Identifying a target, designing an asset and submitting it for IND is a 5-6 multi-million dollar process that involves many high impact data driven decisions. We provide teams with a platform identify complex patterns across multi-modal data to make these decisions efficiently and with confidence
A new data-layer that harnesses the power of both technologies to make biological data-mining easy.
Unify data sources and assets into a fully connected knowledge graph.
Craft custom scoring systems using any pattern in the graph to objectively and systematically mine your graph for novel insights.
Start mining your data in 3 easy steps.
Construct an ontology to capture the semantic concepts, relationships, and properties needed to model scientific information in your own way.
Leverage API integrations include REST services to stream in data from s3 and gcs. Hook up your workflows to connect the outputs to the platform.
Let the platform work its magic. Sit back and watch your sequencing data self-organize into a semantic knowledge graph and search it with the Knowledge Engine
Share a compelling narrative with your team. Leverage collaborative, interactive and customizable multi-omic dashboards to explore large cohorts of data.
Tools to wrangle, process, and analyze multi-omics data, including Bulk RNAseq, scRNAseq, WGS, WES, ChIP-seq and more.
Developers
REST API to connect the BioBox platform to internal tools.
Public Data
Instantly access over 85,000 analysis ready publicly available sequencing datasets from TCGA, GEO, SRA, and more.
Get answers based on evidence, not hallucinations.
Learn more about how modern biotechs are deploying BioBox to hit R&D milestones and make mission-critical decisions with confidence.
Identify and prioritize disease specific targets. Obtain a comprehensive understanding of the biological underpinnings of a disease. Compare and contrast targets identified in the public domain and in your proprietary data.
Find compelling evidence across public and private data to support the efficacy of a target. Identify target and disease relationships across multi-omic observations. Share findings and collaborate with team members.
Find additional indications for your therapeutic asset to expand its value. Use the BioBox Knowledge Engine to create in-silico models and uncover hidden connections between drug and diseases.