OOIR: Observatory of International Research

Papers

(The H4-Index of Briefings in Bioinformatics is 70. 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 2021-06-01 to 2025-06-01.)

Article	Citations
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	1044
Corrigendum to: Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein	487
Knowledge bases and software support for variant interpretation in precision oncology	337
Computational model for ncRNA research	264
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	230
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	208
DeepCheck: multitask learning aids in assessing microbial genome quality	201
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	201
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	190
Genome sequencing data analysis for rare disease gene discovery	188
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	183
Defining the functional divergence of orthologous genes between human and mouse in the context of miRNA regulation	178
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	178
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	168
Combining power of different methods to detect associations in large data sets	163
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	149
Clustered tree regression to learn protein energy change with mutated amino acid	146
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	139
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	133
Attribute-guided prototype network for few-shot molecular property prediction	128
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	125
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	124
Distant metastasis identification based on optimized graph representation of gene interaction patterns	123
Computational analyses of bacterial strains from shotgun reads	120
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	117

mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	115
A robust statistical approach for finding informative spatially associated pathways	112
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	110
AptaDiff: de novo design and optimization of aptamers based on diffusion models	104
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	103
Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations	101
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	100
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	100
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	98
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	97
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	96
Building multiscale models with PhysiBoSS, an agent-based modeling tool	95
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	94
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	92
ADENet: a novel network-based inference method for prediction of drug adverse events	92
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	91
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	91
Circular RNAs and complex diseases: from experimental results to computational models	89
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	88
Making PBPK models more reproducible in practice	87
Comparative analysis of molecular fingerprints in prediction of drug combination effects	84
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	84
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	84
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	83
Machine learning modeling of RNA structures: methods, challenges and future perspectives	82
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	81
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	80
Analysis of super-enhancer using machine learning and its application to medical biology	80
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	78
Assessing protein model quality based on deep graph coupled networks using protein language model	78
Identification of vital chemical information via visualization of graph neural networks	78
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	77
A robust and scalable graph neural network for accurate single-cell classification	76
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	76
Ensemble learning based on matrix completion improves microbe-disease association prediction	76
Large-scale predicting protein functions through heterogeneous feature fusion	75
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	75
Protein phosphorylation database and prediction tools	75
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	74
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	74
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	73
Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution	73
Deep learning in integrating spatial transcriptomics with other modalities	72
Mol2Context-vec: learning molecular representation from context awareness for drug discovery	71
Learning discriminative and structural samples for rare cell types with deep generative model	71
ADEIP: an integrated platform of age-dependent expression and immune profiles across human tissues	70