasks. Due to the scarcity of labele...
Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.
Apoptosis : an international journal on programmed cell death
Dec 4, 2024
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...
Transformers significantly improve splice site prediction.
Communications biology
Dec 4, 2024
Mutations that affect RNA splicing significantly impact human diversity and disease. Here we present a method using transformers, a type of machine learning model, to detect splicing from raw 45,000-nucleotide sequences. We generate embeddings with r...
Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.
Frontiers in immunology
Dec 4, 2024
BACKGROUND: Low back pain resulting from intervertebral disc degeneration (IVDD) represents a significant global social problem. There are notable differences in the distribution of lymphatic vessels (LV) in normal and pathological intervertebral dis...
Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning.
Scientific reports
Dec 3, 2024
Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of...
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