4.7 Article

GCN-GENE: A novel method for prediction of coronary heart disease-related genes

Related references

Note: Only part of the references are listed.
Article Biochemical Research Methods

NmRF: identification of multispecies RNA 2′-O-methylation modification sites from RNA sequences

Chunyan Ao et al.

Summary: This study developed a predictor based on machine learning to identify 2'-O-methylation modification sites in RNA. The predictor showed high efficiency and accuracy in identifying modification sites across multiple species, outperforming existing tools.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biochemical Research Methods

POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability

Fengcheng Li et al.

Summary: Mass spectrometry-based proteomic technique is essential in studying biological processes. However, current statistical frameworks neglect the reproducibility among identified features. Thus, developing a tool to identify reproducible and generalizable proteomic signatures is crucial.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biology

Non-contact screening system based for COVID-19 on XGBoost and logistic regression

Chunjiao Dong et al.

Summary: This study aims to apply machine learning and non-contact monitoring system to automatically screen potential COVID-19 patients. The results show that the XGBoost + LR algorithm performs excellently in classification, and some sleep parameters are important features for classification.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

Article Biology

Machine learning-based prediction of drug and ligand binding in BCL-2 variants through molecular dynamics

John R. Hamre et al.

Summary: Replica exchange molecular dynamics (REMD) simulations combined with machine learning were used to predict mechanisms of Venetoclax resistance caused by BCL-2 protein variants. Shifts in variant structures contribute to drug resistance, and a prediction method was established elucidating the structure-function relationship.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

Article Biochemistry & Molecular Biology

Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique

Hasan Zulfiqar et al.

Summary: The study aimed to establish a robust deep learning model to recognize 4mC sites in Geobacter pickeringii. By using different feature descriptors and optimization algorithms, the accuracy of the model was improved.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2022)

Article Biochemical Research Methods

Optimization of metabolomic data processing using NOREVA

Jianbo Fu et al.

Summary: A peak table is a typical output of metabolomic experiments, and its processing is crucial in metabolomics research. The NOREVA protocol, a newly developed software tool, evaluates and optimizes data processing through various workflows, making data processing more efficient.

NATURE PROTOCOLS (2022)

Article Biochemistry & Molecular Biology

VARIDT 2.0: structural variability of drug transporter

Tingting Fu et al.

Summary: This study describes a major update of the VARIDT database, including experimental resolved structures and structural variability data updates through literature review and homology modeling. The newly collected data are essential for explaining drug sensitivity, revealing drug-drug interaction mechanisms, and more.

NUCLEIC ACIDS RESEARCH (2022)

Article Biology

PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods

Weiqi Xia et al.

Summary: This study presents a novel protein function annotation strategy, PFmulDL, which integrates multiple deep learning methods to address the limitations of existing methods in annotating proteins in "rare classes". The new model is capable of annotating a larger number of protein families and significantly improving prediction performance.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

Article Biochemical Research Methods

Identifying drug-target interactions based on graph convolutional network and deep neural network

Tianyi Zhao et al.

Summary: In order to improve the identification of DTIs, a DPP network was established and a novel learning framework GCN-DTI was proposed. The method utilizes graph convolutional networks to learn DPP features and deep neural networks to predict final DTI labels, outperforming existing approaches significantly.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Deep-DRM: a computational method for identifying disease-related metabolites based on graph deep learning approaches

Tianyi Zhao et al.

Summary: This study introduces a graph deep learning method, Deep-DRM, for identifying diseases-related metabolites. By calculating the similarities between metabolites and diseases, building networks, and applying a deep neural network, Deep-DRM shows outstanding performance in identifying true metabolite-disease pairs.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemistry & Molecular Biology

SC2disease: a manually curated database of single-cell transcriptome for human diseases

Tianyi Zhao et al.

Summary: SC2disease is a manually curated database aiming to provide a comprehensive and accurate resource of gene expression profiles in various cell types for different diseases. It documents comparisons of differentially expressed genes between different cell types, tissues, and disease-related health status, offering new possibilities to address biological and medical questions. The database also reanalyzes gene expression matrix by a unified pipeline to improve comparability between different studies and compares cell-type-specific genes with corresponding genes of lead SNPs identified in GWAS for trait specificity implications.

NUCLEIC ACIDS RESEARCH (2021)

Review Biotechnology & Applied Microbiology

Prediction of bio-sequence modifications and the associations with diseases

Chunyan Ao et al.

Summary: This review comprehensively summarizes the predictors for protein, RNA, and DNA modification sites and their association with diseases, emphasizing the importance of accurately identifying and understanding modification sites for disease research.

BRIEFINGS IN FUNCTIONAL GENOMICS (2021)

Article Biochemical Research Methods

Chemical Genetic Validation of GWAS-derived Disease Loci

Yuan Quan et al.

Summary: Utilizing chemical genetics information to validate GWAS-derived disease loci and interpret their underlying pathogenesis through comparative analysis, this study identified numerous loci associated with drug target genes, disease traits, and drug indications. More than 40% of genes were recognized as disorder factors, highlighting the potential power of chemical genetic validation. Inferences about the pathogenesis of these loci were made based on the corresponding drug mode of action, suggesting important implications for not only medical genetics but also the evaluation of GWAS methodology.

CURRENT BIOINFORMATICS (2021)

Article Biochemical Research Methods

MDAPlatform: A Component-based Platform for Constructing and Assessing miRNA-disease Association Prediction Methods

Yayan Zhang et al.

Summary: The study developed an easy-to-use platform called MDAPlatform for constructing and evaluating miRNA-disease association prediction methods. Users can conduct cross-validation experiments and compare their methods with others using this platform, with visualized results provided.

