ArticleFrontiers in bioengineering and biotechnology2018
GitHub Statistics as a Measure of the Impact of Open-Source Bioinformatics Software.
Article in Frontiers in bioengineering and biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 21 citations in OpenAlex.
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- Bioinformatics Methods for Transcriptome Analysis on Teratogenesis Testing.Methods in molecular biology (Clifton, N.J.) · 2024Article
- A comprehensive overview of cellular senescence from 1990 to 2021: A machine learning-based bibliometric analysis.Frontiers in medicine · 2023Article
- Cultivation modes impacting root microbiomes and metabolites in medicinal orchidFrontiers in microbiomes · 2023Article
- Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software.Genome biology · 2022Article
- Mutation Characteristics and Phylogenetic Analysis of FiveAnimals : an open access journal from MDPI · 2022Article
- Analyzing the interactions of mRNAs, miRNAs and lncRNAs to predict ceRNA networks in bovine cystic follicular granulosa cells.Frontiers in veterinary science · 2022Article
- Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers.Nature methods · 2021Review
- The role of metadata in reproducible computational research.Patterns (New York, N.Y.) · 2021Review
- A Bibliometric Analysis of 14,822 Researches on Myocardial Reperfusion Injury by Machine Learning.International journal of environmental research and public health · 2021Article
- Molecular bases of responses to abiotic stress in trees.Journal of experimental botany · 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
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern research is increasingly data-driven and reliant on bioinformatics software. Publication is a common way of introducing new software, but not all bioinformatics tools get published. Giving there are competing tools, it is important not merely to find the appropriate software, but have a metric for judging its usefulness. Journal's impact factor has been shown to be a poor predictor of software popularity; consequently, focusing on publications in high-impact journals limits user's choices in finding useful bioinformatics tools. Free and open source software repositories on popular code sharing platforms such as GitHub provide another venue to follow the latest bioinformatics trends. The open source component of GitHub allows users to bookmark and copy repositories that are most useful to them. This Perspective aims to demonstrate the utility of GitHub "stars," "watchers," and "forks" (GitHub statistics) as a measure of software impact. We compiled lists of impactful bioinformatics software and analyzed commonly used impact metrics and GitHub statistics of 50 genomics-oriented bioinformatics tools. We present examples of community-selected best bioinformatics resources and show that GitHub statistics are distinct from the journal's impact factor (JIF), citation counts, and alternative metrics (Altmetrics, CiteScore) in capturing the level of community attention. We suggest the use of GitHub statistics as an unbiased measure of the usability of bioinformatics software complementing the traditional impact metrics.
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.