OOIR: Observatory of International Research

Papers

(The H4-Index of BMC Bioinformatics is 49. 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 2022-06-01 to 2026-06-01.)

Article	Citations
Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis	1572
Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis	346
SALON ontology for the formal description of sequence alignments	164
CMIC: predicting DNA methylation inheritance of CpG islands with embedding vectors of variable-length k-mers	143
Combining whole genome sequencing and non-adaptive group testing for large-scale ethnicity screens	135
Weighted overlapping group lasso for integrating prior network knowledge into gene set analysis	122
REDalign: accurate RNA structural alignment using residual encoder-decoder network	121
SKiM-GPT: combining biomedical literature-based discovery with large language model hypothesis evaluation	120
Prior knowledge on context-driven DNA fragmentation probabilities can improve de novo genome assembly algorithms	120
A shrinkage-based statistical method for testing group mean differences in quantitative bottom-up proteomics	118
A binary biclustering algorithm based on the adjacency difference matrix for gene expression data analysis	110
SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration	108
CircWalk: a novel approach to predict CircRNA-disease association based on heterogeneous network representation learning	104
Enabling personalised disease diagnosis by combining a patient’s time-specific gene expression profile with a biomedical knowledge base	99
Prediction of hot spots in protein–DNA binding interfaces based on discrete wavelet transform and wavelet packet transform	93
Machine learning for multi-omics data integration in crop improvement: a systematic review	89
DualGCN-GE: integration of spatiotemporal representations from whole-blood expression data with dual-view graph convolution network to identify Parkinson’s disease subtypes	73
Correction: DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction	72
Multivariate estimation of factor structures of complex traits using SNP-based genomic relationships	72
Combining denoising of RNA-seq data and flux balance analysis for cluster analysis of single cells	72
LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks	70
CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice	69
A two-phase clustering procedure based on allele specific expression	68
Mabs, a suite of tools for gene-informed genome assembly	67
HPC-T-Assembly: a pipeline for de novo transcriptome assembly of large multi-specie datasets	66

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens	66
A gene based combination test using GWAS summary data	65
Latent dirichlet allocation for double clustering (LDA-DC): discovering patients phenotypes and cell populations within a single Bayesian framework	63
Hitac: a hierarchical taxonomic classifier for fungal ITS sequences compatible with QIIME2	63
Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data	62
Abstraction-based segmental simulation of reaction networks using adaptive memoization	62
Prediction of HIV-1 protease cleavage site from octapeptide sequence information using selected classifiers and hybrid descriptors	61
Empowering the discovery of novel target-disease associations via machine learning approaches in the open targets platform	61
A comparative analysis of topological domain callers over RNA-associated interactome	60
PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins	57
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction	56
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	55
Multilayer network alignment based on topological assessment via embeddings	55
Deep learning and multi-omics approach to predict drug responses in cancer	54
Grace-AKO: a novel and stable knockoff filter for variable selection incorporating gene network structures	54
Integrated analysis of the voltage-gated potassium channel-associated gene KCNH2 across cancers	53
Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology	52
SVhound: detection of regions that harbor yet undetected structural variation	51
DTIP-WINDGRU a novel drug-target interaction prediction with wind-enhanced gated recurrent unit	51
A novel modality contribution confidence-enhanced multimodal deep learning framework for multiomics data	50
MTAGCN: predicting miRNA-target associations in Camellia sinensis var. assamica through graph convolution neural network	49
A novel IVN-entropy based distance-driven MARCOS framework for evaluating and ranking global green hydrogen-producing countries	49
MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction	49
Identification of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in alimentary tract malignancies	49
NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects	49