Watershed Informatics provides a bioinformatics platform that automates data analysis across various biological domains, including genomics and proteomics, using customizable workflows and templates. The platform reduces analysis time by 86% and processes 300TB of biological data monthly, enabling researchers to generate insights without extensive coding experience.
Funding
Funding not disclosed
Founders
Product
Problem
Analyzing biological data, including genomics and proteomics, is often a time-consuming and complex process, requiring extensive coding experience and specialized bioinformatics expertise. The manual nature of these analyses can lead to delays in research and hinder the generation of timely insights.
Solution
Watershed Informatics offers a bioinformatics platform designed to automate data analysis across diverse biological domains. The platform utilizes customizable workflows and templates to streamline the analysis process, significantly reducing the time required to generate insights. By automating these tasks, Watershed Informatics enables researchers to efficiently process and analyze large volumes of biological data, even without extensive coding knowledge. The platform's scalable infrastructure and customizable user interface facilitate collaboration and accelerate the pace of biological discovery.
Target Audience
The primary target audience includes researchers in various biological domains, such as genomics, proteomics, and multi-omics, particularly cancer biologists and those involved in drug discovery and development.
Features
- Customizable workflows and templates for various biological data types, including genomics, transcriptomics, proteomics, multi-omics, and high content imaging
- Automated data analysis pipelines that reduce analysis time by up to 86%
- Scalable infrastructure capable of processing over 300TB of biological data monthly
- Support for a wide range of applications, including drug target discovery, biomarker identification, and disease modeling
- User-friendly interface designed to facilitate collaboration between biologists and bioinformaticians
- Integration of Geneformer, a deep-learning model for predicting tissue-specific gene network dynamics
- GPU-enabled biocomputing for rapid execution of complex algorithms
- Unrestricted access to open-source coding tools