Unify your data & Accelerate Innovation with Knowledge Graphs
Unify all of your data, simplify access and unlock insights all using the power of our Knowledge Graph Engine.
Benefits
The Wisecube Knowledge Graph Engine can help unify and synthesize hidden patterns in your private and public data and reveal hidden insights. It can also learn from these patterns and make intelligent predictions based on it. By uncovering insights quickly, you can save days and accelerate innovation.
Go beyond search
Wisecube helps organizations build a connected graph of concepts and evidence from millions of documents and databases uncovering explicit connections and inferring undiscovered links using our cutting edge NLP. Search is just the beginning when it comes to Wisecube.
Find insights faster while staying on top of your research
Biomedical data is growing at an exponential rate and is no longer humanly possible to keep up with it. Wisecube analyzes and synthesizes hundreds of thousands of personalized research papers in your field each day to give you a crystallized picture of your domain. Stay on top of the latest research to understand critical insights needed to unlock the next level of discoveries.
Make novel discoveries by accessing hidden patterns
Wisecube focuses on the things you care about and synthesizes them into easy to understand topics and insights. We use NLP and machine learning to analyze and connect millions of data points from various literature sources and databases so you can keep track of complex research fields.
Technology
Built using cutting edge technology and ground-breaking AI and NLP algorithms on top of our scalable and open AI platform, Wisecube knowledge graph engine is the best of breed application when it comes to analytics.
Advanced NLP
Wisecube helps surface high level research themes and topics to reveal insights in Biomedicine and Healthcare within seconds. The natural language processing (NLP) and AI platform can analyze millions of biomedical publications, clinical trials, protein and chemical databases, all accessible through a user-friendly visual interface.
Comprehensive Knowledge Graph
By synthesizing a variety of data sources, including Biomedical Literature, Chemical, Protein and several side effect databases into the Wisecube Knowledge Graph, Customers can integrate their own proprietary data to discover hidden insights and patterns in existing knowledge bases.
Cutting-Edge Algorithms
Wisecube has developed state of the art AI algorithms that can predict hidden relationships in the knowledge graph built by our open and extensible natural language processing pipelines. This allows us to infer and predict non-obvious relationships between diseases, proteins, compounds and many other biomedical concepts.
Open AI Platform
Wisecube is built on an open and extensible visual AI platform called Nephos. As part of our commitment to the scientific and data science community we not only provide the Wisecube products itself but also the underlying pipeline that we use to build the final graph itself. This means that you can extend it to incorporate your own data sources very easily.
Roche Case Study: Accelerating Biomedical Innovation by Combining NLP and Knowledge Graphs
Biomedical research is hampered by the triple challenges of disjointed data, unstructured data explosion, and lack of accessibility. In this talk, we demonstrate how combining new innovations in NLP and Graph Analytics can act as a potent remedy and accelerate biomedical research, by automatically building knowledge graphs from unstructured documents.
We introduce three techniques to fuse disjointed datasets, analyze them as a whole, surface hidden patterns, and answer concrete research questions.
We also present the biomedical knowledge graph we built in the process, the entities and relations in the database, and how they can be useful for various medical purposes such as clinical decision support and drug discovery.
Who We Are
We are a team of veteran data scientists and engineers that focus on solutions for the Life Sciences Industry. We have been building and operating data driven products and platforms for many decades. We have taken our passion for data and have chosen to apply it in the life sciences domain where we can have a truly life changing impact.
Vishnu Vettrivel
Founder and CEO
Alex Thomas
Principal Data Scientist
Alin Blidisel
Lead Platform Engineer
Dr.Zakaria Cherfaoui
Head of Pharma Solutions
Who We Work With
Frequently Asked Questions
What are the data sources you use?
We build the Wisecube knowledge graph by parsing millions of abstracts and full text publications from MEDLINE™ and PubMed Central™, as well as other structured data sources such as WikiData, ClinicalTrials.gov, Uniprot, CHEMBL and many others. Additional proprietary content can be added to the platform through partnerships with publishers, or the internal document holdings of our Enterprise customers.
Do you process data from tables and illustrations?
How do you account for research that may not be accurate or reproducible?
Can you integrate 3rd party data sources such as patents, proprietary documents and databases?
Yes, we have integrated several 3rd party databases. New data sources are continuously being added to the platform. Please contact us if you would like to know what is planned next or would like to add a custom or proprietary data source. Also being an open platform, it is also possible for your data science team to use the Wisecube Knowledge Graph Engine pipeline to extend it.
Is my data secure with Wisecube Knowledge Graph Engine ?
How are you different than WikiData ?
In addition to incorporating the life sciences subset of WikiData, We also incorporate additional data from Clinicaltrials.gov, and inferred relationships from Pubmed. Even though there is some clinical trials data in WikiData, but it is often missing important elements, for e.g. links to the condition or intervention or links to outcomes.
Have you conducted any quality checks to ensure your Knowledge graph is reliable ?
Yes, we take quality very seriously. We ensure reliablity in multiple ways:
- We work with Wikidata and Semantic Data experts who have contributed a lot to WikiData who has come up with an extensive test set to validate the graph.
- We use existing sample queries used by WikiData to validate comparative quality.
- Finally, we compare our graph results to other knowledge graphs to ensure quality and reliablity.
How does information around clinical trials, conditions, and interventions get added to your Knowledge Graph?
We have built a custom parser that can extract specific information from clinical trials using state-of-the-art NER (Named Entity Recognition) models. We then fuse this with the underlying information from WikiData to provided augmented clinical trial entities.
What are the data sources you use?
We build the Orpheus knowledge graph by parsing millions of abstracts and full text publications from MEDLINE™ and PubMed Central™, as well as other structured data sources such as Uniprot, CHEMBL and many others. Additional premium content can be added to the platform through partnerships with publishers, or the internal document holdings of our Enterprise customers.
Do you process data from tables and illustrations?
No, at this moment we focus exclusively on deriving insights from Natural Language processing of Textual data and fusing it with structured databases.
How do you account for research that may not be accurate or reproducible?
This is a hard problem, but we do have mechanisms that allow us to weigh insights from various research papers based on various factors including the credibility of the journal, author, citations and others.
Can you integrate 3rd party data sources such as patents, proprietary documents and databases?
Yes, we have integrated several 3rd party databases. New data sources are continuously being added to the platform. Please contact us if you would like to know what is planned next or would like to add a custom or proprietary data source. Also being an open platform, it is also possible for your data science team to use the Orpheus pipeline to extend it.
Is my data secure with Orpheus?
Yes. We have decades of experience securing cloud based platforms and making it compliant with the strictest of regulations. We take the security of our users’ data very seriously and have taken the utmost care in securing our platform and user data.
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Explore patterns, uncover insights and make discoveries in your research area using the power of AI.
