A Bayesian model for single cell transcript expression analysis on MERFISH data | Zendy

Johannes Köster | Zendy; Myles Brown | Zendy; X. Shirley Liu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Bayesian model for single cell transcript expression analysis on MERFISH data

Author(s) -

Johannes Köster,

Myles Brown,

X. Shirley Liu

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty718

Subject(s) - computer science , bayesian probability , workflow , computational biology , expression (computer science) , data mining , raw data , multiplexing , algorithm , biology , artificial intelligence , database , programming language , telecommunications

Multiplexed error-robust fluorescence in-situ hybridization (MERFISH) is a recent technology to obtain spatially resolved gene or transcript expression profiles in single cells for hundreds to thousands of genes in parallel. So far, no statistical framework to analyze MERFISH data is available.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research