Briefings in Bioinformatics

Article	Citations
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	653
Building multiscale models with PhysiBoSS, an agent-based modeling tool	427
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	368
Analysis of super-enhancer using machine learning and its application to medical biology	345
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	334
Large-scale predicting protein functions through heterogeneous feature fusion	311
A comprehensive benchmark of tools for efficient genomic interval querying	264
A robust and scalable graph neural network for accurate single-cell classification	233
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	226
Attribute-guided prototype network for few-shot molecular property prediction	220
Hi-C3: a statistical inference-based model for reconstructing higher-order cell–cell communication networks	212
PLMFit: benchmarking transfer learning with protein language models for protein engineering	207
Assessing protein model quality based on deep graph coupled networks using protein language model	199
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	189
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	175
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	162
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	162
Learning discriminative and structural samples for rare cell types with deep generative model	145
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	144
Improving drug response prediction via integrating gene relationships with deep learning	141
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	134
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	127
Machine learning modeling of RNA structures: methods, challenges and future perspectives	125
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	125
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	121

Phage quest: a beginner’s guide to explore viral diversity in the prokaryotic world	116
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	115
Computational refinement and multivalent engineering of complementarity-determining region-grafted nanobodies on a humanized scaffold for retaining antiviral efficacy	114
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	114
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	113
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	107
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	105
Computational analyses of bacterial strains from shotgun reads	105
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	103
Computational model for ncRNA research	103
Machine learning–augmented m6A-Seq analysis without a reference genome	101
Evaluating large language models for annotating proteins	100
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	99
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	98
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	97
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	94
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	93
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	93
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	92
Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	89
Combining power of different methods to detect associations in large data sets	88
DeepCheck: multitask learning aids in assessing microbial genome quality	87
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	87
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	86
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	85
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	84
A robust statistical approach for finding informative spatially associated pathways	82
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	81
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	80
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	80
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	79
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	79
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	77
Making PBPK models more reproducible in practice	76
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	76
Protein phosphorylation database and prediction tools	76
ADENet: a novel network-based inference method for prediction of drug adverse events	75
Detecting tipping points of complex diseases by network information entropy	75
Distant metastasis identification based on optimized graph representation of gene interaction patterns	74
AptaDiff: de novo design and optimization of aptamers based on diffusion models	73
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	73
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	72
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	72
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	72
From intuition to AI: evolution of small molecule representations in drug discovery	71
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	71
Clustered tree regression to learn protein energy change with mutated amino acid	71
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	70
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	70
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	69

Ensemble learning based on matrix completion improves microbe-disease association prediction	68
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	67
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	67
Deep learning in integrating spatial transcriptomics with other modalities	66
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	66
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	66
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	66
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	65
STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance	65
Identification of vital chemical information via visualization of graph neural networks	65
A review on the application of bioinformatics tools in food microbiome studies	65
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data	64
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder	64
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity	62
Toward high-efficiency, low-resource, and explainable neuropeptide prediction with MSKDNP	62
CHAI: consensus clustering through similarity matrix integration for cell-type identification	62
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs	61
Multi-omics regulatory network inference in the presence of missing data	60
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation	60
Deciphering gene contributions and etiologies of somatic mutational signatures of cancer	60
Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data	60
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline	60
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction	60
A review of methods for predicting DNA N6-methyladenine sites	60
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer	59
TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes	59
Multilevel superposition for deciphering the conformational variability of protein ensembles	58
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions	58
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data	57
BatchDTA: implicit batch alignment enhances deep learning-based drug–target affinity estimation	57
HLA3D: an integrated structure-based computational toolkit for immunotherapy	57
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers	57
Correction to: sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution	56
Phylogenetic inference of inter-population transmission rates for infectious diseases	56
Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer – bioinformatics study for a potential link to MMEJ	56
Inferring kinase–phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets	56
scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data	55
RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data	55
Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project	55
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches	55
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems	55
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference	55
TCM-navigator, a deep learning-based workflow for generation and evaluation of traditional Chinese medicine-like compounds for drug development	54
miRPreM and tiRPreM: Improved methodologies for the prediction of miRNAs and tRNA-induced small non-coding RNAs for model and non-model organisms	54
slORFfinder: a tool to detect open reading frames resulting from trans-splicing of spliced leader sequences	54
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes	54
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach	54
MiRNA–disease association prediction based on meta-paths	53
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions	53
BETA: a comprehensive benchmark for computational drug–target prediction	53
Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review	52
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning	52
Estimation of non-equilibrium transition rate from gene expression data	52
A novel approach to study multi-domain motions in JAK1’s activation mechanism based on energy landscape	52
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis	52
Drug repositioning based on weighted local information augmented graph neural network	52
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	51
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders	51
Capturing large genomic contexts for accurately predicting enhancer-promoter interactions	51
AI-guided discovery and optimization of antimicrobial peptides through species-aware language model	51
LRcell: detecting the source of differential expression at the sub–cell-type level from bulk RNA-seq data	51
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level	50
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN	50
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis	50
Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era	49
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization	49
Efficient prediction of peptide self-assembly through sequential and graphical encoding	48
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization	48
PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network	48
IEPAPI: a method for immune epitope prediction by incorporating antigen presentation and immunogenicity	47
OmniDoublet: a method for doublet detection in multimodal single-cell sequencing data	47
A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology	47
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis	47
Comparative epigenome analysis using Infinium DNA methylation BeadChips	46
Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis	46
Construct a variable-length fragment library for de novo protein structure prediction	46
A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes	46
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information	46
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature	45
ConSIG: consistent discovery of molecular signature from OMIC data	45

Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism	45
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses	45
RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins	45
dSCOPE: a software to detect sequences critical for liquid–liquid phase separation	45
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection	45
scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning	45
ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA	45
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning	44
Differentially expressed genes prediction by multiple self-attention on epigenetics data	43
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants	43
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets	43
Machine learning-assisted substrate binding pocket engineering based on structural information	43
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data	43
Correction to: PHR-search: a search framework for protein remote homology detection based on the predicted protein hierarchical relationships	43
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer	43
Deep learning in structural bioinformatics: current applications and future perspectives	43
Bioinformatics toolbox for exploring target mutation-induced drug resistance	42
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data	42
iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution	42
Learning genotype–phenotype associations from gaps in multi-species sequence alignments	41
Mapping cancer heterogeneity: a consensus network approach to subtypes and pathways	41
EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species	41
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction	41
AMDBNorm: an approach based on distribution adjustment to eliminate batch effects of gene expression data	41
Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model	41
Improved prediction of DNA and RNA binding proteins with deep learning models	41
Benchmarking genome assembly methods on metagenomic sequencing data	40
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model	40
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering	40
Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph Contrastive Learning	40
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy	40
GiGs: graph-based integrated Gaussian kernel similarity for virus–drug association prediction	40
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits	40
CRISP: a deep learning architecture for GC × GC–TOFMS contour ROI identification, simulation and analysis in imaging metabolomics	40
PepTCR-Net: prediction of multi-class antigen peptides by T-cell receptor sequences with deep learning	40
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction	40
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism	40
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes	40
A parameter-free deep embedded clustering method for single-cell RNA-seq data	39
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer	39
Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models	39
MegSite: an accurate nucleic acid-binding residue prediction method based on multimodal protein language model	39
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets	39
DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network	38
Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network	38
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction	38
Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity	38
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	38
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review	38
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network	38
Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform	38
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep	37
Transfer learning of clinical outcomes from preclinical molecular data, principles and perspectives	37
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53	37
Current computational tools for protein lysine acylation site prediction	37
The landscape of the methodology in drug repurposing using human genomic data: a systematic review	37
A tool for feature extraction from biological sequences	37
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering	37
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire	36
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics	36
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data	36
A deep learning method for predicting metabolite–disease associations via graph neural network	36
Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations	36
An automatic immunofluorescence pattern classification framework for HEp-2 image based on supervised learning	36
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	36
MGEGFP: a multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN	36
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis	36
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference	36
ComABAN: refining molecular representation with the graph attention mechanism to accelerate drug discovery	36
An efficient curriculum learning-based strategy for molecular graph learning	36
NSCGRN: a network structure control method for gene regulatory network inference	35
SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission	35
SAM-DTA: a sequence-agnostic model for drug–target binding affinity prediction	35
Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion	35
Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies	35
Identify potential drug candidates within a high-quality compound search space	35
toxCSM: comprehensive prediction of small molecule toxicity profiles	35
HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks	34
scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data	34
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis	34
Advancing edge-based clustering and graph embedding for biological network analysis: a case study in RASopathies	34
EGRET: edge aggregated graph attention networks and transfer learning improve protein–protein interaction site prediction	34
siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis	34
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares	33
Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations	33
HiC4D: forecasting spatiotemporal Hi-C data with residual ConvLSTM	33
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective	33
GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels	33
GAEDGRN: reconstruction of gene regulatory networks based on gravity-inspired graph autoencoders	33
Multimodal deep learning for biomedical data fusion: a review	33
Research progress of miRNA–disease association prediction and comparison of related algorithms	33
Benchmarking large language models for genomic knowledge with GeneTuring	33
scDeconv: an R package to deconvolve bulk DNA methylation data with scRNA-seq data and paired bulk RNA–DNA methylation data	32
Ontology-aware neural network: a general framework for pattern mining from microbiome data	32
emPDBA: protein-DNA binding affinity prediction by combining features from binding partners and interface learned with ensemble regression model	32