Briefings in Bioinformatics

Article	Citations
Correction to: Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design	946
Towards molecular structure discovery from cryo-ET density volumes via modelling auxiliary semantic prototypes	445
Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences	304
BioGSF: a graph-driven semantic feature integration framework for biomedical relation extraction	229
Complex p53 dynamics regulated by miR-125b in cellular responses to reactive oxidative stress and DNA damage	189
Fast heritability estimation based on MINQUE and batch training	186
Correction to: Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison	181
scMitoMut for calling mitochondrial lineage-related mutations in single cells	180
DockEM: an enhanced method for atomic-scale protein–ligand docking refinement leveraging low-to-medium resolution cryo-EM density maps	173
VITALdb: to select the best viroinformatics tools for a desired virus or application	167
MAEST: accurately spatial domain detection in spatial transcriptomics with graph masked autoencoder	160
Benchmarking copy number aberrations inference tools using single-cell multi-omics datasets	152
Ensemble learning based on matrix completion improves microbe-disease association prediction	152
CSGDN: contrastive signed graph diffusion network for predicting crop gene–phenotype associations	149
spaCI: deciphering spatial cellular communications through adaptive graph model	146
Detecting tipping points of complex diseases by network information entropy	145
PharmBERT: a domain-specific BERT model for drug labels	137
Benchmarking methods for detecting differential states between conditions from multi-subject single-cell RNA-seq data	136
Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data	133
Integrated multi-omics with machine learning to uncover the intricacies of kidney disease	129
Circular RNAs and complex diseases: from experimental results to computational models	128
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	126
The hitchhikers’ guide to RNA sequencing and functional analysis	120
miProBERT: identification of microRNA promoters based on the pre-trained model BERT	115
Improving drug response prediction via integrating gene relationships with deep learning	115

Novel genetic insight for psoriasis: integrative genome-wide analyses in 863 080 individuals and proteome-wide Mendelian randomization	113
A comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions	111
Post-transcriptional regulation supports the homeostatic expression of mature RNA	105
A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction	104
DeepPFP: a multi-task-aware architecture for protein function prediction	104
Correction to: siGCD: a web server to explore survival interaction of genes, cells and drugs in human cancers	103
Corrigendum to: Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein	100
Knowledge bases and software support for variant interpretation in precision oncology	100
Potential of dissimilarity measure-based computation of protein thermal stability data for determining protein interactions	99
Deep reinforcement learning identifies personalized intermittent androgen deprivation therapy for prostate cancer	98
Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data	98
Statistical challenges in longitudinal microbiome data analysis	97
DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding	97
Positive-unlabeled learning in bioinformatics and computational biology: a brief review	96
preMLI: a pre-trained method to uncover microRNA–lncRNA potential interactions	95
Machine learning modeling of RNA structures: methods, challenges and future perspectives	93
Improved inter-protein contact prediction using dimensional hybrid residual networks and protein language models	92
Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations	90
CoraL: interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides	90
FireProt 2.0: web-based platform for the fully automated design of thermostable proteins	89
Refining computational inference of gene regulatory networks: integrating knockout data within a multi-task framework	88
Unveiling promising drug targets for autism spectrum disorder: insights from genetics, transcriptomics, and proteomics	86
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	85
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	85
Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies	84
HiCDiff: single-cell Hi-C data denoising with diffusion models	84
SSG-LUGIA: Single Sequence based Genome Level Unsupervised Genomic Island Prediction Algorithm	84
MHCBI: a pipeline for calculating peptide-MHC binding energy using semi-empirical quantum mechanical methods with explicit/implicit solvent models	80
Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design	80
Correction: Insights from analyses of low complexity regions with canonical methods for protein sequence comparison	79
Alignment-free estimation of sequence conservation for identifying functional sites using protein sequence embeddings	79
C-RCPred: a multi-objective algorithm for interactive secondary structure prediction of RNA complexes integrating user knowledge and SHAPE data	79
ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features	78
Integrating spatial transcriptomics and bulk RNA-seq: predicting gene expression with enhanced resolution through graph attention networks	78
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	78
RNMFLP: Predicting circRNA–disease associations based on robust nonnegative matrix factorization and label propagation	77
