Biological Systems

The Biological Systems focus area advances the study of biological systems as part of complex natural systems. It transcends three of LANL’s capability pillars: Science of Signatures (SoS), Complex Natural and Engineered Systems (CNES) and Information Science & Technology (IS&T) by addressing signatures of natural or human-induced phenomena on biological systems. This includes developing data-intensive computing approaches to advance a fundamental understanding of the behavior of microbial systems (across all scales) in response to environmental perturbations as well as their roles in bioenergy, bioremediation, carbon cycling, and the health of the human/environment interface. Many of the approaches rely on LANL’s long-standing expertise and established strengths in microbiology, genomics, and bioinformatics. Furthermore, understanding the contribution of environmental reservoirs to the transmission of human disease could help to predict hot spots for emergence of microbial infections. For example, there is currently great interest in the survivability of viruses, such as the SARS-CoV2 virus, for understanding mechanisms of transmission and establishing disease detection methods in a community. 

Focus Area

We emphasize approaches that integrate computation and experiment with independent data analysis approaches that can leverage advances in areas such as artificial intelligence and machine learning.

It is encouraged that proposals exploit unique LANL resources such as:

a) LANL high performance computing
b) DOE-sponsored climate models
c) LANL experimental capabilities in genomics and bioanalytical chemistry such as mass spectrometry, NMR etc.
d) Synthetic biology approaches to regulate biological systems for a re-directed purpose

Specific topics of interest:

1. Metagenomics: new approaches to elucidate interspecies interactions.

a. Between single or multicellular organisms in response to significant change in their environment. Identifying unique species-independent signatures.
b. Algorithm development and novel data analysis routines exploiting HPC

2. Impacts and consequences: approaches for understanding impacts of significant events or environmental change.

a. growth of harmful algal blooms as a result of adjacent agricultural practices or effluents; biofuel algal cultures and ponds as a result of microbial invasion.
b. extreme patterns of carbon flow under varied N-deposition scales;

3. Disease dynamics at the human/environment interface:

a. Establish methods of environmental testing to include highly complex environmental matrices.  (e.g. genetic characterization and quantification of SARS-CoV-2 genomes present in wastewater to define viral genotypes currently being transmitted). Understand persistence of pathogenic microbes in the environment and subsequent risks to the human population.
b. Visualizing, forecasting and understanding epidemic and outbreak dynamics.