Introduction
If 2025 felt busy, that’s because it was. Bioinformatics continued its steady shift from “Can we do this?” to “How do we do this well, at scale, and reproducibly?”
Single-cell datasets kept getting larger. Transcriptomics workflows became more multi-modal. AI crossed the line from hype into tooling people were genuinely experimenting with. At the same time, familiar challenges did not go away. Workflow management, data wrangling, visualization, and choosing the right tool instead of the shiny one all remained front and center.
At Bridge Informatics, our most-read blogs reflected exactly that balance: practical guidance, clear comparisons, and early looks at emerging technologies. Below are our top five most popular blog posts of 2025, counting down to the most-read article of the year.
5. Tied for Fifth Place
Two articles shared the fifth spot in 2025, reflecting strong interest in both the future of AI-assisted coding and the rapidly evolving single-cell ecosystem.
AI Coding Agents in Bioinformatics: A First Look at OpenAI’s Codex
Why it resonated: Curiosity, paired with a healthy dose of skepticism.
AI coding agents started appearing everywhere in 2025, and this post takes a grounded look at what OpenAI’s Codex can and cannot do for bioinformatics workflows. Rather than positioning coding agents as replacements for expertise, the article explores where they can realistically save time, such as boilerplate code, refactoring, and exploratory scripting, and where careful human oversight remains essential.
This was a popular read for teams experimenting with AI tools while still prioritizing correctness and reproducibility.
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Single-Cell Analysis Landscape: Platforms, Trends, and Market Insights
Why it resonated: Single-cell analysis is not slowing down, and neither is the tooling ecosystem.
This article zooms out from individual methods to examine the broader single-cell landscape. It surveys platforms, emerging trends, and market dynamics shaping how single-cell data is generated, analyzed, and commercialized.
For bioinformaticians making strategic decisions about tools, vendors, or long-term skill development, this post provided valuable context beyond day-to-day analysis.
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4. From Pandas to Spark and Back Again: Why Bioinformatics Should Know DuckDB
Why it resonated: Everyone is tired of both overengineering and underengineering.
This post struck a chord with bioinformaticians who routinely work with large tabular datasets. Pandas does not always scale, Spark can be heavy to deploy, and sometimes a simpler solution is exactly what is needed. This article explains where DuckDB fits into that gap and why it is surprisingly powerful for analytical workloads.
It makes a compelling case for DuckDB as a practical middle ground between in-memory Python tools and fully distributed systems.
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3. Battle of the Workflow Managers
Why it resonated: Because everyone has opinions about workflows.
Workflow managers are foundational to modern bioinformatics, and choosing one can feel oddly personal. This post offers a clear, experience-driven comparison of popular workflow managers, including Snakemake, Nextflow, WDL, and CWL.
Rather than declaring a single winner, the article focuses on matching tools to team size, infrastructure, and long-term maintainability. It proved especially useful for teams scaling pipelines or re-evaluating older decisions.
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2. Getting the Most Out of scGPT for Single-Cell Annotation
Why it resonated: Bioinformaticians wanted practical guidance, not just model hype.
Foundation models for biology generated enormous interest in 2025, but applying them effectively remains non-trivial. This article focuses on scGPT and provides a realistic look at how it can be used for single-cell annotation.
The post covers what scGPT does well, where it struggles, and how to think critically about model assumptions when integrating it into existing pipelines. It treats scGPT as a powerful tool, but one that still requires domain knowledge and validation.
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1. Visualizing Transcriptomics Data in Cancer – the most popular blog of 2025!
Why it resonated: Visualization is still where insight either happens or does not.
The most-read Bridge Informatics blog of 2025 tackled one of the most persistent challenges in cancer research: making sense of complex transcriptomics data. This post explores how to visualize bulk and single-cell RNA-seq data in ways that support interpretation rather than obscuring it.
From dimensionality reduction and batch effects to choosing visual encodings that highlight tumor heterogeneity and pathway activity, this article offered practical guidance for turning high-dimensional data into biological insight.
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Looking Ahead
If 2025 taught us anything, it is that bioinformatics is no longer just about analysis. It is about choosing the right abstractions, scaling responsibly, and integrating AI without losing scientific rigor.
We are excited to keep exploring these themes in 2026. If you missed any of the posts above, now is a great time to catch up. If there are topics you would like us to cover next, we would love to hear from you. Click here to get in touch!