Data science Archives

Addressing common challenges with Knowledge Graphs

In this blog we describe the pivotal role of semantic enrichment in the creation of effective Knowledge Graphs, and illustrate how semantic Knowledge Graphs help answer complex scientific questions.
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Using the SciBite knowledge graph to explore biomedical literature

“Do you have a pre-made knowledge graph covering biomedical literature?” is a question we often hear at SciBite. The answer is yes we do, and in this blog post we’ll describe what our SciBite Knowledge Graph is, its content and the types of questions it can answer.
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What is a Semantic Knowledge Graph?

At a time where more and more of our customer projects revolve around knowledge graph creation, we thought it was about time we blogged on what exactly a knowledge graph is and explain a bit more about how our semantic enrichment technology is being used to facilitate the production of such a powerful data model.
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The 12 days of Machine Learning tips for creating labelled training data

On the first day of Christmas SciBite gave to me... 12 top tips for creating labelled Machine Learning training data.
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The pivotal role of semantic enrichment in the evolution of data commons

In this blog post, discover how Pfizer have integrated SciBite’s semantically enriched vocabularies into their Data Commons project, which has the goal of enabling scientists to develop and refine hypotheses by investigating correlations between genetic and phenotypic data.
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Of burns and bums: Machine Learning surprises!

As many of our regular visitors will know, the focus of our work here at SciBite is unlocking the knowledge held in the vast amount of biomedical text researchers have access to. Sometimes this yields well, interesting, results...
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Drug repurposing, rare diseases and semantic analytics

In this blog we cover how to look potentially reduce the cost of and speed up the repurposing pipeline.
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Machine Learning and phenotype triangulation

Disease detective part 3: In our final disease detective article, we’ll take Part 2’s topic a little further and zoom in on how we can find new relationships between diseases where direct evidence is sparse.
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Exploring mechanistically-related diseases through shared phenotypic profiles

Disease detective part 2: Today, we’ll look at a fresh way of enabling scientific researchers, either in pharmaceutical R&D or in medical institutes to deepen their investigations and consider new links.
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The Relationship Game – Knowledge Graphs

Scientific knowledge can be represented as relationships between things. Thousands or millions of such relationships make a knowledge graph or network analysis. SciBite technology enables extraction of these relationships, and in doing so, can uncover knowledge that might otherwise have remained hidden
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