William Morrell

R&D Computer Science

Author profile picture

R&D Computer Science

wmorrel@sandia.gov

Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-9292

Biography

Morrell’s work focuses on laboratory data management systems, applying information technology to facilitate collaboration, analysis, archives, and reproducibility. This work includes both writing custom software and integrating it with existing software, working on the Internet, instrument controller workstations, servers, and personal computers. The majority of his code is in Python, Java, and JavaScript.

Education and Prior Position

Bachelor’s Degree: Computer Science, University of Southern California (2002-2006)

Master’s Degree: Computer Science (Multimedia and Creative Technologies), University of Southern California (2006-2006)

Computer Scientist, Lawrence Livermore National Lab (2007-2009)

Education and Prior Position

Bachelor’s Degree: Computer Science, University of Southern California (2002-2006)

Master’s Degree: Computer Science (Multimedia and Creative Technologies), University of Southern California (2006-2006)

Computer Scientist, Lawrence Livermore National Lab (2007-2009)

Research Interests

Electronic Lab Notebooks

Morrell’s early work at Sandia focused on various Electronic Lab Notebook (ELN) solutions. ELNs store research notes in digital form, allowing for multiple benefits, including: monitoring and sharing, automated timestamping, embedded multimedia, and the ability to search.

Experiment Data Depot

The Experiment Data Depot is an open-source platform for storing the data and metadata for multi-omic biological research. The project goal is to facilitate engineering collaboration in synthetic biology by providing a standardized format and ontology for multi-omic datasets, bridging experimental practitioners data from the lab to datasets used by analysts, modelers, and machine-learning.

Selected Publication

  • Morrell, William C., et al. The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. ACS Synthetic Biology 2017 6 (12), 2248-2259. DOI: 10.1021/acssynbio.7b00204