Synopsis of Social media discussions
Several discussions praise the publication as a 'favourite paper of 2017,' emphasizing its innovative approach to protein structure determination using metagenome data. The tone ranges from simple endorsements to mentioning potential applications, showing a balanced mixture of appreciation and curiosity.
Agreement
Moderate agreementMost discussions express positive or supportive views towards the publication, reflecting general agreement with its significance.
Interest
Moderate level of interestThe posts show moderate curiosity, with some highlighting the importance of the research and its innovative methods.
Engagement
Moderate level of engagementParticipants are engaging by referencing specific aspects like methods and implications, but the depth is somewhat superficial.
Impact
Moderate level of impactThere is recognition that the work could be influential, especially in fields like protein research and therapeutics, indicating a moderate impact.
Social Mentions
YouTube
3 Videos
Bluesky
1 Posts
5 Posts
8 Posts
Blogs
6 Articles
News
15 Articles
2 Posts
Metrics
Video Views
1,398
Total Likes
53
Extended Reach
51,893
Social Features
40
Timeline: Posts about article
Top Social Media Posts
Posts referencing the article
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RT @jgreener64: Favourite paper of 2017 "Protein structure determination using metagenome sequence data" by Ovchinnikov et al. (1/4) http…
view full postJanuary 8, 2025
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Joe Greener
@jgreener64.bsky.social (Bluesky)Favourite paper of 2017 "Protein structure determination using metagenome sequence data" by Ovchinnikov et al. (1/4) www.science.org/doi/10.1126/...
view full postJanuary 8, 2025
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Joe Greener
@jgreener64 (Twitter)Favourite paper of 2017 "Protein structure determination using metagenome sequence data" by Ovchinnikov et al. (1/4) https://t.co/lYThcWxeOZ https://t.co/7jVGXHkopc
view full postJanuary 8, 2025
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adhara_mathphys
@adhara_mathphys (Twitter)RT @m_sekijima: @biochem_fan 下記とか?! https://t.co/bNc0j7EY1v https://t.co/SSZvxWYHT8 https://t.co/Vo7ug4oJXV 識者の @Ag_smith さん、どうでしょうか。
view full postOctober 9, 2024
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tny
@tny_twtr (Twitter)RT @m_sekijima: @biochem_fan 下記とか?! https://t.co/bNc0j7EY1v https://t.co/SSZvxWYHT8 https://t.co/Vo7ug4oJXV 識者の @Ag_smith さん、どうでしょうか。
view full postSeptember 18, 2024
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Masakazu Sekijima
@m_sekijima (Twitter)@biochem_fan 下記とか?! https://t.co/bNc0j7EY1v https://t.co/SSZvxWYHT8 https://t.co/Vo7ug4oJXV 識者の @Ag_smith さん、どうでしょうか。
view full postSeptember 18, 2024
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Yongchan Lee
@YongChan_zzz (Twitter)RT @sokrypton: @eugenevalkov In the past, we even called it "Protein structure determination" cus the signal you get from MSA/coevolution (…
view full postNovember 13, 2021
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Sergey Ovchinnikov
@sokrypton (Twitter)@eugenevalkov In the past, we even called it "Protein structure determination" cus the signal you get from MSA/coevolution (even w/o any supervised learning) is as good as you would from any other experimental source. With AF/RF we just made this more efficient (2/2) https://t.co/z8ZLWj47Cm
view full postNovember 12, 2021
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Ian Haydon
@ichaydon (Twitter)@sjurgis @gordonwells @rivatez @medialab @UWproteindesign huh - weird. Articles are: Massively parallel de novo protein design for targeted therapeutics And: Protein Structure Determination using Metagenome sequence data
view full postApril 28, 2019
Abstract Synopsis
Helen Yu
@Hypat1aYu (Twitter)