Cytokinetics, Inc.

Paypal, Inc.

Vadim Kutsyy

Eugeni Vaisberg

Wei Zhang

Jun Zhang

Fei Li

Xiaohan Yun

Zhenyin Yang

Yang Yu

Ying Yue

Haoran Zhang

Meng Zang

Quin Zuo

Jinhong Fan

Junshi Guo

Zhe Huang

Chaoyi Chen

Ke Zheng

Daniel A Coleman

Siddarth Anand

Mikhail Kourjanski

Tingjie Jia

Qinghai Fu

Wenbing Zhu

Systems and methods that describe a graph database system with an online component and an offline component, are provided. Write events that modify a first graph in a real-time graph database included in the online component are received. Graph logs that include changes to the first graph in the real-time graph database caused by the write events are generated. The graph logs are transmitted to an offline component of the graph database system in a chronological order. A second graph in the offline component is modified using the graph logs. The first graph and the second graph are instantiated using a graph schema.

Graph database system

Image analysis methods and apparatus are used for distinguishing live and dead cells. The methods may involve segmenting an image to identify the region(s) occupied by one or more cells and determining the presence of a particular live-dead indicator feature within the region(s). In certain embodiments, the indicator feature is a cytoskeletal component such as tubulin. Prior to producing an image for analysis, cells may be treated with a marker that highlights the live-dead indicator in the image. In the case of tubulin, the marker will co-locate with tubulin and provide a signal that is captured in the image (e.g., a fluorescent emission).

Assay for distinguishing live and dead cells

A method for calculating distances between stimulus response curves (e.g., dose response curves) allows classification of stimuli. The response curves show how the phenotype of one or more cells changes in response to varying levels of the stimulus. Each 'point' on the curve represents quantitative phenotype or signature for cell(s) at a particular level of stimulus (e.g., dose of a therapeutic). The signatures are multivariate phenotypic representations of the cell(s). They include various features of the cell(s) obtained by image analysis. To facilitate the comparison of stimuli, distances between points on the response curves are calculated. First, the response curves may be aligned on a coordinate representing a separate distance, r, from a common point of negative control (e.g., the point where no stimulus is applied). Integration on r may be used to compute the distance between two response curves. The distance between response curves is used to classify stimuli.

Characterizing biological stimuli by response curves

Growing community of inventors

Los Altos, CA, United States of America

Vadim Kutsyy