CURRENT BIOINFORMATICS (2021)

Article Biology

Disease type detection in lung and colon cancer images using the complement approach of inefficient sets

Mesut Togacar

Summary: The study utilized an artificial intelligence-supported model and optimization methods to classify lung and colon cancers' histopathological images, achieving a 99.69% overall accuracy rate by training image classes with the DarkNet-19 model, selecting efficient features using Equilibrium and Manta Ray Foraging optimization algorithms, and combining these features with the Support Vector Machine (SVM) method.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Review Biology

A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach

Mei Sze Tan et al.

Summary: Alzheimer's Disease is a common neurodegenerative disease affecting cognition, with increasing incidence as the elderly population grows. Diagnosis is based on clinical criteria including patient history, physical examination, neuropsychological testing and appropriate investigations. Omics techniques may aid in diagnosis and exploration of disease development mechanisms.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Biochemical Research Methods

An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction

Jiajie Peng et al.

Summary: This paper proposes an end-to-end learning framework based on heterogeneous graph convolutional networks for drug-target interactions (DTI) prediction, named end-to-end graph (EEG)-DTI. The framework learns the feature representations of drugs and targets during training, and outperforms existing methods in DTI prediction.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Prediction and collection of protein-metabolite interactions

Tianyi Zhao et al.

Summary: PMI-DB is a freely accessible, comprehensive and accurate resource of PMIs, providing non-interaction samples and supporting deep learning prediction of PMIs, which helps reduce experimental costs and facilitates the construction of more accurate algorithms.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Prediction of Microbe-drug Associations Based on Chemical Structures and the KATZ Measure

Lingzhi Zhu et al.

Summary: The study introduces a computational model, HMDAKATZ, for identifying potential human microbe-drug associations. Experimental results show that HMDAKATZ outperforms four other computational models in various cross-validation methods. Case studies also demonstrate that HMDAKATZ is an effective way to discover hidden microbe-drug associations.

CURRENT BIOINFORMATICS (2021)

Article Computer Science, Artificial Intelligence

Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators

Hui Yang et al.

Summary: The study designed a computational system to predict diabetes risk by combining various types of physical examination data. Statistical analysis was conducted on different physical examination indexes to develop a model that can distinguish diabetes patients from healthy individuals. A diabetes risk scorecard was established to improve the convenience and flexibility of the model. Lastly, an online diabetes risk assessment system was set up to enhance diabetes cascade screening and personal lifestyle management.

INFORMATION FUSION (2021)

Article Biochemistry & Molecular Biology

Netrin-1 in Atherosclerosis: Relationship between Human Macrophage Intracellular Levels and In Vivo Plaque Morphology

Susanna Fiorelli et al.

Summary: Netrin-1 and its receptor UNC5b play critical roles in the atherosclerotic process, with significant differences in expression levels between CAD patients and control subjects. Their expression levels are associated with plaque progression and stabilization.

BIOMEDICINES (2021)

Article Biology

DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network

Cheng Chen et al.

Summary: The study introduces a novel method DNN-DTIs for predicting drug-target interactions, demonstrating superior accuracy compared to other predictors, especially suitable for drug repositioning research.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Biochemical Research Methods

DeepLGP: a novel deep learning method for prioritizing lncRNA target genes

Tianyi Zhao et al.

BIOINFORMATICS (2020)

Review Genetics & Heredity

Artificial RNA Editing with ADAR for Gene Therapy

Sonali Bhakta et al.

CURRENT GENE THERAPY (2020)

Review Hematology

Periodontitis, coronary heart disease and myocardial infarction: treat one, benefit all

Riccardo Nocini et al.

BLOOD COAGULATION & FIBRINOLYSIS (2020)

Article Medicine, Research & Experimental

Proinflammatory cytokine IFN-γ, lncRNA BANCR and the occurrence of coronary artery disease

Hongli Wang et al.

LIFE SCIENCES (2019)

Article Biochemistry & Molecular Biology

HumanNet v2: human gene networks for disease research

Sohyun Hwang et al.

NUCLEIC ACIDS RESEARCH (2019)

Article Cardiac & Cardiovascular Systems

Genetics and Genomics of Congenital Heart Disease

Samir Zaidi et al.

CIRCULATION RESEARCH (2017)

Article Biochemistry & Molecular Biology

BioGPS: building your own mash-up of gene annotations and expression profiles

Chunlei Wu et al.

NUCLEIC ACIDS RESEARCH (2016)

Article Biochemistry & Molecular Biology

Long non-coding RNA ANRIL regulates inflammatory responses as a novel component of NF-κB pathway

Xiao Zhou et al.

RNA BIOLOGY (2016)

Article Biotechnology & Applied Microbiology

Association of polymorphisms in long non-coding RNA H19 with coronary artery disease risk in a Chinese population

Wei Gao et al.

MUTATION RESEARCH-FUNDAMENTAL AND MOLECULAR MECHANISMS OF MUTAGENESIS (2015)

Article Cardiac & Cardiovascular Systems

Polycystin-2 mutations lead to impaired calcium cycling in the heart and predispose to dilated cardiomyopathy

Jere Paavola et al.

JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY (2013)

Review Endocrinology & Metabolism

The metabolic syndrome - Prevalence, CHD risk, and treatment

C Sarti et al.

JOURNAL OF DIABETES AND ITS COMPLICATIONS (2006)

Article Genetics & Heredity

Identification of a novel non-coding RNA, MIAT, that confers risk of myocardial infarction

Nobuaki Ishii et al.

JOURNAL OF HUMAN GENETICS (2006)