ArticleMolecular cell2013
New insights from existing sequence data: generating breakthroughs without a pipette.
Article in Molecular cell, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- mirnaQC: a webserver for comparative quality control of miRNA-seq data.Nucleic acids research · 2020Article
- An interactive environment for agile analysis and visualization of ChIP-sequencing data.Nature structural & molecular biology · 2016Article
- Long-range RNA pairings contribute to mutually exclusive splicing.RNA (New York, N.Y.) · 2016Article
- Determining exon connectivity in complex mRNAs by nanopore sequencing.Genome biology · 2015Article
- Unlocking Triticeae genomics to sustainably feed the future.Plant & cell physiology · 2013Review
- Counting on co-transcriptional splicing.F1000prime reports · 2013Article
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
Abstract
With the rapidly declining cost of data generation and the accumulation of massive data sets, molecular biology is entering an era in which incisive analysis of existing data will play an increasingly prominent role in the discovery of new biological phenomena and the elucidation of molecular mechanisms. Here, we discuss resources of publicly available sequencing data most useful for interrogating the mechanisms of gene expression. Existing next-generation sequence data sets, however, come with significant challenges in the form of technical and bioinformatic artifacts, which we discuss in detail. We also recount several breakthroughs made largely through the analysis of existing data, primarily in the RNA field.
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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.