MantleBio develops a cloud-based platform that integrates data management and analysis tools for biological research, enabling scientists to organize, analyze, and share complex datasets without extensive setup. The platform addresses the inefficiencies in data handling and collaboration in biotech, providing ready-to-run workflows and a centralized database for reproducible research.
Funding
Funding not disclosed
Founders
Product
Problem
Biological research faces challenges in managing and analyzing complex datasets, often relying on disparate tools and manual processes. This leads to inefficiencies in data handling, difficulties in collaboration, and a lack of reproducibility in research findings.
Solution
MantleBio offers a cloud-based platform that integrates data management, analysis tools, and collaboration features specifically designed for biological research. The platform provides scientists with a centralized workspace to organize, analyze, and share complex datasets without extensive setup or coding expertise. Ready-to-run workflows and a unified database enable reproducible research, accelerate data-driven discovery, and streamline the transition from ad-hoc exploration to reusable analyses. By connecting data, computation, and teams, MantleBio aims to close the gap between data and discovery in the life sciences.
Target Audience
MantleBio's primary customers are scientists, researchers, and data scientists in biotech, pharmaceutical, and academic institutions who require a unified platform for managing, analyzing, and collaborating on biological data.
Features
- Cloud-based platform accessible from any web browser, eliminating the need for local software installations.
- Ready-to-run workflows for common biological analyses, including bulk RNA sequencing, spatial transcriptomics, and fluorescence microscopy.
- Integrated data management system for organizing and storing biological data and metadata in a searchable and accessible format.
- Python notebooks designed for scientific research, enabling reproducible and reusable analyses with captured environments.
- No-code pipelines for analyzing data directly from the browser or through a Python SDK.
- Collaboration features for sharing data, notebooks, and pipelines with teammates.
- Integrations with Benchling, AWS, Nextflow, and GitHub for seamless data exchange and workflow automation.