R2-DDI: relation-aware feature refinement for drug–drug interaction prediction	77
DaDL-SChlo: protein subchloroplast localization prediction based on generative adversarial networks and pre-trained protein language model	76
Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation	76
Contexts and contradictions: a roadmap for computational drug repurposing with knowledge inference	76
Multiphysical graph neural network (MP-GNN) for COVID-19 drug design	74
Predicting miRNA–disease associations via learning multimodal networks and fusing mixed neighborhood information	74
SEGCECO: Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication	74
Identifying cancer prognosis genes through causal learning	73
The five pillars of computational reproducibility: bioinformatics and beyond	73
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	73
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	73
TRIAGE: an R package for regulatory gene analysis	72
DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations	72
A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra	71

Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	71
Integrating scRNA-seq and scATAC-seq with inter-type attention heterogeneous graph neural networks	71
Inferring tumor purity using multi-omics data based on a uniform machine learning framework MoTP	70
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	70
eQTLHap: a tool for comprehensive eQTL analysis considering haplotypic and genotypic effects	69
Analysis of super-enhancer using machine learning and its application to medical biology	69
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	68
Corrigendum to: Genetic mechanisms of COVID-19 and its association with smoking and alcohol consumption	68
SatXplor—a comprehensive pipeline for satellite DNA analyses in complex genome assemblies	68
Multiomics integration-based molecular characterizations of COVID-19	67
Correction to: HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	67
PartIES: a disease subtyping framework with Partition-level Integration using diffusion-Enhanced Similarities from multi-omics Data	67
Benchmarking digital PCR partition classification methods with empirical and simulated duplex data	67
Comprehensive evaluation of noise reduction methods for single-cell RNA sequencing data	66
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	66
ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data	65
Choice of assemblers has a critical impact on de novo assembly of SARS-CoV-2 genome and characterizing variants	65
PELMI: Realize robust DNA image storage under general errors via parity encoding and local mean iteration	65
ifDEEPre: large protein language-based deep learning enables interpretable and fast predictions of enzyme commission numbers	65
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	64
SC-AIR-BERT: a pre-trained single-cell model for predicting the antigen-binding specificity of the adaptive immune receptor	64
ProteinF3S: boosting enzyme function prediction by fusing protein sequence, structure, and surface	63
A novel framework for phage-host prediction via logical probability theory and network sparsification	63
cyclicpeptide: a Python package for cyclic peptide drug design	62
Deciphering progressive lesion areas in breast cancer spatial transcriptomics via TGR-NMF	62
DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations	62
Genome-wide association neural networks identify genes linked to family history of Alzheimer’s disease	62
FedSPL: federated self-paced learning for privacy-preserving disease diagnosis	61
DeepTTA: a transformer-based model for predicting cancer drug response	61
Accurate TCR-pMHC interaction prediction using a BERT-based transfer learning method	60
Computational anti-COVID-19 drug design: progress and challenges	60
A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains	60
A robust and scalable graph neural network for accurate single-cell classification	60
RefRGim: an intelligent reference panel reconstruction method for genotype imputation with convolutional neural networks	59
HIP: a method for high-dimensional multi-view data integration and prediction accounting for subgroup heterogeneity	58
Comparison of approaches to transcriptomic analysis in multi-sampled tumors	58
Unsupervised construction of gene regulatory network based on single-cell multi-omics data of colorectal cancer	58
Genome sequencing data analysis for rare disease gene discovery	58
AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease	57
An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology	57
Analysis of affinity purification-related proteomic data for studying protein–protein interaction networks in cells	57
Deep autoregressive generative models capture the intrinsics embedded in T-cell receptor repertoires	57
Evaluation of graphical models for multi-group metabolomics data	57
The accurate prediction and characterization of cancerlectin by a combined machine learning and GO analysis	57
INTREPPPID—an orthologue-informed quintuplet network for cross-species prediction of protein–protein interaction	56
Comprehensive characterization genetic regulation and chromatin landscape of enhancer-associated long non-coding RNAs and their implication in human cancer	56
Locus-specific expression analysis of transposable elements	55
circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier	55
A hybrid positive unlabeled learning framework for uncovering scaffolds across human proteome by measuring the propensity to drive phase separation	55
