Wing Ki (Catherine) Wong

Sr. Scientist @Roche. Oxford DPhil in Bioinformatics. Former @Opiglets, working on antibody, TCR, and GPCR design. Views my own.

[airr_community @airr_community]

Wing Ki Wong (Roche Diagnostics GmbH) discusses how integrating advanced language models, bioinformatics tools and antigen-mapped repertoires could accelerate the discovery and optimization of therapeutic antibodies. #AIRRC7 Full agenda: https://t.co/PhZ7b68Pmf

[Brennan Abanades @brennanaba]

Our most recent piece of work "The Patent and Literature Antibody Database (PLAbDab): an evolving reference set of functionally diverse, literature-annotated antibody sequences and structures" has just been released on bioRxiv (https://t.co/JUHJV3PTfb)!!

[Wing Ki (Catherine) Wong @WingKiCatherine]

Exciting opportunities in machine learning for protein design. Bonus: you’ll join a vibrant team at the birthplace of therapeutic proteins @Roche_de : https://t.co/cdOObnQTnf

[Alissa Hummer @AlissaHummer]

Very excited to announce our new preprint, with my PhD work on deep learning to predict change in antibody-antigen binding affinity!

Investigating the Volume and Diversity of Data Needed for Generalizable Antibody-Antigen ΔΔG Prediction
https://t.co/7Cf2x4fBPK

🧵⬇️

[Wing Ki (Catherine) Wong @WingKiCatherine]

W're hiring! If you are interested in computational protein engineering, reach out to us! #roche #postdoc #antibody #proteinengineering https://t.co/H4KeoDTrHh

[Brennan Abanades @brennanaba]

Excited to share our most recent piece of work at @OPIGlets : ImmuneBuilder, a set of deep learning based tools to predict the structure of antibodies, nanobodies and TCRs. (https://t.co/WMDRNBqysB)

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

Our new tool, KA-Search, allows exhaustive yet efficient antibody mining through billions of natural sequences (from OAS and/or your private data), enabling new avenues in function & immunogenicity prediction. Work led by @HegelundOlsen and @brennanaba.

https://t.co/xSt8si8lpW

[Matt Raybould @mijr12]

TCR-mimetic antibodies (TCRms) are a transformative new therapeutic modality. We've computationally profiled structures of TCRms/TCRs bound to pMHC to highlight trends in their antigen recognition. TCR-likeness offers a derisking strategy for TCRm design. https://t.co/ezyenRzCez

[GreiffLab 💻🔬💊 @victorgreiff]

Very happy that our work on generative machine learning for antibody design is now out in mAbs https://t.co/mCpEInbBZa. All details are in the preprint thread below. The peer-reviewed version contains more controls and also more comparisons of synthetic and experimental data.

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

Finding important communities in spatiotemporal networks is difficult w/out orthogonal data. DPhil student @JamesWilsenach uses Hidden Markov Graph Models for unsupervised detection/ranking of communities w/ applications to brain state networks https://t.co/0NDYbLQpeo #openaccess

[bioRxiv Bioinfo @biorxiv_bioinfo]

Yclon: Ultrafast clustering of B cell clones from high-throughput immunoglobulin repertoire sequencing data https://t.co/sXuR0a8Df5 #biorxiv_bioinfo

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

Some database milestones this week: Thera-SAbDab passed 700 WHO-recognised antibody-based therapeutics (742) while CoV-AbDab passed 5,000 expressed antibodies/nanobodies able to bind to coronaviruses (5033)!
Thera-SAbDab: https://t.co/2fGJne51XP
CoV-AbDab: https://t.co/nPmMsEYZR6

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

https://t.co/d40ZS2td4V

Introducing AbLang, an antibody-specific language model to generate info-rich antibody representions. AbLang's potential is shown by restoring missing Ab residues with higher accuracy than 'germline filling'. Test it out yourself: https://t.co/KaWdiMV8vS!

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

Checkout our new review: AI in 3D Compound Design! https://t.co/jiOAwwEvGC From DPhil student @Hadfield5595

[Oxford Protein Informatics Group (OPIG) @OPIGlets]

ABlooper, our open-source EGNN-based approach for antibody Fv modelling, is now published in Bioinformatics. Work led by OPIG DPhil student @brennanaba

https://t.co/X6cEBxKO0t

[bioRxiv Bioinfo @biorxiv_bioinfo]

AbLang: An antibody language model for completing antibody sequences https://t.co/9QJdLu2zmV #biorxiv_bioinfo

[Sergey Ovchinnikov @sokrypton]

"The AlphaFold parameters are made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license" 🙂
https://t.co/dBenjo9JCd

(thanks to @BrianWeitzner for alerting me)

[Wing Ki (Catherine) Wong @WingKiCatherine]

#machinelearning #antibody #research

[Wing Ki (Catherine) Wong @WingKiCatherine]

Are you in informatics, machine learning or antibody analytics? Want to do an internship at Roche? Check out our latest position: https://t.co/oBxiE4VcWG

[Wing Ki (Catherine) Wong @WingKiCatherine]

And here is the listing on LinkedIn: Roche: Intern - Advanced Analytics Network - Machine learning for antibody development https://t.co/xSnwUXGIYa