OOIR: Observatory of International Research

Papers

(The H4-Index of Briefings in Bioinformatics is 65. 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 2020-03-01 to 2024-03-01.)

Article	Citations
Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization	758133037
oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data	462
NetCoMi: network construction and comparison for microbiome data in R	203
Predicting drug–disease associations through layer attention graph convolutional network	183
LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files	160
Identifying drug–target interactions based on graph convolutional network and deep neural network	156
BioGPT: generative pre-trained transformer for biomedical text generation and mining	148
MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm	144
CellTalkDB: a manually curated database of ligand–receptor interactions in humans and mice	138
Expression profile of immune checkpoint genes and their roles in predicting immunotherapy response	137
Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities	134
AntiCP 2.0: an updated model for predicting anticancer peptides	127
AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes	123
InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening	121
A deep learning method for predicting metabolite–disease associations via graph neural network	116
Prognosis and personalized treatment prediction in TP53-mutant hepatocellular carcinoma: an in silico strategy towards precision oncology	114
Multimodal deep learning for biomedical data fusion: a review	112
A review on drug repurposing applicable to COVID-19	108
Circular RNAs and complex diseases: from experimental results to computational models	105
Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer	105
The miRNA: a small but powerful RNA for COVID-19	103
Application of deep learning methods in biological networks	102
Predicting the potential human lncRNA–miRNA interactions based on graph convolution network with conditional random field	100
Deep-belief network for predicting potential miRNA-disease associations	99
Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research	99

Exploration of natural compounds with anti-SARS-CoV-2 activityviainhibition of SARS-CoV-2 Mpro	98
DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence	98
A roadmap for multi-omics data integration using deep learning	96
Network Pharmacology and bioinformatics analyses identify intersection genes of niacin and COVID-19 as potential therapeutic targets	95
Biological network analysis with deep learning	93
Systemic effects of missense mutations on SARS-CoV-2 spike glycoprotein stability and receptor-binding affinity	92
A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information	90
Immune cell infiltration-based signature for prognosis and immunogenomic analysis in breast cancer	89
A survey on computational models for predicting protein–protein interactions	87
A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data	87
SSI–DDI: substructure–substructure interactions for drug–drug interaction prediction	87
M6A2Target: a comprehensive database for targets of m6A writers, erasers and readers	86
Molecular characterization, biological function, tumor microenvironment association and clinical significance of m6A regulators in lung adenocarcinoma	85
Detection algorithms and attentive points of safety signal using spontaneous reporting systems as a clinical data source	84
Venn diagrams in bioinformatics	84
Drug repositioning based on the heterogeneous information fusion graph convolutional network	84
An end-to-end heterogeneous graph representation learning-based framework for drug–target interaction prediction	83
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides	82
Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19	82
Utilizing graph machine learning within drug discovery and development	81
Meta-i6mA: an interspecies predictor for identifying DNAN6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework	80
Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method	78
Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization	77
Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace	76
GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels	74
Discovery of G-quadruplex-forming sequences in SARS-CoV-2	73
Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions	72
Current challenges for unseen-epitope TCR interaction prediction and a new perspective derived from image classification	72
POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability	72
Tumor immune microenvironment lncRNAs	72
A weighted bilinear neural collaborative filtering approach for drug repositioning	71
DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites	71
Anticancer peptides prediction with deep representation learning features	71
Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2	70
Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 gliob	70
Multi-view Multichannel Attention Graph Convolutional Network for miRNA–disease association prediction	70
Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework	69
Pan-cancer analysis of NLRP3 inflammasome with potential implications in prognosis and immunotherapy in human cancer	67
PharmKG: a dedicated knowledge graph benchmark for bomedical data mining	66
Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19	66
Health informatics and EHR to support clinical research in the COVID-19 pandemic: an overview	65
Text mining approaches for dealing with the rapidly expanding literature on COVID-19	65
ggmsa: a visual exploration tool for multiple sequence alignment and associated data	65
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets	65
Semantic similarity and machine learning with ontologies	65
MetaFS: Performance assessment of biomarker discovery in metaproteomics	65