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JADBio

By JADBio
5.0/54 reviews

No-code AutoML platform that helps life science researchers build predictive models and find biomarkers.

AutoMLBiomarker DiscoveryLife SciencesNo-Code ML
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Overview

What is JADBio?

JADBio, short for Just Add Data Bio, is a no-code automated machine learning platform for biomedical and life science research. It runs automated pipelines for preprocessing, feature selection, model training, and validation on high-dimensional data, supporting classification, regression, survival, and single-cell analysis. It returns compact feature signatures for biomarker discovery. Bioinformaticians, biologists, clinical researchers, and academic labs use JADBio to build predictive models and biological insights without programming or deep data science expertise.

Best for
BioinformaticiansLife Science ResearchersClinical ResearchersAcademic LabsBiotech Companies
Product snapshot
Category
Data Mining & Discovery
Best for
Biomedical predictive modeling
Deployment
Cloud
Free trial
Yes
Integrations
REST API, Python client
AI features
Yes
Key features

Key features of JADBio

Automated model creation

Runs full machine learning pipelines from data upload to validated model.

Feature selection

Finds small sets of predictive features useful as biomarker signatures.

Survival analysis

Models time-to-event outcomes alongside classification and regression tasks.

High-dimensional data

Handles datasets with up to about one million features.

Shareable results

Shares analysis results through links without requiring recipient accounts.

Open API

Automates analyses through a REST API and Python client.

Reviews

JADBio reviews

4 reviews

Overall

5.0/5

  • Ease of use4.8/5
  • Features4.8/5
  • Value for money5/5
  • Customer support5/5

What users like

  • Very easy to use
  • Fast results with minimal input
  • No bioinformatics expertise required
  • Compact models that avoid overfitting

What users dislike

  • No deep learning methods
  • Hard to use with time series
  • Pricing not published online
  • Narrow focus on life sciences

Buse S.

IT Manager

“Liked the fast data processing with minimal input, which helped build biosignatures. Found that deep learning methods are not applied in the analyses.”

Ekaterini C.

Professor

“Liked needing no bioinformatics expertise, models with few selected features, no overfitting, and biological insight. Found it lacks a full pipeline from data acquisition to scientific conclusions.”

Grigoris A.

Professor

“Liked how straightforward the platform is and the strong results it delivered for AI in mental health projects. Noted no major drawbacks.”

Vasiliki D.

Director of Healthcare Department

“Liked that it is very easy to use and returns results quickly. Found that requiring one sample per row makes time series data hard to use, and deep learning is missing.”

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Integrations

JADBio integrations

JADBio offers an Open API across its plans, giving teams a REST API to upload data, start analyses, and retrieve models and results programmatically. A Python client published on GitHub and a documentation portal support scripted workflows, so bioinformatics teams can call JADBio from their own pipelines and notebooks. The platform is also listed on AWS Marketplace. It accepts tabular data such as omics, clinical, and single-cell datasets, and trained models can be exported for use elsewhere. Results can be shared with colleagues through links without requiring them to hold accounts. Deeper connectors to lab systems or data warehouses are not documented, so buyers should confirm with the vendor.

FAQ

Frequently asked questions about JADBio