Evidence map›Paper›PMID 41716218›Full record

ReviewFrontiers in bioinformatics2025

Essential nucleic acid omics: a theoretical foundation for early-stage users.

Andrew J Maritan, Frank J Stewart

Abstract readReview
In one paragraph

Review in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Andrew J MaritanMontana State University, Department of Microbiology & Cell Biology, Bozeman, MT, United States.
Frank J StewartMontana State University, Department of Microbiology & Cell Biology, Bozeman, MT, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern biology often relies on the analysis of entire sets of molecules (omics). A subset of omics uses nucleic acid sequencing to reconstruct genomes and profile gene expression. Novel findings and existing data are contextualized by databases, which have been growing exponentially due to falling sequencing costs and increased computing access. The increasing accessibility of omics has led to rapid adoption and widespread self-training via open-access tools. In this training environment new users (many of whom are students also applying computing for the first time) are confronted with Terabytes of sequence data and an ocean of topic-specific computing guides (often directed at high-level users). This flood of information creates an initial barrier of confusion and frustration, where it is challenging to identify the overarching goals of omics analyses through the details of computing. We believe this confusion is understandable but not pre-destined, as omics is-at its core-simple. This simplicity comes from its modular nature, where any analysis requires familiarity with only a few consistent steps. Here, we identify core elements of all omics analyses-data products, tools, and workflows-using microbiology applications to ground the discussion. This structure is informed by first-hand experience training early-stage omics users, where covering omics theory provides a foundation for practical implementation.

Indexed as

beginnerearly careerFAIRguideISAMAGSmetabarcodingpipeline

Identifiers

PMID41716218
PMCPMC12913566

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.