Methodologically, for what we believe to be the first time, we jointly optimize over a rich space of architectures for the policy network, the hyperparameters of the training procedure and the formulation of the decision process. Comprehensive empirical results on two widely-used RNA Design bench...
A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we presentDeepCRISPR, a comprehens...
Deep learning to decode sites of RNA translation in normal and cancerous tissues RNA translation is a core cell process that is deregulated in cancer. Here, the authors show that a machine learning approach, RiboTIE, can reconstruct RNA translation in cancer and non-cancer cells. In medulloblast...
The field of graph deep learning is still rapidly evolving and many research ideas emerge by standing on the shoulders of giants. To ease the process,DGl-Gois a command-line interface to get started with training, using and studying state-of-the-art GNNs. DGL collects a rich set ofexample...
& Zhou, Y. RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning. Nat. Commun. 10, 5407 (2019). Article Google Scholar Wang, J., Cao, H., Zhang, J. Z. H. & Qi, Y. Computational protein design with deep learning neural ...
A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we presentDeepCRISPR, a comprehens...
Vaccine Design Predicting RNA Secondary Structure We also provideexamplesthat implement various algorithms and show the methods running the algorithms: The PaddleHelix team participated in multiple competitions related to bio-computing. The solutions can be foundhere. ...
För närvarande fungerar en pipeline för automatisk generering av slutsatsdragning endast för träningspipeline som skapats enbart av de inbyggda designerkomponenterna. Det skapar ett pipelineutkast för batchinferens åt dig. Pipelineutkastet för batchinferens använder den trän...
Architecture Design: Inference chips often have optimized architectures for specific operations like matrix multiplication, while training chips may have more flexible architectures to handle diverse training tasks. Example: Inference Chip: A dedicated AI chip in a smartphone that quickly identifies objects...
Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models Cascaded diffusion models can be used to synthesize realistic whole-slide image tiles from latent representations of RNA-sequencing data from human tumours. ...