6 ms·

Impressive if true, although I am very sceptical of the results. The real test is to put their neck on the line and predict/warn of the next significant variant

by axg11 5y ago

Impressive if true, although I am very sceptical of the results. The real test is to put their neck on the line and predict/warn of the next significant variant. If the authors are not willing to do this, I doubt that the algorithm is useful. As a side note, the first author on this paper is the CEO of InstaDeep. I see it as a red flag that the CEO of a 150+ person company would put themselves as first author on this paper. Perhaps I'm unfairly judging and the CEO really was the lead contributor to the study.

mlindner 5y ago
> As a side note, the first author on this paper is the CEO of InstaDeep. I see it as a red flag that the CEO of a 150+ person company would put themselves as first author on this paper. Perhaps I'm unfairly judging and the CEO really was the lead contributor to the study. Authors on scientific papers are ordered by name, so whoever's name is first is pure coincidence.
- axg11 5y ago
  This isn't true for the field of biology or medicine. If you take a look at the order of authors on the paper in question you can also see that the ordering is not alphabetical.
- gpm 5y ago
  The order of authors varies by field. I believe in biology it usually starts with the person who did most of the work (or people, but if more than one it's explicitly noted), everyone who contributed in the middle, principal investigator (i.e. head of lab) last. In this case I notice that they first sorted all the instadeep people to the front, and biontech people to the end... not sure what I'm supposed to take away from the ordering, but it's not random.
  - meepmorp 5y ago
    Or sometimes PI first, depending on the scope of the PI's ego
  - orintorynchus 5y ago
    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 contribution areas.
orintorynchus 5y ago
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 been verifying all our predictions experimentally, post factum. And the method is purely data driven - with no fitting to the experiments or observations. The first author came up with the approach, participated in analysis and got his hands dirty as everyone else. While he is a CEO of a 160+ person company, this has been a labor of love for all of us, done to a large extent in the evenings, during weekends and holidays. It is indeed an unusual situation. But this was not a regular project and InstaDeep is not a regular company either.
- whycombagator 5y ago
  Thank you for chiming in. It’s great that you detected them. I’m curious how many false positives you had during that same time? Did you detect many others that just didn’t pan out to be of significance?
  - orintorynchus 5y ago
    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 with Omicron. However, there are lineages, which are prospectively dangerous, that we detect. As the classification is relative, there is no fixed threshold beyond which we would call for alert. In the evaluation, we have been looking at 20 sequences per week, as this was roughly the testing capacity of our partners. Going for ONE sequence a week makes us detect some variants a bit later, but still. The sequences and lineages we predicted to be of interest were predominantly spreading afterwards. Some were just a blip on the radar, though. We aimed at sensitivity and not missing ominous signs, rather than specificity. NB: Each week there are thousands (now 12k+) new sequence variants. Out of them we consider 20. And detect most of the variants as early on as on the first day.
- zxexz 5y ago
  Wow, amazing to see you here. I have somewhat of a bioinformatics background, and this is the sort of work that I always found very interesting - do you think your team will produce some sort of high level architectural and process breakdown at some point?
jdavis703 5y ago
Because of both founder effects and potentially people taking earlier containment actions, I’m unsure that’s a realistic measure. It’s like how people said Y2K was just a conspiracy theory because most systems kept running — without realizing the early warnings and preparations is the reason Y2K wasn’t a civilizational disruption.

by axg11 5y ago

mlindner 5y ago

> As a side note, the first author on this paper is the CEO of InstaDeep. I see it as a red flag that the CEO of a 150+ person company would put themselves as first author on this paper. Perhaps I'm unfairly judging and the CEO really was the lead contributor to the study. Authors on scientific papers are ordered by name, so whoever's name is first is pure coincidence.

axg11 5y ago
This isn't true for the field of biology or medicine. If you take a look at the order of authors on the paper in question you can also see that the ordering is not alphabetical.
gpm 5y ago
The order of authors varies by field. I believe in biology it usually starts with the person who did most of the work (or people, but if more than one it's explicitly noted), everyone who contributed in the middle, principal investigator (i.e. head of lab) last. In this case I notice that they first sorted all the instadeep people to the front, and biontech people to the end... not sure what I'm supposed to take away from the ordering, but it's not random.
- meepmorp 5y ago
  Or sometimes PI first, depending on the scope of the PI's ego
- orintorynchus 5y ago
  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 contribution areas.

orintorynchus 5y ago

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 been verifying all our predictions experimentally, post factum. And the method is purely data driven - with no fitting to the experiments or observations. The first author came up with the approach, participated in analysis and got his hands dirty as everyone else. While he is a CEO of a 160+ person company, this has been a labor of love for all of us, done to a large extent in the evenings, during weekends and holidays. It is indeed an unusual situation. But this was not a regular project and InstaDeep is not a regular company either.

whycombagator 5y ago
Thank you for chiming in. It’s great that you detected them. I’m curious how many false positives you had during that same time? Did you detect many others that just didn’t pan out to be of significance?
- orintorynchus 5y ago
  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 with Omicron. However, there are lineages, which are prospectively dangerous, that we detect. As the classification is relative, there is no fixed threshold beyond which we would call for alert. In the evaluation, we have been looking at 20 sequences per week, as this was roughly the testing capacity of our partners. Going for ONE sequence a week makes us detect some variants a bit later, but still. The sequences and lineages we predicted to be of interest were predominantly spreading afterwards. Some were just a blip on the radar, though. We aimed at sensitivity and not missing ominous signs, rather than specificity. NB: Each week there are thousands (now 12k+) new sequence variants. Out of them we consider 20. And detect most of the variants as early on as on the first day.
zxexz 5y ago
Wow, amazing to see you here. I have somewhat of a bioinformatics background, and this is the sort of work that I always found very interesting - do you think your team will produce some sort of high level architectural and process breakdown at some point?

jdavis703 5y ago

Because of both founder effects and potentially people taking earlier containment actions, I’m unsure that’s a realistic measure. It’s like how people said Y2K was just a conspiracy theory because most systems kept running — without realizing the early warnings and preparations is the reason Y2K wasn’t a civilizational disruption.