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Making Sense of Multiomics Data

The use of multiomics technologies and analysis for research continues to expand in academia and across industry. Multiomics assays measure multiple sources of biological…

J.P. Morgan 2026: From AI Hype to ROI

It wasn’t foggy, but sunny. The literal clouds cleared over San Francisco last week, and with them, the ‘AI fog’ of hype finally lifted at the 44th J.P. Morgan Healthcare…

Turning R&D Into Scalable, Reproducible Solutions

At this year’s NextGen omics conference in London, we explored one of the most persistent challenges in bioinformatics: how to transform fast-moving R&D work into workflows…

Single-Cell: Where Machine Learning Meets Biology

Single-cell analysis stands at the intersection of machine learning (ML) and biology, with advances in microfluidic technology generating massive datasets that are ideal for …

Robrecht Cannoodt

Re-thinking user-friendly computational workflows

Modern-day computational workflows often combine tens to a hundred different computational steps. These include off-the-shelf bioinformatics tools, trusted open source…

Easy H5AD access in R with anndataR

A best practices approach to single-cell analysis requires combining methods from the three major ecosystems: scverse for Python and Bioconductor or Seurat for R. Each of…

How to Avoid the GitHub Graveyard?

Each summer a familiar scene repeats itself across research groups and R&D units: students graduate, postdocs move on, contractors wrap up. Along with them vanishes a wealth…

Webinar: Mastering Bioinformatics Data Workflows

On May 15, we hosted a free webinar that brought together deep technical insights and real world experience on how to build robust, sustainable and efficient bioinformatics…

Mastering Bioinformatics Tool & Workflow Management with Viash

Are you a bioinformatician tired of spending hours configuring environments, debugging container arguments, or struggling with complex workflow maintenance? Our…

Why modern omics data projects need better workflow tools

In today’s fast-paced research and development environments, the ability to build, maintain and scale data processing workflows efficiently isn’t just a technical necessity…

10 Common pitfalls in omics data processing

In today’s data-driven world, efficiently processing and analyzing large volumes of biological data is crucial for organizations to maintain a competitive edge and foster…

Data Intuitive fuels Tabula Sapiens v2

We’re thrilled to share the exciting news of the Tabula Sapiens v2 preprint launch on bioRxiv! 🎉 Data Intuitive is proud to have played a key role in this groundbreaking…

Robrecht Cannoodt

Navigating the use of LLMs for Code Generation

Data Intuitive is committed to streamlining bioinformatics workflow development processes. Our core tool, Viash¹, was developed to simplify and standardize computational…

Standardizing Benchmarks in Spatial Omics with OpenProblems

Spatial omics is an emerging field that is allowing researchers to unravel the complexities of cellular organization and function within their native tissue context. Given…

Sai Nirmayi Yasa

Technical overview: how Viash works in practice

Viash is a command-line tool that transforms scripts into self-contained, reusable and reproducible components.

Running OpenPipeline on public data

Effortlessly execute Openpipeline workflows from its open-source repo using a straightforward, user-friendly process on nf-tower

Explainer animation Viash

1 minute explainer video about the possibilities of Viash

Why use Nextflow and Viash?

Nextflow is a leading workflow manager in computational biology, known for its portability, scalability, and reproducibility. However, developing workflows can be…

Viash Basics Demo

Watch our screencast demonstration to see the getting started script of Viash.io in action.

GitHub Action: Reclaim The Bytes

In the dynamic world of data science and software development, making efficient use of available resources is not just an option but an absolute necessity. In a lot of our…

Robrecht Cannoodt

anndata: annotated data in R

anndata is a commonly used Python package for keeping track of data and learned annotations, and can be used to read from and write to the h5ad file format. It is also the…

Robrecht Cannoodt

Dynverse: Inferring trajectories using dyno

Dynverse, utilizing the ‘dyno’ package, is a state-of-the-art framework designed for inferring cellular trajectories from single-cell RNA sequencing data. It offers a…

Robrecht Cannoodt

A Practical Approach to Model Error - Part 2

It’s been a while since I first wrote about tackling model error using a simple model. It’s about time to come back to it.

A Practical Approach to Model Error

In this post, I want to get a better sense of the effects of model error by simulating a very simple model for the spreading of a virus. It’s based on an analysis performed…

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