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

**Authors:** Andrew J. Maritan, Frank J. Stewart

PMC · DOI: 10.3389/fbinf.2025.1721028 · Frontiers in Bioinformatics · 2026-02-04

## TL;DR

This paper explains the basic theory of omics for beginners, helping them understand the core concepts and avoid confusion when working with large biological data.

## Contribution

It introduces a theoretical framework for omics that simplifies learning for early-stage users through modular concepts and practical examples.

## Key findings

- Omics analyses can be simplified into consistent steps, making them easier to learn for new users.
- Training early-stage users with theoretical foundations improves their practical implementation skills.
- Microbiology applications help ground the discussion and clarify the modular nature of omics.

## 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.

## Full-text entities

- **Genes:** CNTN2 (contactin 2) [NCBI Gene 6900] {aka AXT, EPEO5, FAME5, TAG-1, TAX, TAX1}, LYZ (lysozyme) [NCBI Gene 4069] {aka AMYLD5, LYZF1, LZM}
- **Diseases:** sickle-cell anemia (MESH:D000755), FAIR (MESH:C567300)
- **Chemicals:** SDS (MESH:D012967), Phenol (MESH:D019800), chloroform (MESH:D002725), TRIzol (MESH:C411644), amino acids (MESH:D000596), nitrogen (MESH:D009584), methane (MESH:D008697), Bash (-)
- **Species:** Staphylococcus aureus (species) [taxon 1280], Haemophilus influenzae (species) [taxon 727], Pseudomonas sp. (species) [taxon 306], Homo sapiens (human, species) [taxon 9606], Saccharomyces cerevisiae (baker's yeast, species) [taxon 4932], Escherichia coli (E. coli, species) [taxon 562]

## Full text

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## Figures

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## References

234 references — full list in the complete paper: https://tomesphere.com/paper/PMC12913566/full.md

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Source: https://tomesphere.com/paper/PMC12913566