Slack / Private Message Drop — page 143

[2020-08-22 16:12:51] [Kristian Andersen] Didn't see that - link? [2020-08-22 16:13:43] [Eddie Holmes] https://twitter.com/BallouxFrancois/status/1297207044664184832?s=20 [2020-08-22 16:20:28] [Kristian Andersen] Yeah.... can't really dismiss potential passage or engineering based on a circular tree. I'm glad he's found his community on Twitter though - the highlight of any career. Surely. [2020-08-22 16:27:03] [Eddie Holmes] Surely. He's one a whole set of people who let Twitter go to their head. [2020-08-22 16:46:05] [Kristian Andersen] Very few have made that transition successfully - there are a handful though, like Natalie Dean who's managed to stay remarkably on point. [2020-08-22 17:10:20] [Eddie Holmes] I draw the line at one who thinks they're living out a Camus novel. [2020-08-22 17:18:13] [Kristian Andersen] You're sooo old man :stuck_out_tongue_winking_eye: [2020-08-22 18:47:48] [Eddie Holmes] You're not wrong. Papers with Camus quotes should automatically be rejected. [2020-08-23 15:29:49] [Eddie Holmes] This photo I just took seems strangely profound - even the dog has abandoned The Donald... [shared file(s): IMG_1361.JPG] [2020-08-24 04:10:15] [Andrew Rambaut] Koonin doing mad stuff again... ```Prediction of the incubation period for COVID-19 and future virus disease outbreaks Ayal B Gussow; Noam Auslander; Yuri I Wolf; Eugene Koonin Research article Abstract: Background: A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. During the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well-being and the global economy. However, the biological factors that determine the duration of the virus incubation period remain poorly understood. Results: We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features such as the number of protein-coding genes and the GC-content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine