OOIR: Observatory of International Research

Papers

(The H4-Index of Briefings in Bioinformatics is 68. 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 2022-08-01 to 2026-08-01.)

Article	Citations
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	1026
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	626
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	610
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	501
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	362
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	320
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	233
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	231
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	222
Systematic evaluation of de novo mutation calling tools using whole genome sequencing data	196
Stoichiometry-preserving and stochasticity-aware identification of m6A from direct RNA sequencing	180
Assessing protein model quality based on deep graph coupled networks using protein language model	162
Towards comprehensive benchmarking of medical vision language models	154
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	151
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	148
Ensemble learning based on matrix completion improves microbe-disease association prediction	140
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	140
Genome assembly and gene identification of biosurfactant-producing bacteria for environmental bioremediation	129
Computational refinement and multivalent engineering of complementarity-determining region-grafted nanobodies on a humanized scaffold for retaining antiviral efficacy	128
Building multiscale models with PhysiBoSS, an agent-based modeling tool	128
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	122
Multi-marker testing based on accelerated failure time models under possible left truncation and competing risks	122
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	116
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	115
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	115

Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	114
GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis	113
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	110
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	103
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	103
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	101
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	100
A robust statistical approach for finding informative spatially associated pathways	99
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	98
STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance	98
Clustered tree regression to learn protein energy change with mutated amino acid	95
Learning discriminative and structural samples for rare cell types with deep generative model	93
Protein phosphorylation database and prediction tools	93
Hi-C3: a statistical inference-based model for reconstructing higher-order cell–cell communication networks	93
DADA-EV: domain-adaptive diffusion autoencoder for estimating tissue- and cell-type-specific origin in extracellular vesicle transcriptomes	93
Nonlinear kernel-based high-dimensional inference for set-based genetic association studies	92
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	91
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	91
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	89
Making PBPK models more reproducible in practice	87
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	86
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	84
Computational model for ncRNA research	84
AICellType: a large language model-based platform for accurate cell type annotation	82
DeepCheck: multitask learning aids in assessing microbial genome quality	81
Analysis of super-enhancer using machine learning and its application to medical biology	80
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	79
Identification of vital chemical information via visualization of graph neural networks	79
Improving drug response prediction via integrating gene relationships with deep learning	79
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	79
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	78
A comprehensive benchmark of tools for efficient genomic interval querying	78
Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior	77
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	77
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	76
Graph-based RNA structural representation reveals determinants of subcellular localization	74
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	74
Attribute-guided prototype network for few-shot molecular property prediction	73
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	73
Machine learning modeling of RNA structures: methods, challenges and future perspectives	72
FGeneBERT: function-driven pre-trained gene language model for metagenomics	72
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	72
Large-scale predicting protein functions through heterogeneous feature fusion	70
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	68
Machine learning–augmented m6A-Seq analysis without a reference genome	68