Briefings in Bioinformatics

Article	Citations
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	734
Clustered tree regression to learn protein energy change with mutated amino acid	485
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	424
Ensemble learning based on matrix completion improves microbe-disease association prediction	406
STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance	389
Analysis of super-enhancer using machine learning and its application to medical biology	329
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	251
Hi-C3: a statistical inference-based model for reconstructing higher-order cell–cell communication networks	247
Phage quest: a beginner’s guide to explore viral diversity in the prokaryotic world	227
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	217
Computational refinement and multivalent engineering of complementarity-determining region-grafted nanobodies on a humanized scaffold for retaining antiviral efficacy	216
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	212
Computational model for ncRNA research	185
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	177
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	163
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	152
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	147
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	145
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	135
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	130
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	129
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	120
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	118
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	117
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	117

Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	116
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	112
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	112
Building multiscale models with PhysiBoSS, an agent-based modeling tool	108
A robust statistical approach for finding informative spatially associated pathways	106
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	106
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	105
A comprehensive benchmark of tools for efficient genomic interval querying	102
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	101
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	101
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	96
Computational analyses of bacterial strains from shotgun reads	95
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	94
Systematic evaluation of de novo mutation calling tools using whole genome sequencing data	94
FGeneBERT: function-driven pre-trained gene language model for metagenomics	92
DeepCheck: multitask learning aids in assessing microbial genome quality	90
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	90
Protein phosphorylation database and prediction tools	88
QTFPred: robust high-performance quantum machine learning modeling that predicts main and cooperative transcription factor bindings with base resolution	86
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	86
From intuition to AI: evolution of small molecule representations in drug discovery	85
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	85
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	84
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	84
Making PBPK models more reproducible in practice	83
Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior	83
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	81
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	81
Towards comprehensive benchmarking of medical vision language models	81
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	81
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	79
Attribute-guided prototype network for few-shot molecular property prediction	77
A review on the application of bioinformatics tools in food microbiome studies	77
Genome assembly and gene identification of biosurfactant-producing bacteria for environmental bioremediation	77
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	76
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	75
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	75
Deep learning in integrating spatial transcriptomics with other modalities	75
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	73
Detecting tipping points of complex diseases by network information entropy	73
Improving drug response prediction via integrating gene relationships with deep learning	72
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	72
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	72
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	70
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	68
Machine learning–augmented m6A-Seq analysis without a reference genome	68
Learning discriminative and structural samples for rare cell types with deep generative model	68
Large-scale predicting protein functions through heterogeneous feature fusion	67
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	67
A robust and scalable graph neural network for accurate single-cell classification	66

PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	65
Assessing protein model quality based on deep graph coupled networks using protein language model	65
Identification of vital chemical information via visualization of graph neural networks	65
Machine learning modeling of RNA structures: methods, challenges and future perspectives	64
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	64
AptaDiff: de novo design and optimization of aptamers based on diffusion models	64
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	63
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	63
ADENet: a novel network-based inference method for prediction of drug adverse events	63
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	62
PLMFit: benchmarking transfer learning with protein language models for protein engineering	62
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	62
Deciphering gene contributions and etiologies of somatic mutational signatures of cancer	61
Toward high-efficiency, low-resource, and explainable neuropeptide prediction with MSKDNP	61
Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data	61
Evaluating large language models for annotating proteins	61
A review of methods for predicting DNA N6-methyladenine sites	61
Multi-omics regulatory network inference in the presence of missing data	61
TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes	60
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions	60
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer	60
Inferring kinase–phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets	58
Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer – bioinformatics study for a potential link to MMEJ	58
HLA3D: an integrated structure-based computational toolkit for immunotherapy	58
Correction to: sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution	58
Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project	57
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches	57
Phylogenetic inference of inter-population transmission rates for infectious diseases	57
scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data	56
ConSIG: consistent discovery of molecular signature from OMIC data	55
BioWorkflow: Retrieving comprehensive bioinformatics workflows from publications	55
RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data	54
Estimation of non-equilibrium transition rate from gene expression data	54
Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review	54
TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool	54
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions	54
OmniDoublet: a method for doublet detection in multimodal single-cell sequencing data	53
ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA	53
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs	52
RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins	52
slORFfinder: a tool to detect open reading frames resulting from trans-splicing of spliced leader sequences	51
MiRNA–disease association prediction based on meta-paths	51
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach	51
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning	51
BETA: a comprehensive benchmark for computational drug–target prediction	50
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline	50
Multilevel superposition for deciphering the conformational variability of protein ensembles	50
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data	50
Capturing large genomic contexts for accurately predicting enhancer-promoter interactions	50
Construct a variable-length fragment library for de novo protein structure prediction	50
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis	49
CHAI: consensus clustering through similarity matrix integration for cell-type identification	49
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	49
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference	49
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder	49
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN	49
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data	48
scAED: a framework for mapping the enhancer state at single-cell resolution	48
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity	48
BatchDTA: implicit batch alignment enhances deep learning-based drug–target affinity estimation	48
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers	48
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems	48
Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism	47
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction	47
A novel approach to study multi-domain motions in JAK1’s activation mechanism based on energy landscape	47
Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis	46
dSCOPE: a software to detect sequences critical for liquid–liquid phase separation	46
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information	46
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning	46
AI-guided discovery and optimization of antimicrobial peptides through species-aware language model	46
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature	46
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection	45
Drug repositioning based on weighted local information augmented graph neural network	45
scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning	45
Efficient prediction of peptide self-assembly through sequential and graphical encoding	45
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses	45
AI-assisted patient matching for personalized cancer medicine	44
IEPAPI: a method for immune epitope prediction by incorporating antigen presentation and immunogenicity	44
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis	44
Structure-enhanced deep learning accelerates aptamer selection for small molecule families like steroids	44