Deciphering the genetic architecture of human brain structure and function: a brief survey on recent advances of neuroimaging genomics	55
A high-dimensional omnibus test for set-based association analysis	54
Cancerous time estimation for interpreting the evolution of lung adenocarcinoma	54
A robust statistical approach for finding informative spatially associated pathways	54
Building multiscale models with PhysiBoSS, an agent-based modeling tool	54
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	53
Matching single cells across modalities with contrastive learning and optimal transport	53
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	52
Two-stage-vote ensemble framework based on integration of mutation data and gene interaction network for uncovering driver genes	52
GPMeta: a GPU-accelerated method for ultrarapid pathogen identification from metagenomic sequences	52
eSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data	51
KGANSynergy: knowledge graph attention network for drug synergy prediction	51
STMHCpan, an accurate Star-Transformer-based extensible framework for predicting MHC I allele binding peptides	51
BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data	50
iEssLnc: quantitative estimation of lncRNA gene essentialities with meta-path-guided random walks on the lncRNA-protein interaction network	50
m6ATM: a deep learning framework for demystifying the m6A epitranscriptome with Nanopore long-read RNA-seq data	50
Protein phosphorylation database and prediction tools	50
Integrative COVID-19 biological network inference with probabilistic core decomposition	49
ProsmORF-pred: a machine learning-based method for the identification of small ORFs in prokaryotic genomes	49
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	49
Heavy chain sequence-based classifier for the specificity of human antibodies	48
DEWNA: dynamic entropy weight network analysis and its application to the DNA-binding proteome in A549 cells with cisplatin-induced damage	48
SARS-CoV-2 transmissibility compared between variants of concern and vaccination status	48
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	48
MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis	47
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	47
A review of feature selection strategies utilizing graph data structures and Knowledge Graphs	47
A multi-task prediction method based on neighborhood structure embedding and signed graph representation learning to infer the relationship between circRNA, miRNA, and cancer	47
DeepMiceTL: a deep transfer learning based prediction of mice cardiac conduction diseases using early electrocardiograms	47
RiceSNP-BST: a deep learning framework for predicting biotic stress–associated SNPs in rice	47
Distant metastasis identification based on optimized graph representation of gene interaction patterns	46

Adversarial regularized autoencoder graph neural network for microbe-disease associations prediction	46
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	46
iDRPro-SC: identifying DNA-binding proteins and RNA-binding proteins based on subfunction classifiers	46
Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses	45
EnGens: a computational framework for generation and analysis of representative protein conformational ensembles	45
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	45
Detection of germline CNVs from gene panel data: benchmarking the state of the art	45
Bridging-BPs: a novel approach to predict potential drug–target interactions based on a bridging heterogeneous graph and BPs2vec	45
Heterogeneous graph contrastive learning with gradient balance for drug repositioning	45
Augmenting small biomedical datasets using generative AI methods based on self-organizing neural networks	45
ML-PLIC: a web platform for characterizing protein–ligand interactions and developing machine learning-based scoring functions	44
Defining the single base importance of human mRNAs and lncRNAs	44
An inductive transfer learning force field (ITLFF) protocol builds protein force fields in seconds	44
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	44
Deep transfer learning for clinical decision-making based on high-throughput data: comprehensive survey with benchmark results	44
Contrastively generative self-expression model for single-cell and spatial multimodal data	43
Making PBPK models more reproducible in practice	43
Network analytics for drug repurposing in COVID-19	43
A comprehensive assessment of hurdle and zero-inflated models for single cell RNA-sequencing analysis	43
MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification	43
Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning	43
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	43
Comprehensive bioinformatics and machine learning analyses for breast cancer staging using TCGA dataset	42
Computational analyses of bacterial strains from shotgun reads	42
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	42
IndGOterm: a qualitative method for the identification of individually dysregulated GO terms in cancer	42
GraphTGI: an attention-based graph embedding model for predicting TF-target gene interactions	41
Letter to the editor: testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis	41
Bioinformatics/network topology analysis of acupuncture in the treatment of COVID-19: response to methodological issues	41
Precise identification of somatic and germline variants in the absence of matched normal samples	41
BiTSC 2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data	41
