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 2021-09-01 to 2025-09-01.)

Article	Citations
Computational model for ncRNA research	585
Genome sequencing data analysis for rare disease gene discovery	397
Large-scale predicting protein functions through heterogeneous feature fusion	318
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	312
Building multiscale models with PhysiBoSS, an agent-based modeling tool	277
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	272
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	243
Combining power of different methods to detect associations in large data sets	217
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	213
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	206
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	200
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	194
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	186
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	167
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	159
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	154
A robust statistical approach for finding informative spatially associated pathways	152
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	148
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	146
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	134
Ensemble learning based on matrix completion improves microbe-disease association prediction	133
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	129
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	126
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	119
Clustered tree regression to learn protein energy change with mutated amino acid	117

CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	117
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	114
Machine learning–augmented m6A-Seq analysis without a reference genome	114
Evaluating large language models for annotating proteins	110
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	109
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	105
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	104
Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations	104
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	103
Protein phosphorylation database and prediction tools	97
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	97
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	97
DeepCheck: multitask learning aids in assessing microbial genome quality	96
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	96
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	96
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	95
Deep learning in integrating spatial transcriptomics with other modalities	94
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	93
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	93
Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	93
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	92
Attribute-guided prototype network for few-shot molecular property prediction	91
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	87
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	86
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	85
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	84
Computational analyses of bacterial strains from shotgun reads	84
PLMFit: benchmarking transfer learning with protein language models for protein engineering	83
A comprehensive benchmark of tools for efficient genomic interval querying	83
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	83
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	82
Machine learning modeling of RNA structures: methods, challenges and future perspectives	82
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	82
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	78
Machine learning methods, databases and tools for drug combination prediction	78
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	78
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	77
Distant metastasis identification based on optimized graph representation of gene interaction patterns	76
A review on the application of bioinformatics tools in food microbiome studies	74
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	74
A robust and scalable graph neural network for accurate single-cell classification	73
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	73
Assessing protein model quality based on deep graph coupled networks using protein language model	73
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	73
AptaDiff: de novo design and optimization of aptamers based on diffusion models	72
Detecting tipping points of complex diseases by network information entropy	72
Making PBPK models more reproducible in practice	72