Not exactly "finding out", but rather estimating. It's all about prioritizing testing through detecting suspiciously "good" and unexpected outliers popping up.
That's the key bit here. Supervised learning is not applicable here and any sort of fitting to known labels is doomed to fail. The system is not calibrated, tuned or parameterized. The ML part learns in a…
The idea is to introduce a bit of sanity into the current world, to calm down overreactions to every new, scary looking variant. And on the flip side - to identify the truly scary ones early on, so that proper measures…
We are actively looking for motivated colleagues. Feel free to look at the page above or drop us an email at hello[at]instadeep.com. We are also happy to make new friends and work together on exciting projects - same…
The method, in its current incarnation, is detecting dangerous variants and not foreseeing them. We can use the same approach to forecast plausible developments, but there are so many latent variables (intrapatient…
I am sure we will, in due time. If you have any particular hopes or wishes, we will try to accommodate as much as we can.
This is something that amazes me. Any time a true High Risk Variant appears, it is clear as day in the system. This was the case with Lambda, Mu (which we predicted to have a limited propensity to proliferate), and now…
The system is constantly learning, so it "retunes" itself. We can infer epitopes from structure, but we found that data derived from known complexes is sufficient for our purpose. Current version of EWS does not…
What we hope for is rather informing the public policy. Now, any time a scary looking variant is sequenced, there is some public commotion, uncertainty about the future repercussions. We want to be able to gauge the…
Well, there is a lot of overlapping nomenclature. Here by variant we understand any sample, which is not identical sequence-wise to sequences seen before. Most of the observed mutations are innocuous and do not lead to…
It is not random. InstaDeep has designed, developed, built, benchmarked the method. BioNTech performed experimental validation, provided expert insight into the problem domain. Hence, authors are segmented by…
I am the second author of the paper. We have been putting our head on the line for the last half a year. We detected Lambda, Mu (with a caveat, that we did not consider it competitive) and Omicron - all blindly. We have…
Not exactly "finding out", but rather estimating. It's all about prioritizing testing through detecting suspiciously "good" and unexpected outliers popping up.
That's the key bit here. Supervised learning is not applicable here and any sort of fitting to known labels is doomed to fail. The system is not calibrated, tuned or parameterized. The ML part learns in a…
The idea is to introduce a bit of sanity into the current world, to calm down overreactions to every new, scary looking variant. And on the flip side - to identify the truly scary ones early on, so that proper measures…
We are actively looking for motivated colleagues. Feel free to look at the page above or drop us an email at hello[at]instadeep.com. We are also happy to make new friends and work together on exciting projects - same…
The method, in its current incarnation, is detecting dangerous variants and not foreseeing them. We can use the same approach to forecast plausible developments, but there are so many latent variables (intrapatient…
I am sure we will, in due time. If you have any particular hopes or wishes, we will try to accommodate as much as we can.
This is something that amazes me. Any time a true High Risk Variant appears, it is clear as day in the system. This was the case with Lambda, Mu (which we predicted to have a limited propensity to proliferate), and now…
The system is constantly learning, so it "retunes" itself. We can infer epitopes from structure, but we found that data derived from known complexes is sufficient for our purpose. Current version of EWS does not…
What we hope for is rather informing the public policy. Now, any time a scary looking variant is sequenced, there is some public commotion, uncertainty about the future repercussions. We want to be able to gauge the…
Well, there is a lot of overlapping nomenclature. Here by variant we understand any sample, which is not identical sequence-wise to sequences seen before. Most of the observed mutations are innocuous and do not lead to…
It is not random. InstaDeep has designed, developed, built, benchmarked the method. BioNTech performed experimental validation, provided expert insight into the problem domain. Hence, authors are segmented by…
I am the second author of the paper. We have been putting our head on the line for the last half a year. We detected Lambda, Mu (with a caveat, that we did not consider it competitive) and Omicron - all blindly. We have…