ArticleAnnals of the New York Academy of Sciences2012
Accurate evaluation and analysis of functional genomics data and methods.
Article in Annals of the New York Academy of Sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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.
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Who cites it
13 citing papers in PubMed.
- Effusion: prediction of protein function from sequence similarity networks.Bioinformatics (Oxford, England) · 2019Article
- NewG3 (Bethesda, Md.) · 2019Article
- Enabling Precision Medicine through Integrative Network Models.Journal of molecular biology · 2018Review
- CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.Bioinformatics (Oxford, England) · 2018Article
- Organellar genome assembly methods and comparative analysis of horticultural plants.Horticulture research · 2018Article
- Machine Learning Analysis IdentifiesG3 (Bethesda, Md.) · 2017Article
- Implicating candidate genes at GWAS signals by leveraging topologically associating domains.European journal of human genetics : EJHG · 2017Article
- Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.Cell systems · 2017Article
- Negative example selection for protein function prediction: the NoGO database.PLoS computational biology · 2014Article
- Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity.Genome medicine · 2014Article
- Parametric Bayesian priors and better choice of negative examples improve protein function prediction.Bioinformatics (Oxford, England) · 2013Article
- Assessing identity, redundancy and confounds in Gene Ontology annotations over time.Bioinformatics (Oxford, England) · 2013Article
- Chapter 2: Data-driven view of disease biology.PLoS computational biology · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner.
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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.