BioBox Platform

Graph Data System for Biology

90% of drug programs fail often due to inappropriate target selection. BioBox helps scientists construct and manage knowledge graphs, query it, and develop custom target prioritization systems to zero-in on high-value targets quickly in an evidence-based way.

Trusted by scientists
Technology

Build a graph, run algorithms, get scores.

A new data-layer that harnesses the power of both technologies to make biological data-mining easy.

Foundation Graphs

Unify data sources and assets into a fully connected knowledge graph.

Scoring Algorithms

Craft custom scoring systems using any pattern in the graph to objectively and systematically mine your graph for novel insights.

How it works

It's easy to start

Start mining your data in 3 easy steps.

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1. Define your Ontology

Construct an ontology to capture the semantic concepts, relationships, and properties needed to model scientific information in your own way.

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2. Connect your data

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.

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3. Get results

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

More features

All the tools you need

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Data Dashboards

Share a compelling narrative with your team. Leverage collaborative, interactive and customizable multi-omic dashboards to explore large cohorts of data.

Experience a new way to converse with your data

Get answers based on evidence, not hallucinations.

Solutions

Use cases

Learn more about how modern biotechs are deploying BioBox to hit R&D milestones and make mission-critical decisions with confidence.

Target Identification

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.

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Evaluate Feasibility
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Establish Causality
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Public Data Access
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Evidence Ranking

Target Prioritization

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.

Custom Scoring
Hypothesis Testing
Causality Modelling
Multi-omic data integration

Drug Repurposing

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.

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Market Expansion
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Causal Inference
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Predict Outcomes
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Find Indications