Impact Factor
4.87
Journal Citation Impact
Estimated influence, citation density, publishing volume, and citation integrity from the analytics table.
Citation rate
9.88
12,638 total citations
h5-index
118
h5 depth signal
Cited share
89.8%
1,235 of 1,376
Total citations
12,638
Citation footprint
Metric signal
9.37
External metric anchor
Self-citation
5.0%
629 self-citations
Citations Trend
Monthly Publications Cadence
Citing Geographic Demographics
China
2,725
United States
1,048
Australia
199
United Kingdom
192
Germany
187
Citing Fields of Research
Genetics & Genomics
2,753
AI & Machine Learning
1,747
Protein Structure & Folding
847
Noncoding RNA
499
Nucleic Acids Chemistry
302
Publishing Activity & Reach
Volume, recency, access pattern, and citing-community signals from the journal analytics record.
All-time article footprint
5,964
Articles tracked across the journal lifetime
Indexed publication set
1,376
1,235 cited publications
Last 12 months
780
111.4 publications/month
Open access share
99.9%
779 OA publications in the last year
Leading citing country
China
2,725 citing publications
Leading citing field
Genetics & Genomics
2,753 citing publications
Latest tracked publication
1 September 2026
10 recent records available
Coverage & Indexing History
v1n1, Feb. 2000-
v1n1, Feb. 2000-
Active Coverage
Active Coverage
Research Focus & Classification
Indexed Subjects
Genetics & Genomics
AI & Machine Learning
Protein Structure & Folding
Broad Categories
Computational Biology
Genetics & Genomics
MeSH Descriptors
Computational Biology
Databases, Factual
Medical Informatics
Molecular Sequence Data
Software
Latest Publications
Recent article records with DOI-first linking and condensed abstracts.
01
DOI 10.1093/bib/bbag563
Open DOI
DeepU-PRS: nonlinear and uncertainty-aware SNP heritability modeling for annotation-informed polygenic risk scoring
Polygenic risk scores (PRSs) are widely used to quantify genetic predisposition to complex traits, and their predictive accuracy can be enhanced by incorporating functional annotations into single-nucleotide polymorphism (SNP) effect-siz...
02
DOI 10.1093/bib/bbag559
Open DOI
Decoding cellular vulnerabilities for interpretable drug response prediction
Accurate prediction of anticancer drug response remains challenging because conventional approaches based on chemical structures and baseline molecular profiles do not directly capture drug-induced perturbations or cellular dependencies....
03
DOI 10.1093/bib/bbag549
Open DOI
Assessing the impact of parental linear gene normalization on the performance of statistical models for circular RNA differential expression analysis
Background: Circular RNAs (circRNAs) have emerged as promising non-invasive cancer biomarkers due to their stability, abundance in body fluids, and regulatory potential. However, circRNA differential expression analysis (DEA) remains cha...
04
05
DOI 10.1093/bib/bbag557
Open DOI
Cross-tissue graph attention networks for semi-supervised gene expression prediction
High-throughput biotechnologies have significantly advanced precision medicine by enabling the exploitation of global gene expression patterns to enhance our understanding of disease etiology, progression, and treatment options. However,...
06
DOI 10.1093/bib/bbag571
Open DOI
DecBin: Bayesian-optimized deep clustering for long-read metagenomic binning
Accurate metagenomic binning is essential for reconstructing microbial genomes, thereby facilitating the discovery of novel taxa, the identification of pathogens, and the characterization of antimicrobial resistance genes. Most existing ...
07
DOI 10.1093/bib/bbag560
Open DOI
An integrative multi-omics modeling framework for chemotherapy response prediction through microRNA–target regulatory signatures
Chemotherapy remains a cornerstone of cancer treatment, yet therapeutic resistance continues to limit durable clinical responses. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that orchestrate diverse cell...
08
DOI 10.1093/bib/bbag545
Open DOI
BRIDGE-KO: auditable transfer learning with bridged knockoffs improves cross-cohort microbiome prediction of immunotherapy response
Transfer learning promises to reuse AI models across biomedical studies, but it often fails when differences between datasets introduce cohort-specific artifacts and ‘negative transfer.’ We present BRIDGE-KO, an interpretable deep-learni...
09
DOI 10.1093/bib/bbag564
Open DOI
Explainable/interpretable artificial intelligence and knowledge graph neural network for synthetic lethality prediction: overview, challenges, and future directions
Synthetic lethality (SL) provides a powerful foundation for targeted oncology by identifying gene pairs whose simultaneous disruption is fatal to cancer cells while sparing healthy tissue. However, mapping these interactions experimental...
10
DOI 10.1093/bib/bbag567
Open DOI
KAT-Net: a hyperbolic routing framework for joint lysine acylation site prediction with shared sequence–structure representations
Protein lysine acylation regulates protein function through changes in local chemistry, structure, and molecular interactions. Acetylation (Kac), succinylation (Ksucc), and crotonylation (Kcr) share the lysine centre but differ in acyl-g...
Bibliographical & Catalog Notes
Also available online.
v.1, no. 1 (Feb. 2000)20010725 Notice published Printed on acid-free paper that meets the full ANSI standard for Permanent Paper