ArticleDatabase : the journal of biological databases and curation2020
Variation benchmark datasets: update, criteria, quality and applications.
Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review.Journal of medical Internet research · 2024Pooled it
- Accurate, Scalable Structural Variant Genotyping in Complex Genomes at Population Scales.Molecular biology and evolution · 2025Article
- Benchmarking, detection, and genotyping of structural variants in a population of whole-genome assemblies using the SVGAP pipeline.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking of variant pathogenicity prediction methods using a population genetics approach.Bioinformatics advances · 2025Article
- AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.Human genomics · 2024Article
- Variant Effect Prediction in the Age of Machine Learning.Cold Spring Harbor perspectives in biology · 2024Review
- Machine Learning-Guided Protein Engineering.ACS catalysis · 2023Review
- Artificial Intelligence in Surgical Training for Kidney Cancer: A Systematic Review of the Literature.Diagnostics (Basel, Switzerland) · 2023Review
- Updated benchmarking of variant effect predictors using deep mutational scanning.Molecular systems biology · 2023Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
- Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles.Annual review of ecology, evolution, and systematics · 2022Article
- PON-All: Amino Acid Substitution Tolerance Predictor for All Organisms.Frontiers in molecular biosciences · 2022Article
- Computational approaches for predicting variant impact: An overview from resources, principles to applications.Frontiers in genetics · 2022Review
- A Novel Computer Vision Model for Medicinal Plant Identification Using Log-Gabor Filters and Deep Learning Algorithms.Computational intelligence and neuroscience · 2022Article
- Pathogenic variation types in human genes relate to diseases through Pfam and InterPro mapping.Frontiers in molecular biosciences · 2022Article
- Measuring and interpreting pervasive heterogeneity, poikilosis.FASEB bioAdvances · 2021Article
- PON-Sol2: Prediction of Effects of Variants on Protein Solubility.International journal of molecular sciences · 2021Article
- Systematic evaluation of the effect of polyadenylation signal variants on the expression of disease-associated genes.Genome research · 2021Article
- Problems in variation interpretation guidelines and in their implementation in computational tools.Molecular genetics & genomic medicine · 2020Article
- CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations.Genome medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Development of new computational methods and testing their performance has to be carried out using experimental data. Only in comparison to existing knowledge can method performance be assessed. For that purpose, benchmark datasets with known and verified outcome are needed. High-quality benchmark datasets are valuable and may be difficult, laborious and time consuming to generate. VariBench and VariSNP are the two existing databases for sharing variation benchmark datasets used mainly for variation interpretation. They have been used for training and benchmarking predictors for various types of variations and their effects. VariBench was updated with 419 new datasets from 109 papers containing altogether 329 014 152 variants; however, there is plenty of redundancy between the datasets. VariBench is freely available at http://structure.bmc.lu.se/VariBench/. The contents of the datasets vary depending on information in the original source. The available datasets have been categorized into 20 groups and subgroups. There are datasets for insertions and deletions, substitutions in coding and non-coding region, structure mapped, synonymous and benign variants. Effect-specific datasets include DNA regulatory elements, RNA splicing, and protein property for aggregation, binding free energy, disorder and stability. Then there are several datasets for molecule-specific and disease-specific applications, as well as one dataset for variation phenotype effects. Variants are often described at three molecular levels (DNA, RNA and protein) and sometimes also at the protein structural level including relevant cross references and variant descriptions. The updated VariBench facilitates development and testing of new methods and comparison of obtained performances to previously published methods. We compared the performance of the pathogenicity/tolerance predictor PON-P2 to several benchmark studies, and show that such comparisons are feasible and useful, however, there may be limitations due to lack of provided details and shared data. Database URL: http://structure.bmc.lu.se/VariBench.
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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 Socratic graph.