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Phylogenetic Analysis of Trait Evolution

Abstract: 

Phylogenetic Analysis of Trait Evolution

These researchers study the evolution of traits that influence chances of speciation and extinction. Plant mating system is one such trait, because it strongly affects population sizes and distributions of genetic diversity. Geographic range is another such trait because geologic, climatic, and biotic conditions all affect population size and subdivision. Other traits are often associated with these, and it can be challenging to identify the particular traits or trait combinations that most directly affect speciation and extinction.

This work typically involves two phases of analysis, each of which can be computationally intensive for groups of more than, say, a thousand species. First is constructing a phylogeny of living species from DNA sequence data. Second is fitting models of trait evolution, speciation, and extinction to those phylogenies. Such analyses are easily parallelized, especially when conducted in a Bayesian statistical framework, and so the researchers can readily make use of MSI's cluster resources.

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Group name: 
eeg

Analysis of Colonic Bacterial Populations; MicroRNA Pathway Analysis

Abstract: 

Analysis of Colonic Bacterial Populations; MicroRNA Pathway Analysis

Examining bacteria populations within the large intestine of mammals (the microbiome) has become of tremendous interest. These researchers focus on how different dietary treatments affect such populations. They are currently examining the effect of amount of dietary fat and of types of dietary fiber influence such populations, and will soon begin another project examining how polylactose, a potential new prebiotic, may affect the microbiome. MSI's computing resources are extremely important in analyzing the bacterial DNA sequence data obtained from the University of Minnesota Genomics Center that are used to identify the genus and species of bacteria present in the microbiome.

A second area of interest is understanding what changes occur in different species of microRNA (miRNA) in the colonic mucosa of carcinogen-treated animals exposed to different dietary interventions, and how these changes may influence different metabolic pathways related to colon cancer. This project uses Integrated Pathway Analysis software available through MSI.

Both of these activities will help further our understanding how diet can reduce colon cancer risk, and by what mechanism this may occur.

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Group name: 
gallaher

Modeling of Nanodusty Plasmas

Abstract: 

Modeling of Nanodusty Plasmas

These researchers are developing computational models of gas plasmas in which nanoparticles nucleate and grow. Their main interest is in the types of plasmas used for industrial applications such as semiconductor processing and materials synthesis. The group's primary focus is on the development of numerical models to simulate the spatiotemporal evolution of such plasmas, including the nucleation, growth, charging and transport of nanoparticles, and the effect of the nanoparticle aerosol on the plasma behavior. They are improving a 1D model of a two-parallel plates capacitively-coupled RF plasma that has been developed in the group. The main goal is to tailor nanoparticle size and flux to the substrate located at the bottom electrode. Experiments are done at the LPICM group in Paris, France. In addition, this group collaborates with the Kushner group from the University of Michigan to develop a 2D model of a capacitively-coupled RF plasma used for the synthesis of silicon nanocrystals in which a mixture of Ar:SiH4 flows through a narrow quartz tube. 

A Research Spotlight about this group's work appeared on the MSI website in March 2014.

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Group name: 
girshick

Antimicrobial Peptides and Autoimmune Disease

Abstract: 

Antimicrobial Peptides and Autoimmune Disease

The Sjögren’s Syndrome Knowledge Base (SSKB) is a resource for Sjögren’s syndrome research. The foundation for SSKB is a database of genes and proteins associated with Sjögren’s syndrome extracted from PubMed. The foundational database was established using the text-mining program EBIMed to query the Pubmed database, using the search term "Sjogren's Syndrome" restricted to "MeshHeadingsList."

The initial search in 2007 resulted in a selection of 7,733 abstracts and 1,293 potential genes/proteins. The abstracts were manually evaluated to remove duplicates and false-positives, resulting in a preliminary database of about 900 protein names and associated genes. In the case of older publications, where gene names were not readily identifiable, gene names were assigned based on in depth evaluation of the protein name context and available gene data in public databases, including Entrez and Uniprot. The data is continually updated and manually annotated to include new publications and data relating to the genes in the SSKB.

