IN005
Automating Molecular Analysis of Environmental Systems Towards Increasing Throughput, Confidence, and Detection of Challenging Analytes

Session ID#: 161876

Session Description:
Increasing demand for comprehensive molecular characterization of environmental samples highlights critical bottlenecks in traditional human-powered analytical workflows across disciplines.   

To enhance our ability to probe complex ecosystems it is necessary to develop (semi-)automated and/or in-situ workflows for sample preparation, analytical measurements, and data analyses. Furthermore, automated workflows increase objectivity and robustness of workflows, increasing scientific fidelity.   

In this session, we aim to facilitate interdisciplinary discussions of novel techniques, key best practices, technological gaps, and automated analytical pipelines in or for complex environmental systems.   

Ecosystems of interest include the atmosphere, soils, rivers, lakes, and oceans, with a focus on molecular level characterization of their complex, recalcitrant, or short-lived components, such as bioactive signaling molecules. These systems present unique challenges as a result of matrix diversity and heterogeneity.   

We encourage submissions from diverse fields, highlighting successes, challenges, and advancements in sample preparation, analytical techniques, and data analysis pipelines.

Co-Organized:
  • B - Biogeosciences
Index Terms:

0452 Instruments and techniques [BIOGEOSCIENCES]
0458 Limnology [BIOGEOSCIENCES]
0486 Soils/pedology [BIOGEOSCIENCES]
1998 Workflow [INFORMATICS]

Primary Convener:  Allison Myers-Pigg, Pacific Northwest National Laboratory, Marine and Coastal Research Laboratory, Sequim, United States; University of Toledo, Toledo, United States
Conveners:  William Kew1, John Bargar1 and Allison Myers-Pigg2, (1)Pacific Northwest National Laboratory, Environmental Molecular Sciences Laboratory, Richland, WA, United States(2)Pacific Northwest National Laboratory, Sequim, United States
 
Metabotandem And Metabodirect: Software Pipelines for the Analysis of High Throughput Metabolomics Data for Complex Environmental Samples (1129955)
Christian Ayala1, Malak M Tfaily1 and Nathalia Graf Grachet2, (1)University of Arizona, Department of Environmental Science, Tucson, AZ, United States, (2)University of Arizona, Tucson, United States
See more of: Earth and Space Science Informatics
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