Finally biologists can also use numpy (array programming). Handling e.g. DNA and protein sequences with convenience and speed, like physicists and machine learners for decades have worked with numerical data: https://t.co/06MjAmBINx (1/3)

This is an interesting idea: turning a cancer's drug resistance against it These are growth curves of tumours in mice, treated with a drug (a tyrosine kinase inhibitor). The tumours initially shrink but they all - slowly but surely - become resistant: This study aimed to convert

Exciting news! Our research paper on benchmarking BCR sequencing and antibody mass spectrometry on bulk and single cell levels, previously shared as a preprint, is now officially published. Take a look at the peer-reviewed version here:

1/8 Can negative dataset choices boost ML performance? We show that selecting negative samples is crucial for enhancing generalization and rule discovery in adaptive immune receptors. Learn more in this thread! 🧬 https://t.co/tiYdgv5sU0

Our paper on the linguistics-based formalization of antibody language is out in @NatComputSci. Work led by @MaiSpaceHa Rahmad Akbar and @PRobertImmodels . Summary thread: https://t.co/5QGruT3T2o.

Here is my biggest contribution to #science so far. A short series of memes inspired by #AlphaFold3 from @GoogleDeepMind 1/9🧵

Vincent Van Deuren (University of Antwerp) analyzed the synovial fluid T-Cell Receptor (TCR) repertoire across different arthritis groups and T-cell subsets, to characterize the T-cells associated with HLA-B27 related spondyloarthropathies. #AIRRC7 https://t.co/PhZ7b68Pmf

Some observations from my very brief #AlphaFold3 (AF3) benchmarking: AF3 is good for globular proteins, soluble proteins, conserved proteins, RNA/DNA-protein complexes, etc. AF3 is bad for IDPs, protein-protein complexes, antibodies, protein-switches, membrane proteins, etc.

Are you developing new machine learning methods for immune receptor/repertoire data? You can save yourself a lot of time by developing your method inside immuneML. Read all about it in our updated documentation: https://t.co/wq5d88E8il (1/3)

We’re excited to share our preprint where we show, for the first time, the atomically accurate design of VHH antibodies!

New opening for a PhD student in my lab, co-supervised with @F_Lund_Johansen . This position is ERC-funded and focuses on novel experimental technologies for antibody-antigen binding screening 📷

Lin Yun-Ju and Dimitrij Ovtcharov's skills at the table lit up #ITTFWorlds2024 today 🔥 #Busan2024 #TableTennis #PingPong #Liebherr

I'm curious how many early-career scientists (MSc/PhD/PostDoc) in Norway are interested in bio-related entrepreneurship. Do you have a general appeal, do you want to learn more, or maybe you are already developing your idea and launching a startup? @UiO_Doc @UniOslo @UiO_LifeSci

Happy to share a new manuscript! "Germinal centers are permissive to subdominant antibody responses" In brief, in simulations, low immunogenic antigens get their B cell response despite the presence of immunodominant antigens. https://t.co/TJttGGqcnQ Explanations below!

I got into ml because the other option was being a lab hazard

Our study on benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling is now on bioRxiv https://t.co/LRr22Vk4MT. Great work by @KhangLeQuy @ISnapkov and @mchernigovskaia. All details are below in the 🧵.

(1/7) Curious about what a blood sample can reveal about humoral immunity? Our latest work combined sequencing methods and mass spectrometry to explore BCR and antibody repertoires and assess their synergistic potential. https://t.co/kGQEgTm93q

Excited to share major progress on next generation of AlphaFold! Together with @IsomorphicLabs, we’ve significantly advanced accuracy & expanded coverage beyond proteins to other key biomolecular classes. Continuing to accelerate science at digital speed

(1/10) Our work on antibody developability is out! We present a cartography of the developability landscapes of the native and human-engineered antibodies. This study was a team effort of @HabibBashour @EvaSmorodina @pariset_matteo , and @Jahn_Zhong https://t.co/kIMBjziQAi

is GPT-4v susceptible to optical illusions? hunch is *of course not*...why would a computer vision system exhibit the same "feature/bugs" specifics as the idiosyncratic wetware wiring of the human visual system? yet for some, it weirdly does: