Future

Life is what you get and what you received......

[Future @ScienceSilva1]

Bringing moments to life, one frame at a time. 📸✨ Explore my photography shop for unique prints that tell a story. Check it out here: https://t.co/vTGrIhS9Rl
#Photography #ArtPrints

[Seubbie Ticket Assistance 🍀 @gohmawo]

Assisted & Secured (1) CAT4 for BTS World Tour ‘Arirang’ in Singapore! (from Army Membership Presale)

Thank you for trusting 🍀

#trishalamat #BTS
#BTS_WORLDTOUR_ARIRANG_SINGAPORE

[Patricia Skowronek @patiskowronek]

In labs, hands-on expertise is often lost because it's not written down. We leverage multimodal AI agents to capture & share it by analyzing video and speech to generate protocols, detect errors, and guide researchers. #AI #TeamMassSpec
📄 Preprint: https://t.co/Nt24iRvSm7 1/🧵

[The Nobel Prize @NobelPrize]

Who are the women that inspire you?

On the eve of #InternationalWomensDay we're highlighting some of the extraordinary women who changed the world. Join us tomorrow when we celebrate more remarkable women.

[Biology+AI Daily @BiologyAIDaily]

AlphaFold and Docking Approaches for Antibody–Antigen and Other Targets: Insights From CAPRI Rounds 47–55

1. This study evaluates the integration of AlphaFold2 and docking techniques in modeling antibody-antigen and other biomolecular complexes, using blind predictive challenges from CAPRI rounds 47–55. It highlights advances in structure prediction and scoring strategies for challenging targets.

2. A key innovation is the use of AlphaFold2 with massive sampling, generating diverse structural models. For an antibody-peptide target (Target 231), the method produced near-native models with medium accuracy, achieving an interface RMSD of 0.96 Å.

3. The study reveals that AlphaFold-derived confidence scores, such as pLDDT, can aid model ranking. However, limitations in these metrics were noted for certain antibody-MHC targets (233, 234), suggesting room for improvement in scoring interfaces.

4. Traditional docking methods, such as ZDOCK and Rosetta, were also employed to complement AlphaFold predictions. These tools proved effective in refining and scoring models, especially for protein-DNA and homology-based templates.

5. A major insight is that combining AlphaFold with docking tools enhances predictive power, but accuracy remains constrained for highly flexible or low-confidence complexes, indicating the need for future methodological refinements.

6. The study underscores the potential of AlphaFold and similar deep learning methods for antibody-antigen modeling. It also highlights the necessity for adapted scoring metrics to improve ranking and identification of accurate models in challenging scenarios.

7. Lessons from CAPRI emphasize the importance of community-driven benchmarks in driving advancements in computational structural biology. They also demonstrate the evolving role of AI in addressing previously intractable problems in complex modeling.

@piercelab @minjaeparq
📜Paper: https://t.co/7H0F2EhUW7
#AlphaFold #AntibodyModeling #ProteinDocking #StructuralBiology #CAPRI

[Amanthi @amanthi4]

An ice replica of #SriLankan Sri Dalada Maligawa (Temple of the Tooth) in #China ❄️🇱🇰
#Buddhism

[The Nobel Prize @NobelPrize]

Tu Youyou discovered a substance called artemisinin, which can be used to treat malaria. Tu not only found a way to extract artemisinin from traditional Chinese medicine, she also tested the new drug on herself to speed up development time.

#NobelPrize

[The Nobel Prize @NobelPrize]

The 2024 #NobelPrize laureates in chemistry Demis Hassabis and John Jumper have successfully utilised artificial intelligence to predict the structure of almost all known proteins.

In 2020, Hassabis and Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.

Read more about their story: https://t.co/nWxcZs6wqC

[Itai Yanai @ItaiYanai]

Doing good science is 90% finding a science buddy to constantly talk to about the project.

[Nina Rouhani @ninarouhani]

I will be recruiting 💫two PhD students💫 for my new lab! (computational learning & memory applied to individual & interactive behavior, https://t.co/EXo6x5fI8Z).

Feel free to e-mail if interested and catch me at SfN! (poster 06 at 1 PM on Wed 10/09)

[Stanford AIMI @StanfordAIMI]

"Artificial Intelligence: The Future of Medicine & Health Care Is Here" -- Dynamic presentations by AIMI Co-director @drnigam & affiliated faculty @FaRodriguezMD show the vital role of #AIinMedicine & how it can benefit the Tri-Valley community. https://t.co/99pUS6wX0W

[イエス・キリスト @yeskiri]

可愛すぎてヤバいwwww

[Matthias Mann Lab @labs_mann]

"🎙️ New episode of The Proteomics Show!
Ep 50: Why study proteins? Matthias @labs_mann breaks down the impact of proteomics, future directions and implications for biology and medicine.
https://t.co/EcmFUkpeIc

[Future @ScienceSilva1]

@depressionlesss Car's first time on a car! 🙈

[Steven Ge @StevenXGe]

We've been awarded an NIH R01 grant to further improve ShinyGO! 🎉
- Thank you for using it and citing our paper!
- These support letters were essential!
- This means the annotation databases will be updated for at least 5 years, also benefiting iDEP users.
- Feel free to request features & functionalities!
#ShinyGO #bioinformatics

[Future @ScienceSilva1]

@easyjet494i Thanks for the reply.

[Future @ScienceSilva1]

@easyJet I’m still waiting for a response regarding being denied boarding and my baggage (which I paid extra) offloaded without permission on 06/09/2024, causing missed flights and extra costs. This disrupted my entire travel plan. Please take prompt action to resolve this.

[Future @ScienceSilva1]

@PunchingCat Furry 🤩

[Future @ScienceSilva1]

@NoCatsNoLife_m Car crash 🥏

[Future @ScienceSilva1]

@Catshealdeprsn Purrfect!