Work

Data and Code for Data-Driven Insights to Accelerate Advanced Biomanufacturing

Year: 2026

Type: dataset

Abstract: This Zenodo record contains datasets and analysis notebooks supporting the manuscript:Lalonde et al., “Data-Driven Insights to Accelerate Advanced Biomanufacturing,” submitted to RSC Digital Discovery (2026).The datasets describe literature-derived cultivation experiments for polyhydroxybutyrate (PHB) production in Synechocystis sp. PCC 6803 and were used for machine-learning model development, interpretation, and experimental validation.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.18422740

Authors: Lalonde, Jessica, Pacheco, Sara, Talapatra, Anjana, Gonzalez Esquer, Cesar, Marrone, Babetta

Institutions: Los Alamos National Laboratory, Duke University, Michigan State University

Language: English

Topic: biodegradable polymer synthesis and properties

Subfield: Biomaterials

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funder: U.S. Department of Energy

Award: G8922005934

OpenAlex ID: W7126058837

Cites:

Cited by:

Related to: 10