Mikaela Cashman

Orcid: 0000-0003-0620-7830

Affiliations:
  • Lawrence Berkeley National Laboratory, USA
  • Oak Ridge National Laboratory, TN, USA (former)
  • Iowa State University, Ames, IA, USA (former)


According to our database1, Mikaela Cashman authored at least 11 papers between 2016 and 2023.

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Bibliography

2023
Data-Driven Whole-Genome Clustering to Detect Geospatial, Temporal, and Functional Trends in SARS-CoV-2 Evolution.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

Longitudinal Effects on Plant Species Involved in Agriculture and Pandemic Emergence Undergoing Changes in Abiotic Stress.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

2022
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
An empirical investigation of organic software product lines.
Empir. Softw. Eng., 2021

Reusability First: Toward FAIR Workflows.
Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020
Using a Genetic Algorithm to Optimize Configurations in a Data-Driven Application.
Proceedings of the Search-Based Software Engineering - 12th International Symposium, 2020

2019
DNA as features: organic software product lines.
Proceedings of the 23rd International Systems and Software Product Line Conference, 2019

2018
Navigating the maze: the impact of configurability in bioinformatics software.
Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering, 2018

2017
End-to-end molecular communication channels in cell metabolism: an information theoretic study.
Proceedings of the 4th ACM International Conference on Nanoscale Computing and Communication, 2017

BioSIMP: Using Software Testing Techniques for Sampling and Inference in Biological Organisms.
Proceedings of the 12th IEEE/ACM International Workshop on Software Engineering for Science, 2017

2016
Test case prioritization of build acceptance tests for an enterprise cloud application: An industrial case study.
J. Syst. Softw., 2016


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