How Modular Pipelines are Changing Bioinformatics

Alper Kucukural, PhD

CTO, ViaScientific

Simplifying complex workflows with Via Foundry’s Lego®-like approach

As life scientists, we know the “elephant in the room” isn’t biology — it’s the data. Traditional research methods reliant on spreadsheets, bespoke code, and manual integration of various tools are not sustainable. These methods are time-consuming to construct, error-prone, and expensive to maintain.

The inefficiency of traditional bioinformatic processes slows research, hinders reproducibility, and reduces collaboration, forcing researchers to recreate new pipelines for each project. This is both costly and unsustainable.

Via Scientific’s Via Foundry, a multi-omics accelerator platform, addresses these issues by transforming complex data processes into modular, reusable workflows that are sustainable, shareable, and ensure reproducibility.

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The Modular Approach

Pipelines today are deeply complex, often requiring thousands of lines of code to support multi-omics scientific exploration. While powerful, this complexity is the Achilles heel of scientific advancement.

However, complexity is not a necessary state; it can be eliminated through abstraction and modularity. The perfect analogy is the ubiquitous Lego® brick. We are all familiar with the incredibly complex models that can be quickly made with Lego® bricks. The magic of the “brick” is that it abstracts away complexity and modularizes the process, allowing the user to focus on their end goal without creating and customizing each brick.

Via Foundry does the exact same thing for bioinformatics — but with code. Via Foundry has transformed pipeline creation and support into our version of the Lego® brick: simple yet powerful — input, output, script. These terms are Via Foundry’s Lego® bricks. With this abstraction, Via Foundry modularizes the complex, empowering you to rapidly build any pipeline necessary to support your scientific journey with unmatched speed, reusability, reproducibility, and shareability.

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Why Modularity Matters

Speed: Rapidly assemble workflows like Lego® structures, accelerating development and delivering timely results critical for research and clinical applications.
Reusability: Reuse pipelines across projects, saving time and resources. Build upon previous work, boosting efficiency and innovation.
Reproducibility: Achieve consistent results with Via Foundry’s reliable framework. Replicate experiments accurately, validating findings and advancing scientific knowledge.
Future-Proofing: Adapt to new challenges and advancements. Incorporate new techniques and tools without overhauling your system.
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Why Via Foundry Stands Out

Seamless Integration: Via Foundry’s pipelines connect effortlessly, simplifying complex processes. Integrate metadata from third-party applications and execute pipelines on various platforms, including AWS, Google Cloud, and on-premises servers.
Enhanced Collaboration: Modular pipelines improve collaboration, allowing researchers to work simultaneously on different project aspects. This accelerates progress and fosters a dynamic research environment.
FAIR Data Sharing: Adheres to FAIR principles, facilitating seamless data sharing and collaboration. Ensure data is well-documented and standardized, increasing transparency, reproducibility, and potential for new discoveries.

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Real-World Impact

Via Foundry’s modular pipelines have significantly boosted research efficiency and outcomes. Explore a few recent success stories:

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A Future Built on Strong Foundations

Modular pipelines are revolutionizing bioinformatics research. Via Foundry’s Lego®-like approach ensures speed, reusability, reproducibility, and future-proofing, empowering researchers to streamline workflows, enhance collaboration, and drive scientific discoveries.

Learn more about Via Foundry and discover how modular pipelines can revolutionize your research. Build your bioinformatics research brick by brick and transform your processes with unprecedented efficiency and reliability.

Alper Kucukural, PhD

CTO of ViaScientific, and Associate Professor at UMass Chan Medical School. I specialize in bioinformatics, machine learning, and large-scale systems.