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Discovery and Study of Microbial Peptide Natural Products


Discovery and Study of Microbial Peptide Natural Products

Since the discovery of penicillin in the 1920s, natural products have had an unmistakable impact on our health and have inspired us with their intricate chemical structures and fascinating underlying metabolic pathways. Historically, biochemical and genetic studies in these systems have focused on free-living, fast growing terrestrial organisms due to technological and laboratory constraints. However, the past 10-15 years have seen an explosion of new DNA sequencing technologies and molecular biological techniques that have, for the first time, allowed genetic access to more subtle and intricate ecosystems.

This lab's work focuses on the discovery and heterologous expression of pathways and genes involved in the biosynthesis of metabolites from unique microbial sources. The researchers use cutting-edge and classical techniques in biochemistry, microbiology, metagenomics, and mass spectrometry to investigate unconventional peptide-based metabolites and pathways invoking radical-mediated chemistry. MSI resources crucial to this group's success include computing power and software for de novo peptide identification from LC-MS data as well as data management and analysis of sequenced microbial genomes. All in all, this research aims to tackle the exponentially expanding genomic universe for the discovery of new enzymology and therapeutics.

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Understanding the Role of Transposable Elements in Maize Abiotic Stress Response


Understanding the Role of Transposable Elements in Maize Abiotic Stress Response

Abiotic stress, such as extreme temperatures or drought, severely limits agricultural productivity. These researchers have evidence that certain families of transposons can confer stress responsive expression patterns to nearby genes in maize. The first aim of this project is to define the role of transposons in gene expression responses to abiotic stress in several different tissues and genotypes. The focus of the second aim is to determining the mechanism by which transposons influence the stress-responsive expression of nearby genes. The third aim of this project will document natural variation for insertion sites of the transposons that confer stress-responsive gene expression and will attempt to identify protocols to mobilize these elements to generate novel allelic diversity in maize. This project will provide novel understanding of the molecular processes that underlie gene expression responses to abiotic stress. MSI is used for NGS data analysis and other downstream computationally intensive tasks.

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What does job exit status XX mean?

The exit_status attribute reported by "qstat -f <jobId>" can help users identify why a job failed. Successful runs report exit_status=0. Non-zero status (positive or negative) implies job failure, but the exact meaning of exit codes varies by software. For jobs submitted to PBS, negative...

Stratus Protected Data Cloud

MSI is building a local research compute cloud environment called Stratus ( ) , which is designed to store and analyze protected data, such as dbGaP. Stratus is a subscription-based infrastructure as a service that enables users to operate within their own self-service...

How do I create a new virtual machine / instance?

The easiest way to boot a VM is through Horizon ( ) Go to Project > Compute > Instances and click Launch Instance Horizon provides a Wizard to help you launch VMs. Look for stars (*); those are required fields and can only be set before instance creation! To begin...


From the Tensorflow website: TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other...

If you are new to bioinformatics this is the best place to start.

This hands-on tutorial will help a new user understand how to use the the Galaxy platform to analyze NGS data by working though the quality control steps needed for Illumina sequencing data.

Global Land Model Development


Global Land Model Development: Time to Shift From a Plant Functional Type to a Plant Functional Trait Approach

This project will advance global land models by shifting from the current plant functional type approach to one that better utilizes what is known about the importance and variability of plant traits, within a framework of simultaneously improving fundamental physiological relations that are at the core of model carbon cycling algorithms. A primary goal for earth system modeling is to make accurate predictions of the future trajectory of the climate system, based on a mechanistic understanding of processes regulating fluxes of mass and energy among system components. Land plays an important role in modifying the earth's mass and energy balance, as a critical link in the global cycling of carbon, among others. Land surface models have developed to include mechanistic representations of vegetation physiology, carbon and nutrient dynamics in plants and soils, how they might respond to changing climate and chemistry, and how those changes might feedback to influence changes in atmospheric greenhouse gases themselves. This project addresses these processes.

Existing models represent the global distribution of vegetation types using the Plant Functional Type concept. Plant Functional Types are classes of plant species with similar evolutionary and life history with presumably similar responses to environmental conditions like CO2, water and nutrient availability. Fixed properties for each Plant Functional Type are specified through a collection of physiological parameters, or traits. These traits, mostly physiological in nature (e.g., leaf nitrogen and longevity) are used in model algorithms to estimate ecosystem properties and/or drive calculated process rates. In most models, 5 to 15 functional types represent terrestrial vegetation; in essence, they assume there are a total of only 5 to 15 different kinds of plants on the entire globe. This assumption of constant plant traits captured within the functional type concept has serious limitations, as a single set of traits does not reflect trait variation observed within and between species and communities. While this simplification was necessary decades past, substantial improvement is now possible. Rather than assigning a small number of constant parameter values to all grid cells in a model, procedures will be developed that predict a frequency distribution of values for any given grid cell. Thus, the mean and variance, and how these change with time, will inform and improve model performance.

The trait-based approach will improve land modeling by: incorporating patterns and heterogeneity of traits into model parameterization, thus evolving away from a framework that considers large areas of vegetation to have near identical trait values; utilizing what is know about trait-trait, -soil, and -climate relations to improve algorithms used to predict processes at multiple stages; and allowing for improved treatment of physiological responses to environment (such as temperature and/or CO2 response of photosynthesis or respiration).

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Data Retention and Protection

The following policies pertain to specific systems managed by MSI. The specific elements of this policy and MSI's data policies in general are consistent with the University policy on data management and are therefore applicable to the transfer and storage of data on MSI resources. */ Data...

A New Metal-Organic Framework for Catalysis

Chemists are often interested in developing new catalysts that will improve the efficiency of chemical reactions. They can look to nature to provide examples when designing these new materials. Metalloporphyrins are a class of metal complexes that appear a great deal in biological systems. These...