An interpretable block-attention network for identifying regulatory feature interactions	41
scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding	40
deepGraphh: AI-driven web service for graph-based quantitative structure–activity relationship analysis	40
Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration	40
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	40
TransAC4C—a novel interpretable architecture for multi-species identification of N4-acetylcytidine sites in RNA with single-base resolution	40
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	39
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	39
PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection	39
Learning discriminative and structural samples for rare cell types with deep generative model	39
Prediction of biomarker–disease associations based on graph attention network and text representation	39
Predicting multiple types of miRNA–disease associations using adaptive weighted nonnegative tensor factorization with self-paced learning and hypergraph regularization	39
MLysPRED: graph-based multi-view clustering and multi-dimensional normal distribution resampling techniques to predict multiple lysine sites	38
CORN—Condition Orientated Regulatory Networks: bridging conditions to gene networks	38
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	38
Linking research of biomedical datasets	38
Evaluating large language models for annotating proteins	38
Clustered tree regression to learn protein energy change with mutated amino acid	38
Scalable batch-correction approach for integrating large-scale single-cell transcriptomes	38
MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification	38
Multi-modal chemical information reconstruction from images and texts for exploring the near-drug space	37
NetTDP: permutation-based true discovery proportions for differential co-expression network analysis	37
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	37
Identifying and training deep learning neural networks on biomedical-related datasets	37
Accurate prediction of antibody function and structure using bio-inspired antibody language model	37
Open tools for quantitative anonymization of tabular phenotype data: literature review	37
A universal model of RNA.DNA:DNA triplex formation accurately predicts genome-wide RNA–DNA interactions	37
Line graph attention networks for predicting disease-associated Piwi-interacting RNAs	37
MHADTI: predicting drug–target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms	37
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	37
Response to Letter to Editor ‘Timely need for navigating the potential and downsides of LLMs in healthcare and biomedicine’	37
WEDGE: imputation of gene expression values from single-cell RNA-seq datasets using biased matrix decomposition	36
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data	36
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	36
Assessing polygenic risk score models for applications in populations with under-represented genomics data: an example of Vietnam	36
An effective self-supervised framework for learning expressive molecular global representations to drug discovery	36
Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review	36
Multi-model predictive analysis of RNA solvent accessibility based on modified residual attention mechanism	35
Deep drug-target binding affinity prediction with multiple attention blocks	35
Image-based molecular representation learning for drug development: a survey	35
Omics data analysis and integration for COVID-19 patients – editorial	35
How does the structure of data impact cell–cell similarity? Evaluating how structural properties influence the performance of proximity metrics in single cell RNA-seq data	35
A new framework for drug–disease association prediction combing light-gated message passing neural network and gated fusion mechanism	35
Single-cell RNA sequencing data imputation using bi-level feature propagation	35
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	35
Morphological profiling for drug discovery in the era of deep learning	34
GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction	34
Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair	34
Improved model quality assessment using sequence and structural information by enhanced deep neural networks	34
Identification of drug-side effect association via restricted Boltzmann machines with penalized term	34
Computational model for ncRNA research	34
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	34
Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision	34
siGCD: a web server to explore survival interaction of genes, cells and drugs in human cancers	34
DeFusion: a denoised network regularization framework for multi-omics integration	34
GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution	33
Biclustering data analysis: a comprehensive survey	33
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	33
Attribute-guided prototype network for few-shot molecular property prediction	33
Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research	33
bulkAnalyseR: an accessible, interactive pipeline for analysing and sharing bulk multi-modal sequencing data	33
Liquidhope: methylome and genomic profiling from very limited quantities of plasma-derived DNA	33
Quercetin for COVID-19 and DENGUE co-infection: a potential therapeutic strategy of targeting critical host signal pathways triggered by SARS-CoV-2 and DENV	33
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	33