公开(公告)号：US20170249548A1

公开(公告)日：2017-08-31

申请号：US15055446

申请日：2016-02-26

Applicant: Google Inc.

Inventor： Philip Charles Nelson ,  Eric Martin Christiansen ,  Marc Berndl ,  Michael Frumkin

IPC: G06N3/08 ,  G06T7/60

CPC classification number: G06N3/08 ,  G06K9/00127 ,  G06N3/02 ,  G06N3/0454 ,  G06T7/60 ,  G06T2207/20084

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing cell images using neural networks. One of the methods includes obtaining data comprising an input image of one or more biological cells illuminated with an optical microscopy technique; processing the data using a stained cell neural network; and processing the one or more stained cell images using a cell characteristic neural network, wherein the cell characteristic neural network has been configured through training to receive the one or more stained cell images and to process the one or more stained cell images to generate a cell characteristic output that characterizes features of the biological cells that are stained in the one or more stained cell images.

公开(公告)号：US20170061276A1

公开(公告)日：2017-03-02

申请号：US14842774

申请日：2015-09-01

Applicant: Google Inc.

Inventor： Patrick F. Riley ,  Marc Berndl

IPC: G06N3/04

CPC classification number: G06N3/0454 ,  G16C20/70

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving graph data representing an input graph comprising a plurality of vertices connected by edges; generating, from the graph data, vertex input data representing characteristics of each vertex in the input graph and pair input data representing characteristics of pairs of vertices in the input graph; and generating order-invariant features of the input graph using a neural network, wherein the neural network comprises: a first subnetwork configured to generate a first alternative representation of the vertex input data and a first alternative representation of the pair input data from the vertex input data and the pair input data; and a combining layer configured to receive an input alternative representation and to process the input alternative representation to generate the order-invariant features.

Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于接收表示包括通过边缘连接的多个顶点的输入图形的图形数据; 从图形数据生成表示输入图中每个顶点的特征的顶点输入数据和表示输入图中的顶点对的特征的对输入数据; 以及使用神经网络生成所述输入图的顺序不变特征，其中所述神经网络包括：第一子网络，被配置为生成所述顶点输入数据的第一替代表示和所述顶点输入中的所述对输入数据的第一替代表示 数据和对输入数据; 以及组合层，其被配置为接收输入替代表示并且处理所述输入替代表示以生成所述顺序不变特征。

公开(公告)号：US20170116371A1

公开(公告)日：2017-04-27

申请号：US14921973

申请日：2015-10-23

Applicant: Google Inc.

Inventor： Michelle Therese Hoerner Dimon ,  Marc Berndl ,  Marc Adlai Coram ,  Brian Trippe ,  Patrick F. Riley ,  Philip Charles Nelson

IPC: G06F19/24 ,  G06N3/08

CPC classification number: G16B40/00 ,  G06N3/0454 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.