Briefings in Bioinformatics

Article	Citations
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	897
STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance	535
Analysis of super-enhancer using machine learning and its application to medical biology	534
Hi-C3: a statistical inference-based model for reconstructing higher-order cell–cell communication networks	461
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	347
Protein phosphorylation database and prediction tools	299
Multi-marker testing based on accelerated failure time models under possible left truncation and competing risks	286
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	242
Improving drug response prediction via integrating gene relationships with deep learning	239
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	229
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	213
FGeneBERT: function-driven pre-trained gene language model for metagenomics	209
Stoichiometry-preserving and stochasticity-aware identification of m6A from direct RNA sequencing	199
Deep learning in integrating spatial transcriptomics with other modalities	178
Learning discriminative and structural samples for rare cell types with deep generative model	176
Assessing protein model quality based on deep graph coupled networks using protein language model	151
Phage quest: a beginner’s guide to explore viral diversity in the prokaryotic world	151
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	136
Computational model for ncRNA research	131
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	127
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	126
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	123
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	121
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	117
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	111

Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	109
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	107
Attribute-guided prototype network for few-shot molecular property prediction	106
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	106
Large-scale predicting protein functions through heterogeneous feature fusion	103
Evaluating large language models for annotating proteins	102
AICellType: a large language model-based platform for accurate cell type annotation	102
PLMFit: benchmarking transfer learning with protein language models for protein engineering	101
Clustered tree regression to learn protein energy change with mutated amino acid	97
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	97
From intuition to AI: evolution of small molecule representations in drug discovery	96
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	94
Building multiscale models with PhysiBoSS, an agent-based modeling tool	94
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	92
Computational refinement and multivalent engineering of complementarity-determining region-grafted nanobodies on a humanized scaffold for retaining antiviral efficacy	91
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	91
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	90
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	89
AptaDiff: de novo design and optimization of aptamers based on diffusion models	89
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	87
Machine learning modeling of RNA structures: methods, challenges and future perspectives	86
Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	86
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	85
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	85
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	85
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	83
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	83
DeepCheck: multitask learning aids in assessing microbial genome quality	81
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	81
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	78
A comprehensive benchmark of tools for efficient genomic interval querying	78
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	78
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	77
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	77
Systematic evaluation of de novo mutation calling tools using whole genome sequencing data	76
Machine learning–augmented m6A-Seq analysis without a reference genome	75
QTFPred: robust high-performance quantum machine learning modeling that predicts main and cooperative transcription factor bindings with base resolution	75
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	73
Predicting protein–carbohydrate binding sites: a deep learning approach integrating protein language model embeddings and structural features	72
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	72
GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis	72
Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior	71
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	71
Towards comprehensive benchmarking of medical vision language models	70
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	69
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	69
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	69
Genome assembly and gene identification of biosurfactant-producing bacteria for environmental bioremediation	68
Identification of vital chemical information via visualization of graph neural networks	68
Ensemble learning based on matrix completion improves microbe-disease association prediction	68

Detecting tipping points of complex diseases by network information entropy	68
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	68
Making PBPK models more reproducible in practice	67
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	67
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	66
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	65
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	64
A robust statistical approach for finding informative spatially associated pathways	63
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	63
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	61
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	61
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	60
Deciphering gene contributions and etiologies of somatic mutational signatures of cancer	60
A review of methods for predicting DNA N6-methyladenine sites	60
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder	59
Correction to: sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution	59
Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer – bioinformatics study for a potential link to MMEJ	59
TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes	59
Inferring kinase–phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets	59
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis	58
TCM-navigator, a deep learning-based workflow for generation and evaluation of traditional Chinese medicine-like compounds for drug development	58
AI-assisted patient matching for personalized cancer medicine	56
scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data	56
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level	56
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction	56
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization	56
A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes	56
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline	56
Correction to: Computational toxicology in drug discovery: applications of artificial intelligence in ADMET and toxicity prediction	56
ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA	56
Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data	55
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data	55
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	55
A novel approach to study multi-domain motions in JAK1’s activation mechanism based on energy landscape	55
BatchDTA: implicit batch alignment enhances deep learning-based drug–target affinity estimation	55
BETA: a comprehensive benchmark for computational drug–target prediction	55
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference	54
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers	54
PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network	54
AI-guided discovery and optimization of antimicrobial peptides through species-aware language model	54
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches	54
Multilevel superposition for deciphering the conformational variability of protein ensembles	53
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information	53
Comparative epigenome analysis using Infinium DNA methylation BeadChips	53
slORFfinder: a tool to detect open reading frames resulting from trans-splicing of spliced leader sequences	53
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems	53
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection	52
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer	51
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization	51
BioWorkflow: Retrieving comprehensive bioinformatics workflows from publications	51
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data	51
ConSIG: consistent discovery of molecular signature from OMIC data	51
OmniDoublet: a method for doublet detection in multimodal single-cell sequencing data	50
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity	50
scAED: a framework for mapping the enhancer state at single-cell resolution	50
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs	50
Estimation of non-equilibrium transition rate from gene expression data	50
CHAI: consensus clustering through similarity matrix integration for cell-type identification	49
Nativeness-constrained diffusion framework for nanobody design	49
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes	49
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses	49
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation	49
Metatranscriptomic analysis uncovers microbial and immune signatures underlying COVID-19 severity	49
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions	48
AnnoAgent: a language agent for single-cell automatic annotation	48
Enhancing protein structure prediction: evaluating the role of amino acid physicochemical features in homology search	48
Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors	48
IEPAPI: a method for immune epitope prediction by incorporating antigen presentation and immunogenicity	48
MSF-CPMP: a novel multi-source feature fusion model for prediction of cyclic peptide membrane permeability	48
Phylogenetic inference of inter-population transmission rates for infectious diseases	47
Towards accurate artificial intelligence models for strain-level phage–host prediction	47
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach	47
PGVDA: a pathway-aggregated genetic dosage framework for interpretable disease classification using machine learning	47
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN	47
Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism	47
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature	47
Estimating population structure using epigenome-wide methylation data	46
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning	46
scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning	46
Multi-omics regulatory network inference in the presence of missing data	46

SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning	46
Component puzzle protein–protein interaction prediction	46
TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool	45
Toward high-efficiency, low-resource, and explainable neuropeptide prediction with MSKDNP	45
dSCOPE: a software to detect sequences critical for liquid–liquid phase separation	45
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis	45
Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review	45
Quantifying transcript complexity via the condition number of gene-specific random matrix	45
Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project	45
Efficient prediction of peptide self-assembly through sequential and graphical encoding	44
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions	44
Deep learning in structural bioinformatics: current applications and future perspectives	43
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis	43
Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era	43
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders	43
A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology	43
Structure-enhanced deep learning accelerates aptamer selection for small molecule families like steroids	43
RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins	43
Drug repositioning based on weighted local information augmented graph neural network	42
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data	41
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction	41
Mapping cancer heterogeneity: a consensus network approach to subtypes and pathways	41
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants	41
Learning genotype–phenotype associations from gaps in multi-species sequence alignments	41
EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species	41
iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution	41
Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model	41
PepTCR-Net: prediction of multi-class antigen peptides by T-cell receptor sequences with deep learning	40
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference	40
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering	40
Current computational tools for protein lysine acylation site prediction	40
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction	40
Bioinformatics toolbox for exploring target mutation-induced drug resistance	40
graphB3—an interpretable graph learning approach for predicting blood–brain barrier permeability	40
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy	40
Cross-RNA transferable sequence representation learning for lncRNA m6A site detection via novel deep domain separation networks	40
Advancing edge-based clustering and graph embedding for biological network analysis: a case study in RASopathies	40
SAM-DTA: a sequence-agnostic model for drug–target binding affinity prediction	40
Causal Temporal Diffusion Networks for Drug Repurposing in Epilepsy	39
Toward next-generation machine learning and deep learning for spatial omics	39
Improved prediction of DNA and RNA binding proteins with deep learning models	39
Benchmarking genome assembly methods on metagenomic sequencing data	39
Identify potential drug candidates within a high-quality compound search space	39
ComABAN: refining molecular representation with the graph attention mechanism to accelerate drug discovery	39
Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion	39
Circling in on plasmids: benchmarking plasmid detection and reconstruction tools for short-read data from diverse species	39
A parameter-free deep embedded clustering method for single-cell RNA-seq data	39
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review	39
Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform	39
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction	39
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis	39
The landscape of the methodology in drug repurposing using human genomic data: a systematic review	39
MegSite: an accurate nucleic acid-binding residue prediction method based on multimodal protein language model	39
GiGs: graph-based integrated Gaussian kernel similarity for virus–drug association prediction	38
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	38
DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network	38
Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations	38
Uncovering allosteric communication in cancer-related histone mutations	38
Disrupting explicit encoding paradigms: property-interactive transformers decode T-cell receptor specificity beyond dataset biases	38
Few-shot drug synergy prediction via rapid cross-tier adaptation meta-optimization	38
Towards Comprehensive Benchmarking of Medical Vision Language Models	38
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep	38
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer	38
PPRS-ID: Indonesian-adjusted partitioned PRS for type 2 diabetes using obesity PRS integration and west Javanese population LD mapping	38
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets	38
Deciphering hierarchical regulatory network of cell fate via an epigenetics-informed heterogeneous graph transformer on single-cell multi-omics data	38
Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations	37
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire	37
MGEGFP: a multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN	37
Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity	37
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares	37
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective	37
Master of Metals2: a graph neural network based architecture for the prediction of zinc binding sites in protein structures	37
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics	36
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes	36
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model	36
Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network	35
Could statistical potential models achieve comparable or better performance than deep learning models?	35
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer	35
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data	35
ST-GCP: a graph convolutional network model with contrastive consistency and permutation for spatial transcriptomics	35
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism	35
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network	35
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	35
NSCGRN: a network structure control method for gene regulatory network inference	35
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering	35
Machine learning-assisted substrate binding pocket engineering based on structural information	35
toxCSM: comprehensive prediction of small molecule toxicity profiles	35
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets	34
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data	34
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits	34
ClusterX: a novel representation learning-based deep clustering framework for accurate visual inspection in virtual screening	34
Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision	34
An automatic immunofluorescence pattern classification framework for HEp-2 image based on supervised learning	34
Correction to: Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	34