ArticleFrontiers in genetics2014
Network Assessor: an automated method for quantitative assessment of a network's potential for gene function prediction.
Article in Frontiers in genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Identifying methamphetamine use predictors in HIV infection: Immune-dopaminergic signatures in peripheral leukocytes and the role of COMT genotype.Brain, behavior, & immunity - health · 2024Article
- Polygenic networks in peripheral leukocytes indicate patterns associated with HIV infection and context-dependent effects of cannabis use.Brain, behavior, & immunity - health · 2022Article
- Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction.PloS one · 2016Article
- Novel function discovery with GeneMANIA: a new integrated resource for gene function prediction in Escherichia coli.Bioinformatics (Oxford, England) · 2015Article
- DNA methylation modifies urine biomarker levels in 1,6-hexamethylene diisocyanate exposed workers: a pilot study.Toxicology letters · 2014Article
- Quantitative assessment and validation of network inference methods in bioinformatics.Frontiers in genetics · 2014Article
- GeneMANIA: Fast gene network construction and function prediction for Cytoscape.F1000Research · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Significant effort has been invested in network-based gene function prediction algorithms based on the guilt by association (GBA) principle. Existing approaches for assessing prediction performance typically compute evaluation metrics, either averaged across all functions being considered, or strictly from properties of the network. Since the success of GBA algorithms depends on the specific function being predicted, evaluation metrics should instead be computed for each function. We describe a novel method for computing the usefulness of a network by measuring its impact on gene function cross validation prediction performance across all gene functions. We have implemented this in software called Network Assessor, and describe its use in the GeneMANIA (GM) quality control system. Network Assessor is part of the GM command line tools.
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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.