Briefings in Bioinformatics

Article	Citations
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	1044
Corrigendum to: Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein	487
Knowledge bases and software support for variant interpretation in precision oncology	337
Computational model for ncRNA research	264
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	230
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	208
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	201
DeepCheck: multitask learning aids in assessing microbial genome quality	201
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	190
Genome sequencing data analysis for rare disease gene discovery	188
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	183
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	178
Defining the functional divergence of orthologous genes between human and mouse in the context of miRNA regulation	178
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	168
Combining power of different methods to detect associations in large data sets	163
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	149
Clustered tree regression to learn protein energy change with mutated amino acid	146
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	139
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	133
Attribute-guided prototype network for few-shot molecular property prediction	128
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	125
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	124
Distant metastasis identification based on optimized graph representation of gene interaction patterns	123
Computational analyses of bacterial strains from shotgun reads	120
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	117

mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	115
A robust statistical approach for finding informative spatially associated pathways	112
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	110
AptaDiff: de novo design and optimization of aptamers based on diffusion models	104
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	103
Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations	101
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	100
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	100
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	98
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	97
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	96
Building multiscale models with PhysiBoSS, an agent-based modeling tool	95
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	94
ADENet: a novel network-based inference method for prediction of drug adverse events	92
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	92
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	91
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	91
Circular RNAs and complex diseases: from experimental results to computational models	89
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	88
Making PBPK models more reproducible in practice	87
Comparative analysis of molecular fingerprints in prediction of drug combination effects	84
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	84
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	84
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	83
Machine learning modeling of RNA structures: methods, challenges and future perspectives	82
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	81
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	80
Analysis of super-enhancer using machine learning and its application to medical biology	80
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	78
Assessing protein model quality based on deep graph coupled networks using protein language model	78
Identification of vital chemical information via visualization of graph neural networks	78
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	77
A robust and scalable graph neural network for accurate single-cell classification	76
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	76
Ensemble learning based on matrix completion improves microbe-disease association prediction	76
Protein phosphorylation database and prediction tools	75
Large-scale predicting protein functions through heterogeneous feature fusion	75
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	75
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	74
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	74
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	73
Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution	73
Deep learning in integrating spatial transcriptomics with other modalities	72
Mol2Context-vec: learning molecular representation from context awareness for drug discovery	71
Learning discriminative and structural samples for rare cell types with deep generative model	71
ADEIP: an integrated platform of age-dependent expression and immune profiles across human tissues	70
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	69
Improving drug response prediction via integrating gene relationships with deep learning	69
Evaluating large language models for annotating proteins	68
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	68

Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	68
Machine learning–augmented m6A-Seq analysis without a reference genome	67
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	67
Detecting tipping points of complex diseases by network information entropy	67
Machine learning methods, databases and tools for drug combination prediction	66
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	66
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	66
From intuition to AI: evolution of small molecule representations in drug discovery	65
A review on the application of bioinformatics tools in food microbiome studies	65
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	64
Correction to: sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution	64
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation	64
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	64
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches	63
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions	63
BatchDTA: implicit batch alignment enhances deep learning-based drug–target affinity estimation	63
Published anti-SARS-CoV-2 in vitro hits share common mechanisms of action that synergize with antivirals	61
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers	61
RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data	61
Inferring kinase–phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets	61
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma	61
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis	61
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference	60
Capturing large genomic contexts for accurately predicting enhancer-promoter interactions	60
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning	60
ConSIG: consistent discovery of molecular signature from OMIC data	60
slORFfinder: a tool to detect open reading frames resulting from trans-splicing of spliced leader sequences	59
LRcell: detecting the source of differential expression at the sub–cell-type level from bulk RNA-seq data	59
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis	59
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses	59
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders	59
Distinct effect of prenatal and postnatal brain expression across 20 brain disorders and anthropometric social traits: a systematic study of spatiotemporal modularity	58
Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer – bioinformatics study for a potential link to MMEJ	57
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions	57
Multi-omics regulatory network inference in the presence of missing data	57
Estimation of non-equilibrium transition rate from gene expression data	57
miRPreM and tiRPreM: Improved methodologies for the prediction of miRNAs and tRNA-induced small non-coding RNAs for model and non-model organisms	56
Phylogenetic inference of inter-population transmission rates for infectious diseases	56
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity	56
Addressing data imbalance problems in ligand-binding site prediction using a variational autoencoder and a convolutional neural network	55
TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes	55
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs	55
Construct a variable-length fragment library for de novo protein structure prediction	54
Detecting methylation quantitative trait loci using a methylation random field method	53
Deciphering gene contributions and etiologies of somatic mutational signatures of cancer	53
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data	53
HLA3D: an integrated structure-based computational toolkit for immunotherapy	53
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data	52
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline	51
Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism	51
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature	51
Optimizing genomic control in mixed model associations with binary diseases	51
A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology	51
scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data	51
A review of methods for predicting DNA N6-methyladenine sites	51
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes	50
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems	50
RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins	50
A novel approach to study multi-domain motions in JAK1’s activation mechanism based on energy landscape	49
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning	49
MiRNA–disease association prediction based on meta-paths	49
dSCOPE: a software to detect sequences critical for liquid–liquid phase separation	49
ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA	48
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization	48
Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis	48
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information	48
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer	47
IEPAPI: a method for immune epitope prediction by incorporating antigen presentation and immunogenicity	47
A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes	47
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN	47
BETA: a comprehensive benchmark for computational drug–target prediction	47
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis	47
Development of interactive biological web applications with R/Shiny	47
Comparative epigenome analysis using Infinium DNA methylation BeadChips	46
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection	46
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder	46
Efficient prediction of peptide self-assembly through sequential and graphical encoding	46
PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network	46
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization	46
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach	46

scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning	45
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level	45
Multilevel superposition for deciphering the conformational variability of protein ensembles	45
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction	45
Drug repositioning based on weighted local information augmented graph neural network	45
Deep learning in structural bioinformatics: current applications and future perspectives	45
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis	44
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes	44
Differentially expressed genes prediction by multiple self-attention on epigenetics data	44
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer	43
SAM-DTA: a sequence-agnostic model for drug–target binding affinity prediction	43
Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform	43
Bioinformatics toolbox for exploring target mutation-induced drug resistance	43
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data	42
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis	42
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering	42
Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies	42
A tool for feature extraction from biological sequences	42
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction	41
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53	41
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	41
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism	41
Transfer learning of clinical outcomes from preclinical molecular data, principles and perspectives	41
ComABAN: refining molecular representation with the graph attention mechanism to accelerate drug discovery	41
An automatic immunofluorescence pattern classification framework for HEp-2 image based on supervised learning	41
NSCGRN: a network structure control method for gene regulatory network inference	41
GiGs: graph-based integrated Gaussian kernel similarity for virus–drug association prediction	41
MGEGFP: a multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN	41
Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model	40
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants	40
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data	40
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model	40
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer	40
Identify potential drug candidates within a high-quality compound search space	40
Learning genotype–phenotype associations from gaps in multi-species sequence alignments	40
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy	40
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets	40
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference	39
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	39
siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis	39
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets	39
Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations	39
Correction to: PHR-search: a search framework for protein remote homology detection based on the predicted protein hierarchical relationships	39
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep	39
EGRET: edge aggregated graph attention networks and transfer learning improve protein–protein interaction site prediction	38
AMDBNorm: an approach based on distribution adjustment to eliminate batch effects of gene expression data	38
HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks	38
Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity	38
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review	38
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data	38
DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network	38
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares	38
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network	37
Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion	37
Current computational tools for protein lysine acylation site prediction	37
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction	37
toxCSM: comprehensive prediction of small molecule toxicity profiles	37
DeepHost: phage host prediction with convolutional neural network	36
Benchmarking genome assembly methods on metagenomic sequencing data	36
Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models	36
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective	36
Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph Contrastive Learning	36
Machine learning-assisted substrate binding pocket engineering based on structural information	36
SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission	36
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits	35
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering	35
A parameter-free deep embedded clustering method for single-cell RNA-seq data	35
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics	35
Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations	35
The landscape of the methodology in drug repurposing using human genomic data: a systematic review	35
Molecular design in drug discovery: a comprehensive review of deep generative models	35
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire	34
An efficient curriculum learning-based strategy for molecular graph learning	34
Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network	34
Improved prediction of DNA and RNA binding proteins with deep learning models	34
CRISP: a deep learning architecture for GC × GC–TOFMS contour ROI identification, simulation and analysis in imaging metabolomics	34
A deep learning method for predicting metabolite–disease associations via graph neural network	33
Letter on the results of the BASiNET method in the paper ‘A systematic evaluation of computational tools for lncRNA identification’	33
Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics	33
Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision	33
iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution	33
GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels	33
Ontology-aware neural network: a general framework for pattern mining from microbiome data	33
Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation	33
Multimodal deep learning for biomedical data fusion: a review	33
Correction to: Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	33
Fine-grained selective similarity integration for drug–target interaction prediction	33
Computational models, databases and tools for antibiotic combinations	33
scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data	33
MiRAGE: mining relationships for advanced generative evaluation in drug repositioning	32
Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment	32
Timely need for navigating the potential and downsides of LLMs in healthcare and biomedicine	32
DKADE: a novel framework based on deep learning and knowledge graph for identifying adverse drug events and related medications	32
CMTT-JTracker: a fully test-time adaptive framework serving automated cell lineage construction	32
Spatially aligned graph transfer learning for characterizing spatial regulatory heterogeneity	32