Last updated on 2024-10-01T21:34:23+00:00 by LN Anderson Human Cell & Tissue Response to HCoV-229E Infection Proteomics (ACS-JM-DP2) The purpose of this experiment was to evaluate the human host response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for...
Last updated on 2024-09-17T19:19:38+00:00 by LN Anderson Human A549 and MRC5 Cell Response to HCoV-229E Infection Transcriptomics (ACS-DP1) The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data...
Last updated on 2024-09-27T16:50:31+00:00 by LN Anderson High-density Lipoprotein (HDL) Structure and Function The purpose of this experiment was to investigate how the interactions between APOA1 and APOA2 on the surface of high-density lipoproteins (HDL) impact particle function. Interactions were...
Citation: Mejia-Rodriguez D, Kim H, Sadler N, Li X, Bohutskyi P, Valiev M, Qian WJ, Cheung MS. PTM-Psi: A python package to facilitate the computational investigation of post-translational modification on protein structures and their impacts on dynamics and functions. Protein Sci. 2023 Dec;32(12)...
Citation : Reichart NJ, Steiger AK, Van Fossen EM, McClure R, Overkleeft HS, Wright AT. Selection and enrichment of microbial species with an increased lignocellulolytic phenotype from a native soil microbiome by activity-based probing. ISME Commun. 2023 Sep 30;3(1):106. doi: 10.1038/s43705-023...
The research goal of this project is to establish model synthetic microbial communities to understand the rules regulating their biological function in order to utilize them as next generation bioproduction platforms capable of reducing carbon and nitrogen footprints in biomanufacturing processes.
We are constructing a streamlined approach to identify phenotype-relevant signatures by integrating various proteomics data. Leveraging protein structures and interaction networks, we will map structural changes and post-translational modifications to identify molecular drivers and subsequently...
The research goal of this project is to develop computational methods to predict cell regulation phenotypes using small molecule and proteome data to understand outcomes in complex biological systems.
The research goal of this project is to build and understand model communities that show carbon storage phenotypes
The research goal of this project is to develop new theory and tools that leverage evolutionary perspectives and knowledge of the energetics of reactions to predict the most likely regulation in a given environment. These methods will accelerate exploration, modeling and understanding of cell...
The research goal of this project is to identify and control host functions hijacked during viral infection through use of PNNL ‘omics technologies and modeling capabilities.
The research goal of this project is to develop a biologically informed machine learning (ML) model that integrates datasets from different studies, and leverages current biological knowledge in an automated manner, to improve predictions in biological data analysis.
By developing explainable, predictive metabolic models of individual microbes, we aim to design consortia that convert light and abundant atmospheric gases into high-value molecules through microbial division of labor.
The science objective of this project is to apply structural proteomics technologies to map the molecular interactome.
The research objective of this project is to develop an integrative and automated multi-PTM profiling capability with deep proteome coverage.
