ReviewNature reviews. Genetics2024
Challenges and best practices in omics benchmarking.
Review in Nature reviews. Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
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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.
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Who cites it
33 citing papers in PubMed.
- Integrative transcriptomic and network analysis elucidates the multi-target molecular mechanisms of carboplatin in melanoma.Medical oncology (Northwood, London, England) · 2026Article
- NeuroMetBench: patient-aware evidence bounds for transcript-derived metabolic representations across cancer proteogenomic contexts.Functional & integrative genomics · 2026Article
- MKMC enables reference-free transcriptomic analysis using k-mer representations.bioRxiv : the preprint server for biology · 2026Article
- GATSBI: improving context-aware protein embeddings through biologically motivated data splits.Bioinformatics (Oxford, England) · 2026Article
- TF-GateNet: An Interpretable and Biologically Guided Framework for Primary-Metastatic State Prediction from Somatic Genomic Alterations.Biomolecules · 2026Article
- Long-read sequencing technologies and bioinformatics: a new perspective for decoding DNA methylation modifications.Journal of translational medicine · 2026Review
- Emerging Urinary Biomarkers and Innovative Technologies for the Early Detection and Personalized Management of Chronic Kidney Disease.International journal of molecular sciences · 2026Review
- Shape-constrained, changepoint additive models for time series omics data with cpam.Nucleic acids research · 2026Article
- GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.bioRxiv : the preprint server for biology · 2026Article
- Liquid biopsy in malignant primary bone tumors: Clinical applications of circulating tumor DNA and circulating tumor cells for diagnosis, prognosis and treatment monitoring (Review).Oncology reports · 2026Review
- Empowering AI data scientists using a multi-agent LLM framework with self-evolving capabilities for autonomous, tool-aware biomedical data analyses.Nature biomedical engineering · 2026Article
- MetaScreener: a robust dual-mode framework for directional prioritization of actionable signatures through multi-dataset and multi-approach integration.Journal of translational medicine · 2026Article
- Navigating the data processing for cytometry-based single-cell proteomics.Nature protocols · 2026Review
- CPSM: an R package for cancer patient survival risk model using transcriptomics and clinical data.GigaScience · 2026Article
- Critical assessment in the age of AI: challenges and opportunities for computational biology.Bioinformatics advances · 2026Article
- Feature learning augmented with sampling and heuristics (FLASH) improves model performance and biomarker identification.NPJ systems biology and applications · 2025Article
- Building a continuous benchmarking ecosystem in bioinformatics.PLoS computational biology · 2025Article
- Recommendations for bioinformatics in clinical practice.Genome medicine · 2025Review
- Methylation reference datasets from quartet DNA materials for benchmarking epigenome sequencing.Nature communications · 2025Article
- Explicit Scale Simulation for analysis of RNA-sequencing count data with ALDEx2.NAR genomics and bioinformatics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological advances enabling massively parallel measurement of biological features - such as microarrays, high-throughput sequencing and mass spectrometry - have ushered in the omics era, now in its third decade. The resulting complex landscape of analytical methods has naturally fostered the growth of an omics benchmarking industry. Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale biological data sets, such as transcriptomics, proteomics and metabolomics. With thousands of omics benchmarking studies published over the past 25 years, the field has matured to the point where the foundations of benchmarking have been established and well described. However, generating meaningful benchmarking data and properly evaluating performance in this complex domain remains challenging. In this Review, we highlight some common oversights and pitfalls in omics benchmarking. We also establish a methodology to bring the issues that can be addressed into focus and to be transparent about those that cannot: this takes the form of a spreadsheet template of guidelines for comprehensive reporting, intended to accompany publications. In addition, a survey of recent developments in benchmarking is provided as well as specific guidance for commonly encountered difficulties.
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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.