# Beyond volume and toward coherence: a research parasite’s perspective

## TL;DR

This paper discusses how reanalyzing existing datasets can lead to new biological insights beyond just data volume.

## Contribution

The paper introduces a perspective on how secondary analysis modes can enhance biological discovery through dataset coherence.

## Key findings

- Meaningful discovery comes from understanding dataset limitations and capabilities.
- Integrating complementary datasets can provide deeper biological insights.
- Secondary analysis modes vary from single omics layer mining to multi-dataset integration.

## Abstract

The Pacific Symposium on Biocomputing recognized my work with the 2024 Junior Research Parasite Award, an honor established to highlight the scientific value of reanalyzing, integrating, and reinterpreting existing datasets. The award invites recipients to reflect on the role of research parasites within the broader ecosystem of computational biology and data reuse. For me, this perspective is rooted in years of working across diverse -omics datasets, where I’ve seen firsthand how the structure, resolution, and context of a dataset shape the biological insight it can support. Rather than focusing on data volume alone, meaningful discovery often emerges from understanding what each dataset can—and cannot—reveal. Here, I outline how different modes of secondary analysis, from integrating complementary datasets to deeply mining a single omics layer.