Work

Gene expression profiling and machine learning to understand and predict primary graft dysfunction

Year: 2007

Type: conference-paper

Source: IEEE International Conference on Bioinformatics and Bioengineering (BIBE)

DOI: 10.1109/bibe.2007.4375692

Authors: Monika Ray, Sekhar Dharmarajan, Johannes Freudenberg, G. Alexander Patterson, Weixiong Zhang

Institutions: University of Washington, Washington University in St. Louis, Cincinnati Children's Hospital Medical Center

Language: English

Topic: Transplantation: Methods and Outcomes

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Science Foundation, National Institutes of Health, National Cancer Institute

OpenAlex ID: W1966157917

FWCI:

Cites: 42

Cited by: 1

Related to: 10