A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes	44
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes	44
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation	44
Component puzzle protein–protein interaction prediction	44
Metatranscriptomic analysis uncovers microbial and immune signatures underlying COVID-19 severity	43
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis	43
PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network	43
Correction to: Computational toxicology in drug discovery: applications of artificial intelligence in ADMET and toxicity prediction	43
Comparative epigenome analysis using Infinium DNA methylation BeadChips	43
Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors	42
TCM-navigator, a deep learning-based workflow for generation and evaluation of traditional Chinese medicine-like compounds for drug development	42
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level	42
Nativeness-constrained diffusion framework for nanobody design	42
AnnoAgent: a language agent for single-cell automatic annotation	42
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization	42
MSF-CPMP: a novel multi-source feature fusion model for prediction of cyclic peptide membrane permeability	42
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders	42
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization	42
A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology	41
LRcell : detecting the source of differential expression at the sub–cell-type level from bulk RNA-seq data	41
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants	41
Deep learning in structural bioinformatics: current applications and future perspectives	41
Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era	41
Correction to: PHR-search: a search framework for protein remote homology detection based on the predicted protein hierarchical relationships	40
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets	40
Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model	40
iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution	40
Learning genotype–phenotype associations from gaps in multi-species sequence alignments	40
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data	40
EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species	40
Mapping cancer heterogeneity: a consensus network approach to subtypes and pathways	39
NSCGRN: a network structure control method for gene regulatory network inference	39
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction	39
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism	39
Identify potential drug candidates within a high-quality compound search space	39
Circling in on plasmids: benchmarking plasmid detection and reconstruction tools for short-read data from diverse species	39
PepTCR-Net: prediction of multi-class antigen peptides by T-cell receptor sequences with deep learning	39
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction	39
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network	39
MegSite: an accurate nucleic acid-binding residue prediction method based on multimodal protein language model	39
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy	39
Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network	38
CRISP: a deep learning architecture for GC × GC–TOFMS contour ROI identification, simulation and analysis in imaging metabolomics	38
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep	38
Improved prediction of DNA and RNA binding proteins with deep learning models	37
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering	37
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data	37
Few-shot drug synergy prediction via rapid cross-tier adaptation meta-optimization	37
Current computational tools for protein lysine acylation site prediction	37
Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations	37
Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations	37
graphB3—an interpretable graph learning approach for predicting blood–brain barrier permeability	37
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares	37
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference	37
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire	36
ComABAN: refining molecular representation with the graph attention mechanism to accelerate drug discovery	36
Differentially expressed genes prediction by multiple self-attention on epigenetics data	36
Transfer learning of clinical outcomes from preclinical molecular data, principles and perspectives	36
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets	36
An efficient curriculum learning-based strategy for molecular graph learning	36
Machine learning-assisted substrate binding pocket engineering based on structural information	36
SAM-DTA: a sequence-agnostic model for drug–target binding affinity prediction	36
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53	36
An automatic immunofluorescence pattern classification framework for HEp-2 image based on supervised learning	36
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer	35
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective	35
Benchmarking genome assembly methods on metagenomic sequencing data	35
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis	35
Disrupting explicit encoding paradigms: property-interactive transformers decode T-cell receptor specificity beyond dataset biases	35
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits	35
ST-GCP: a graph convolutional network model with contrastive consistency and permutation for spatial transcriptomics	35
Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models	35
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes	35
Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform	35
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis	35
Cross-RNA transferable sequence representation learning for lncRNA m6A site detection via novel deep domain separation networks	35
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review	35
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model	35
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data	34
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	34
siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis	34
Bioinformatics toolbox for exploring target mutation-induced drug resistance	34
Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion	34
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	34
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction	34
GiGs: graph-based integrated Gaussian kernel similarity for virus–drug association prediction	34
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering	33
Uncovering allosteric communication in cancer-related histone mutations	33
MGEGFP: a multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN	33
Causal Temporal Diffusion Networks for Drug Repurposing in Epilepsy	33
PPRS-ID: Indonesian-adjusted partitioned PRS for type 2 diabetes using obesity PRS integration and west Javanese population LD mapping	33
A tool for feature extraction from biological sequences	33
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer	33
EGRET: edge aggregated graph attention networks and transfer learning improve protein–protein interaction site prediction	33
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics	33