OOIR: Observatory of International Research

Papers

(The H4-Index of BMC Bioinformatics is 46. 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 2022-01-01 to 2026-01-01.)

Article	Citations
A novel nonparametric computational strategy for identifying differential methylation regions	1324
Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis	379
Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis	279
Multivariate estimation of factor structures of complex traits using SNP-based genomic relationships	168
SALON ontology for the formal description of sequence alignments	138
Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data	120
Correction: DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction	110
Topology preserving stratification of tissue neoplasticity using Deep Neural Maps and microRNA signatures	109
Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology	105
CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice	101
Prior knowledge on context-driven DNA fragmentation probabilities can improve de novo genome assembly algorithms	101
CMIC: predicting DNA methylation inheritance of CpG islands with embedding vectors of variable-length k-mers	101
A shrinkage-based statistical method for testing group mean differences in quantitative bottom-up proteomics	93
A binary biclustering algorithm based on the adjacency difference matrix for gene expression data analysis	90
DualGCN-GE: integration of spatiotemporal representations from whole-blood expression data with dual-view graph convolution network to identify Parkinson’s disease subtypes	89
Combining whole genome sequencing and non-adaptive group testing for large-scale ethnicity screens	88
Weighted overlapping group lasso for integrating prior network knowledge into gene set analysis	87
REDalign: accurate RNA structural alignment using residual encoder-decoder network	83
CircWalk: a novel approach to predict CircRNA-disease association based on heterogeneous network representation learning	76
Enabling personalised disease diagnosis by combining a patient’s time-specific gene expression profile with a biomedical knowledge base	75
Prediction of hot spots in protein–DNA binding interfaces based on discrete wavelet transform and wavelet packet transform	74
Integrated analysis of the voltage-gated potassium channel-associated gene KCNH2 across cancers	74
SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration	71
Multilayer network alignment based on topological assessment via embeddings	64
A gene based combination test using GWAS summary data	61

Abstraction-based segmental simulation of reaction networks using adaptive memoization	61
Prediction of HIV-1 protease cleavage site from octapeptide sequence information using selected classifiers and hybrid descriptors	59
Mabs, a suite of tools for gene-informed genome assembly	56
Grace-AKO: a novel and stable knockoff filter for variable selection incorporating gene network structures	56
LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks	56
SKiM-GPT: combining biomedical literature-based discovery with large language model hypothesis evaluation	55
Hitac: a hierarchical taxonomic classifier for fungal ITS sequences compatible with QIIME2	54
Examination of blood samples using deep learning and mobile microscopy	54
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction	54
HPC-T-Assembly: a pipeline for de novo transcriptome assembly of large multi-specie datasets	52
Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized control	52
Combining denoising of RNA-seq data and flux balance analysis for cluster analysis of single cells	51
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens	51
Empowering the discovery of novel target-disease associations via machine learning approaches in the open targets platform	51
Deep learning and multi-omics approach to predict drug responses in cancer	51
Latent dirichlet allocation for double clustering (LDA-DC): discovering patients phenotypes and cell populations within a single Bayesian framework	50
PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins	48
SVhound: detection of regions that harbor yet undetected structural variation	48
DTIP-WINDGRU a novel drug-target interaction prediction with wind-enhanced gated recurrent unit	46
A-Prot: protein structure modeling using MSA transformer	46
VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples	46