ArticleBiology2024
Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy.
Article in Biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Article
- MRPL13 sustains mitochondrial integrity and MAPK-associated aggressiveness in esophageal squamous cell carcinoma.Cancer cell international · 2026Article
- Integrated multi-omics reveals the ITGB2-IL2RB-NK axis in promoting papillary thyroid carcinoma progression and immune microenvironment crosstalk.Discover oncology · 2026Article
- The quantified immune-aging dysregulation index: a large-language model-powered method for annotating and quantifying systems-level dysregulation.Frontiers in artificial intelligence · 2026Article
- Assessment of Potential Toxic Effects of RNAi-Based Transgenic Cotton on the Non-Target PredatorBiology · 2025Article
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
Abstract
RNA-seq faces persistent challenges due to the ongoing, expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Here, we used Shannon entropy as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, such as DESeq2 and edgeR, but also by combining nine normalization methods with log
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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 Socratic graph.