@aaguaijie Thrilled to introduce tFold, our team's AI solution for structural prediction, functional screening, and sequence design of therapeutic antibodies. Stay tuned for insights on the practical applications of our in-house AI models within a first-in-class pipeline. #tFold
1/4 Exciting news from Tencent AI Lab! Our new research is now available, continuing our previous work with:
A pretrained language model (ESM-PPI) for multi-chain sequences.
The new tFold-Ab model with SOTA antibody prediction performance. https://t.co/O1jRg3JL7D
Thrilled to announce my postdoc study at @JiguangWang lab published today on @NatureComms that captures primary tumors at high metastatic risk through machine learning of large-scale genomic data. A cartoon was made to elucidate the logic behind:
Receive "Absolut award" today from @PRobertImmodels at Norway! The snack still tastes absolutly good after flying 8,555 km from Oslo to Shenzhen🤣Wish Absolut all the best in the review~
@NCIEytanRuppin It surprises me that metastatic potential was not associated with aneuploidy. Previous study showed chromosomal instability could drive metastasis. https://t.co/Hiv3vWSmll
Aligning reads from ancient DNA to sequence variation graphs using vg removes reference bias and improves variant detection sensitivity (especially indels) relative to linear alignment with BWA. From @ruidlpm, @erikgarrison, @richard_durbin and co https://t.co/iHingU20zA
“However, the majority of the methods did not improve performance in downstream analyses compared to no imputation, in particular for clustering and trajectory analysis, and thus should be used with caution.”
Announcing Neural Tangents, a new easy-to-use, open-source neural network library that enables researchers to build finite- and infinite-width versions of neural networks simultaneously. Grab the code and try it for yourself at https://t.co/lckeDRA2kb