COEM: Cross-Modal Embedding for MetaCell Identification

no code implementations • 15 Jul 2022 • Haiyi Mao, Minxue Jia, Jason Xiaotian Dou, Haotian Zhang, Panayiotis V. Benos

Metacells are disjoint and homogeneous groups of single-cell profiles, representing discrete and highly granular cell states.

A Pipeline for Integrated Theory and Data-Driven Modeling of Genomic and Clinical Data

1 code implementation • 5 May 2020 • Vineet K Raghu, Xiaoyu Ge, Arun Balajee, Daniel J. Shirer, Isha Das, Panayiotis V. Benos, Panos K. Chrysanthis

High throughput genome sequencing technologies such as RNA-Seq and Microarray have the potential to transform clinical decision making and biomedical research by enabling high-throughput measurements of the genome at a granular level.

Decision Making Variable Selection

Mixed Graphical Models for Causal Analysis of Multi-modal Variables

1 code implementation • 9 Apr 2017 • Andrew J Sedgewick, Joseph D. Ramsey, Peter Spirtes, Clark Glymour, Panayiotis V. Benos

Graphical causal models are an important tool for knowledge discovery because they can represent both the causal relations between variables and the multivariate probability distributions over the data.

feature selection Graph Learning