Article... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics2021
KARGA: Multi-platform Toolkit for
Article in ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- K-MARVEL: K-Mer-based antimicrobial resistance virtual exploration lab.Nature communications · 2026Article
- resLens: genomic language models to enhance antibiotic resistance gene detection.npj antimicrobials and resistance · 2026Article
- HYMET: a hybrid metagenomic pipeline for accurate and efficient taxonomic classification.GigaScience · 2026Article
- BugBuster: a novel automatic and reproducible workflow for metagenomic data analysis.Bioinformatics advances · 2025Article
- MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing.Nucleic acids research · 2023Article
- TheFrontiers in microbiology · 2023Article
- Bioinformatics and Genomic Analyses of the Suitability of Eight Riboswitches for Antibacterial Drug Targets.Antibiotics (Basel, Switzerland) · 2022Article
- Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions.Artificial intelligence in medicine · 2022Article
- Towards routine employment of computational tools for antimicrobial resistance determination via high-throughput sequencing.Briefings in bioinformatics · 2022Article
- KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genesFrontiers in bioengineering and biotechnology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
High-throughput sequencing is widely used for strain detection and characterization of antibiotic resistance in microbial metagenomic samples. Current analytical tools use curated antibiotic resistance gene (ARG) databases to classify individual sequencing reads or assembled contigs. However, identifying ARGs from raw read data can be time consuming (especially if assembly or alignment is required) and challenging, due to genome rearrangements and mutations. Here, we present the
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.