OOIR: Observatory of International Research

Papers

(The H4-Index of Briefings in Bioinformatics is 72. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)

Article	Citations
A comprehensive benchmark of tools for efficient genomic interval querying	551
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	377
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	294
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	290
ADENet: a novel network-based inference method for prediction of drug adverse events	247
From intuition to AI: evolution of small molecule representations in drug discovery	245
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	237
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	209
Clustered tree regression to learn protein energy change with mutated amino acid	205
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	204
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	195
Machine learning–augmented m6A-Seq analysis without a reference genome	188
Evaluating large language models for annotating proteins	186
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	182
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	162
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	153
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	146
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	145
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	145
Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations	140
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	129
Distant metastasis identification based on optimized graph representation of gene interaction patterns	129
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	126
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	126
Comparative analysis of molecular fingerprints in prediction of drug combination effects	125

Protein phosphorylation database and prediction tools	117
Mol2Context-vec: learning molecular representation from context awareness for drug discovery	114
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	111
Attribute-guided prototype network for few-shot molecular property prediction	111
A review on the application of bioinformatics tools in food microbiome studies	110
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	109
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	106
Computational analyses of bacterial strains from shotgun reads	104
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	104
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	103
Computational model for ncRNA research	101
Genome sequencing data analysis for rare disease gene discovery	98
Machine learning modeling of RNA structures: methods, challenges and future perspectives	97
Identification of vital chemical information via visualization of graph neural networks	96
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	95
Learning discriminative and structural samples for rare cell types with deep generative model	94
A robust and scalable graph neural network for accurate single-cell classification	93
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	93
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	93
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	91
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	90
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	89
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	88
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	88
Deep learning in integrating spatial transcriptomics with other modalities	87
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	86
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	85
Combining power of different methods to detect associations in large data sets	82
Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	82
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	81
AptaDiff: de novo design and optimization of aptamers based on diffusion models	81
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	81
Analysis of super-enhancer using machine learning and its application to medical biology	80
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	80
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	80
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	79
Machine learning methods, databases and tools for drug combination prediction	79
DeepCheck: multitask learning aids in assessing microbial genome quality	77
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	76
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	76
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	75
Improving drug response prediction via integrating gene relationships with deep learning	75
A robust statistical approach for finding informative spatially associated pathways	74
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	73
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	73
Assessing protein model quality based on deep graph coupled networks using protein language model	73
Ensemble learning based on matrix completion improves microbe-disease association prediction	72
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	72