ArticlePLoS computational biology2015
Ten simple rules for reducing overoptimistic reporting in methodological computational research.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for benchmarking of optimization-based approaches for fitting mathematical models.Genome biology · 2019Guideline
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- A systematic benchmark of bioinformatics methods for single-cell and spatial RNA-seq nanopore long reads data.NAR genomics and bioinformatics · 2026Article
- GHIST 2024: The First Genomic History Inference Strategies Tournament.Molecular biology and evolution · 2025Article
- Characterizing the omics landscape based on 10,000+ datasets.Scientific reports · 2025Article
- Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios.Genome biology · 2024Article
- Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients.Clinical and experimental immunology · 2024Article
- Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices.PLoS computational biology · 2024Article
- Opportunities and challenges in application of artificial intelligence in pharmacology.Pharmacological reports : PR · 2023Review
- Ten quick tips for sequence-based prediction of protein properties using machine learning.PLoS computational biology · 2022Article
- How Do Machines Learn? Artificial Intelligence as a New Era in Medicine.Journal of personalized medicine · 2021Review
- Twelve quick steps for genome assembly and annotation in the classroom.PLoS computational biology · 2020Article
- Model Averaging in Viral Dynamic Models.The AAPS journal · 2020Article
- Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods.Computational and structural biotechnology journal · 2020Review
- Machine Learning Methods for Precision Medicine Research Designed to Reduce Health Disparities: A Structured Tutorial.Ethnicity & disease · 2020Review
- Shift in the paradigm towards next-generation microbiology.FEMS microbiology letters · 2019Review
- Essential guidelines for computational method benchmarking.Genome biology · 2019Review
- PotentialNet for Molecular Property Prediction.ACS central science · 2018Article
- Random forest versus logistic regression: a large-scale benchmark experiment.BMC bioinformatics · 2018Article
- On the overestimation of random forest's out-of-bag error.PloS one · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.