We’re very pleased to announce our recent fundraising round, led by OliveTree Ventures. Although sequencing costs are below $1000, interpretation is still a major bottleneck to widespread adoption of NGS testing and that’s where we’re focusing our efforts. Here’s the full press announcement, detailing the whys and hows: February 19th, 2019, Palo Alto, California -- [...]
May you live in interesting times seems like an apt description for the year we’ve had in genomics. Significant advances in science, alongside ethical breaches and major privacy concerns. All the while, the sequencing march forward continues with more interest from countries, consumers and more insurance coverage.I polled the Emedgene team on the most significant [...]
Introduction Reanalysis. With demand for testing accelerating, this is quickly becoming a painful topic for labs. Every patient matters, and deserves the latest science can offer. But reanalyzing an ever-growing number of cases is unsustainable in the long run. If 50% of your cases are unsolved, and you revisit them every 6 or 12 months, [...]
In our previous post, NLP & Genomics: Play with a full deck, we covered all the reasons we want to use Natural Language Understanding to extract unstructured information from genomics publications. We also demonstrated the kinds of information we’re able to extract with our own NLP. In this post, we’re going to cover some of [...]
The Emedgene AI knowledge graph currently holds 28M+ genomics-related publications. Yes, that’s not a typo, over 28 million. Our goal is to hold a current representation of the entire body of genomics knowledge in our AI knowledge graph. A complete and continuously updated web of variants, genes, pathways, phenotypes, and diseases. Information in publications [...]
Front Line Genomics have done an amazing job creating the Genomic Data 101: 2018 Edition. This thorough introduction to genomic data covers everything from generation, data analysis, storage and compression through use of AI to scale interpretation efforts. The exponential growth in genomic data has strained resources - from both a computing, infrastructure, storage and [...]
