公开(公告)号：US20240120022A1

公开(公告)日：2024-04-11

申请号：US18275933

申请日：2022-01-27

Applicant: DeepMind Technologies Limited

Inventor： Andrew W. Senior ,  Simon Kohl ,  Jason Yim ,  Russell James Bates ,  Catalin-Dumitru Ionescu ,  Charlie Thomas Curtis Nash ,  Ali Razavi-Nematollahi ,  Alexander Pritzel ,  John Jumper

IPC: G16B15/00 ,  G16B30/20 ,  G16B40/20

CPC classification number: G16B15/00 ,  G16B30/20 ,  G16B40/20

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing protein design. In one aspect, a method comprises: processing an input characterizing a target protein structure of a target protein using an embedding neural network having a plurality of embedding neural network parameters to generate an embedding of the target protein structure of the target protein; determining a predicted amino acid sequence of the target protein based on the embedding of the target protein structure, comprising: conditioning a generative neural network having a plurality of generative neural network parameters on the embedding of the target protein structure; and generating, by the generative neural network conditioned on the embedding of the target protein structure, a representation of the predicted amino acid sequence of the target protein.

公开(公告)号：US11430123B2

公开(公告)日：2022-08-30

申请号：US16881775

申请日：2020-05-22

Applicant: DeepMind Technologies Limited

Inventor： Simon Kohl ,  Bernardino Romera-Paredes ,  Danilo Jimenez Rezende ,  Seyed Mohammadali Eslami ,  Pushmeet Kohli ,  Andrew Zisserman ,  Olaf Ronneberger

IPC: G06T7/10 ,  A61B5/00 ,  G06T7/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a plurality of possible segmentations of an image. In one aspect, a method comprises: receiving a request to generate a plurality of possible segmentations of an image; sampling a plurality of latent variables from a latent space, wherein each latent variable is sampled from the latent space in accordance with a respective probability distribution over the latent space that is determined based on the image; generating a plurality of possible segmentations of the image, comprising, for each latent variable, processing the image and the latent variable using a segmentation neural network having a plurality of segmentation neural network parameters to generate the possible segmentation of the image; and providing the plurality of possible segmentations of the image in response to the request.

公开(公告)号：US20230298687A1

公开(公告)日：2023-09-21

申请号：US18026376

申请日：2021-11-23

Applicant: DeepMind Technologies Limited

Inventor： Mikhail Figurnov ,  Alexander Pritzel ,  Richard Andrew Evans ,  Russell James Bates ,  Olaf Ronneberger ,  Simon Kohl ,  John Jumper

IPC: G16B15/20 ,  G16B40/20 ,  G06N3/084 ,  G06N3/045

CPC classification number: G16B15/20 ,  G16B40/20 ,  G06N3/084 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predicting a structure of a protein comprising one or more chains. In one aspect, a method comprises: obtaining an initial multiple sequence alignment (MSA) representation; obtaining a respective initial pair embedding for each pair of amino acids in the protein; processing an input comprising the initial MSA representation and the initial pair embeddings using an embedding neural network to generate an output that comprises a final MSA representation and a respective final pair embedding for each pair of amino acids in the protein; and determining a predicted structure of the protein using the final MSA representation, the final pair embeddings, or both.

公开(公告)号：US20200372654A1

公开(公告)日：2020-11-26

申请号：US16881775

申请日：2020-05-22

Applicant: DeepMind Technologies Limited

Inventor： Simon Kohl ,  Bernardino Romera-Paredes ,  Danilo Jimenez Rezende ,  Seyed Mohammadali Eslami ,  Pushmeet Kohli ,  Andrew Zisserman ,  Olaf Ronneberger

IPC: G06T7/10 ,  G06T7/00 ,  A61B5/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a plurality of possible segmentations of an image. In one aspect, a method comprises: receiving a request to generate a plurality of possible segmentations of an image; sampling a plurality of latent variables from a latent space, wherein each latent variable is sampled from the latent space in accordance with a respective probability distribution over the latent space that is determined based on the image; generating a plurality of possible segmentations of the image, comprising, for each latent variable, processing the image and the latent variable using a segmentation neural network having a plurality of segmentation neural network parameters to generate the possible segmentation of the image; and providing the plurality of possible segmentations of the image in response to the request.

公开(公告)号：US20240087686A1

公开(公告)日：2024-03-14

申请号：US18273594

申请日：2022-01-27

Applicant: DeepMind Technologies Limited

Inventor： Alexander Pritzel ,  Catalin-Dumitru Ionescu ,  Simon Kohl

IPC: G16B40/20 ,  G16B15/20 ,  G16B15/30 ,  G16B20/50 ,  G16B30/00

CPC classification number: G16B40/20 ,  G16B15/20 ,  G16B15/30 ,  G16B20/50 ,  G16B30/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for unmasking a masked representation of a protein using a protein reconstruction neural network. In one aspect, a method comprises: receiving the masked representation of the protein; and processing the masked representation of the protein using the protein reconstruction neural network to generate a respective predicted embedding corresponding to one or more masked embeddings that are included in the masked representation of the protein, wherein a predicted embedding corresponding to a masked embedding in a representation of the amino acid sequence of the protein defines a prediction for an identity of an amino acid at a corresponding position in the amino acid sequence, wherein a predicted embedding corresponding to a masked embedding in a representation of the structure of the protein defines a prediction for a corresponding structural feature of the protein.

公开(公告)号：US20230395186A1

公开(公告)日：2023-12-07

申请号：US18034006

申请日：2021-11-23

Applicant: DeepMind Technologies Limited

Inventor： Simon Kohl ,  Olaf Ronneberger ,  Mikhail Figurnov ,  Alexander Pritzel

IPC: G16B15/20 ,  G16B15/30 ,  G06N3/08 ,  G16B40/20

CPC classification number: G16B15/20 ,  G16B15/30 ,  G06N3/08 ,  G16B40/20

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a structure prediction neural network that comprises an embedding neural network and a main folding neural network. According to one aspect, a method comprises: obtaining a training network input characterizing a training protein; processing the training network input using the embedding neural network and the main folding neural network to generate a main structure prediction; for each auxiliary folding neural network in a set of one or more auxiliary folding neural networks, processing at least a corresponding intermediate output of the embedding neural network to generate an auxiliary structure prediction; determining a gradient of an objective function that includes a respective auxiliary structure loss term for each of the auxiliary folding neural networks; and updating the current values of the embedding network parameters and the main folding parameters based on the gradient.