Mo Lotfollahi ✓
@mo_lotfollahi · joined 26 May 2018
ML for biology and drug discovery | Faculty @sangerinstitute @Cambridge_uni
13 007Followers
1 030Following
1 919Posts total
189KViews on collected posts
โพสต์ล่าสุด
กำลังค้นหาโพสต์ใหม่…
Three years ago, my lab at @MSKCancerCenter set out to see if we could harness AI for new therapeutic proteins.
Today in @natBME, our first step in developing these AI-designed molecules as anti-tumor therapies is online.
Read more here: 1/n https://t.co/eb2ufazEKC https://t.co
14.4K views · 207 likes
· 53 reposts · 8 replies
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@mo_lotfollahi Tremendous data resource & model @mo_lotfollahi! But I don't think JEPA == world model (from what I understand is its traditional definition) automatically. And I don't think this is a traditional world model. I cud be wrong. Maybe @ylecun or others may be able to
1.6K views · 10 likes
· 1 reposts · 1 replies
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Excited to share TERRA, a tissue world model 🧬
Over ~1.5 years we ran a large data-generation + modelling effort to build a world model for human tissues, pretrained on 112M cells from spatial transcriptomics (mostly Xenium 5000-plex + public data).
It's built on one of the htt
51.1K views · 399 likes
· 91 reposts · 18 replies
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2:15
Amazing work, super useful for the community
3.8K views · 6 likes
· 2 reposts · 0 replies
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Finally… Excited to share what I’ve been working on for the first half of my PhD!
ENCODE GRAMMAR: One of the largest collections of regulatory DNA seq2func models to date (3,865 in total) trained across ENCODE, with full model interpretations and annotations tracks. 1/n https://
18.8K views · 157 likes
· 34 reposts · 5 replies
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Honoured to have Pushmeet Kohli (@GoogleDeepMind) speak at our #AIxBio conference at the Wellcome Sanger Institute.
Build AI responsibly to benefit humanity”
Exciting times. 🧬
@sangerinstitute https://t.co/V0UlBMJkNl
1.9K views · 31 likes
· 1 reposts · 0 replies
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@mo_lotfollahi @sangerinstitute @CC4AIM congratulations!
229 views · 2 likes
· 0 reposts · 0 replies
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Finally, big thanks to amazing people and collaborators for their support who warmly welcomed me @teichlab @Muzz_Haniffa @roserventotormo @bayraktar_lab @GosiaTrynka @LeopoldParts @MihaelaVDS @jdmccaff and many more.
1.5K views · 10 likes
· 0 reposts · 1 replies
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I would like to thank all collaborators, students snd scientists whom I had the pleasure to work with from industry to academia, special thanks to my mentor @fabian_theis who enabled me to grow as a scientist and provided unprecedented support in my career and life.
1.6K views · 10 likes
· 0 reposts · 1 replies
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We are in an amazing environment with top notch collaborators doing both state-of-art ML/AI and genomics. I am hiring on different levels across various expertises: experimental/wet , core ML/AI, and computational biologists . Please reach out if you are interested! https://t.co
2.5K views · 20 likes
· 0 reposts · 2 replies
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Delighted to finally announce that Lotfollahi Lab starts this year at @sangerinstitute and @CC4AIM in Cambridge University. The lab will develop core AI/ml systems and also generate large scale multi-modal cellular data to advance cell engineering:
https://t.co/qFh5Wl7hGE https:/
87.9K views · 736 likes
· 70 reposts · 52 replies
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เทียบกับบัญชีขนาดเดียวกัน
8 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.
ยอดดูมัธยฐาน3 391บัญชีนี้918ค่ามัธยฐานของ 10K–100K
การเข้าถึง, %26.07%บัญชีนี้3.39%ค่ามัธยฐานของ 10K–100K
การมีส่วนร่วม, %0.70%บัญชีนี้1.53%ค่ามัธยฐานของ 10K–100K
| ตัวชี้วัด | บัญชีนี้ | ค่ามัธยฐานของ 10K–100K | อัตราส่วน |
|---|---|---|---|
| ยอดดูมัธยฐานต่อโพสต์ | 3 391 | 918 | 3.69× |
| การเข้าถึง (ยอดดู ÷ ผู้ติดตาม) | 26.07% | 3.39% | 7.69× |
| อัตราการมีส่วนร่วม | 0.70% | 1.53% | 0.46× |
บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
87.9K15 Jan
2.5K
1.6K
1.5K
229
1.9K8 Jun
18.8K5 Aug
3.8K
51.1K
1.6K
523
2756 Aug
14.4K9 Sep
2.9K10 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.98%15 Jan
0.87%
0.71%
0.74%
0.87%
1.71%8 Jun
1.06%5 Aug
0.23%
1.01%
0.76%
0.57%
0.36%6 Aug
1.89%9 Sep
0.65%10 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.53%.
What the audience does
Likes65.0%1 610 in total
Reposts10.2%253 in total
Replies3.6%88 in total
Quotes0.8%19 in total
Bookmarks20.5%508 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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