ArticleBioinformatics and biology insights2019
On the Upper Bounds of the Real-Valued Predictions.
Article in Bioinformatics and biology insights, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- DAGIP: alleviating cell-free DNA sequencing biases with optimal transport.Genome biology · 2025Article
- AbMelt: Learning antibody thermostability from molecular dynamics.Biophysical journal · 2024Article
- Biologically meaningful genome interpretation models to address data underdetermination for the leaf and seed ionome prediction in Arabidopsis thaliana.Scientific reports · 2024Article
- Assessing computational tools for predicting protein stability changes upon missense mutations using a new dataset.Protein science : a publication of the Protein Society · 2024Article
- Quantification of biases in predictions of protein-protein binding affinity changes upon mutations.Briefings in bioinformatics · 2023Article
- Predicting protein stability changes upon mutation using a simple orientational potential.Bioinformatics (Oxford, England) · 2023Article
- Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset.Briefings in bioinformatics · 2022Article
- From genotype to phenotype in Arabidopsis thaliana: in-silico genome interpretation predicts 288 phenotypes from sequencing data.Nucleic acids research · 2022Article
- Challenges in predicting stabilizing variations: An exploration.Frontiers in molecular biosciences · 2022Article
- A Deep-Learning Sequence-Based Method to Predict Protein Stability Changes Upon Genetic Variations.Genes · 2021Article
- Performance of Regression Models as a Function of Experiment Noise.Bioinformatics and biology insights · 2021Article
- Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine.Computational and structural biotechnology journal · 2020Review
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
No grant is acknowledged in the PubMed record.
Abstract
Predictions are fundamental in science as they allow to test and falsify theories. Predictions are ubiquitous in bioinformatics and also help when no first principles are available. Predictions can be distinguished between classifications (when we associate a label to a given input) or regression (when a real value is assigned). Different scores are used to assess the performance of regression predictors; the most widely adopted include the mean square error, the Pearson correlation (ρ), and the coefficient of determination (or
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.