In a second project, microbiome data are collected by 16S rRNA sequencing of microbial samples from mouse and human anatomical sites. Data storage is requested for large data sets. Analysis is conducted in collaboration with the laboratory of Dan Knights (Computer Science and Engineering).

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Group name: 
gorrsu

Enhancing Scalability and Energy Efficiency in Extreme-Scale Parallel Systems Through Application-Aware Communication Reduction

Abstract: 

Enhancing Scalability and Energy Efficiency in Extreme-Scale Parallel Systems Through Application-Aware Communication Reduction

Accesses to shared data should be synchronized to guarantee correct execution of parallel programs. Synchronization dictates a total or partial order on parallel tasks of execution. Since each synchronization point represents a point of serialization, synchronization can easily hurt scalability of parallel programs. To improve scalability in the face of inevitable synchronization, these researchers propose to relax synchronization. The idea is to eliminate a subset of the synchronization points, and to exploit the implicit noise tolerance of an important class of the future parallel applications – (R)ecognition, (M)ining, and (S)ynthesis, in mitigating relaxation-induced atomicity violations or data races. This project explores how relaxation can improve the scalability of parallel programs. Relaxation can enhance scalability as long as the relaxation-induced degradation in the accuracy of computing remains at acceptable levels. Accordingly, the researchers start with exploration of the trade-off space of accuracy degradation vs. speed-up.

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Group name: 
karpuzcu

Electronic Structure Calculations of Organic Reaction Mechanisms

Abstract: 

Electronic Structure Calculations of Organic Reaction Mechanisms

The hydroxyl radical (OH) is the most important oxidant in the lower atmosphere, or troposphere. Computational research in the past decade, conducted in part by this lab, has begun to elucidate pathways for OH formation that do not require the direct participation of photons. Many of these pathways involve the generation and decomposition of hydroperoxides, and can account for current deficiencies in regional atmospheric chemistry models. In 2015, the Kuwata lab used MSI resources to address the reactivity of an atmospherically relevant hydroperoxide, the vinyl hydroperoxide formed in alkene ozonolysis. In 2016, MSI resources will be used to treat a wider set of possible vinyl hydroperoxide reactions. The researchers are especially interested in the molecules derived from the ozonolysis of isoprene because isoprene is the most abundant unsaturated hydrocarbon in the lower atmosphere. Their predictions for these reactions could therefore have a huge impact on the understanding of atmospheric chemistry. In particular, if researchers predict significant yields of stable alcohols, this would lower the predicted OH yield of isoprene ozonolysis. The resulting deficit in the OH atmospheric “budget” would drive a search for additional OH sources.

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Group name: 
kuwatak0

Snapshot Serengeti: Camera Traps to Monitor Biodiversity in Serengeti National Park, TZ

Abstract: 

Snapshot Serengeti: Camera Traps to Monitor Biodiversity in Serengeti National Park, TZ

Camera traps can be used to address large-scale questions in community ecology by providing systematic data on an array of wide-ranging species. These researchers deployed 225 camera traps across 1,125 km2 in Serengeti National Park, Tanzania, to evaluate spatial and temporal inter-species dynamics. The cameras have operated continuously since 2010 and had accumulated 99,241 camera-trap days and produced 1.2 million sets of pictures by 2013. Members of the general public classified the images via the citizen-science website Snapshot Serengeti. Multiple users viewed each image and recorded the species, number of individuals, associated behaviours, and presence of young. Over 28,000 registered users contributed 10.8 million classifications. The consensus classifications and raw imagery provide an unparalleled opportunity to investigate multi-species dynamics in an intact ecosystem and a valuable resource for machine-learning and computer-vision research.

This research was featured in a Research Spotlight on the MSI website in July 2015. 

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Group name: 
packerc

Magnetoencephalographic Studies of Motor Uncertainty in Health and Disease

Abstract: 

Magnetoencephalographic Studies of Motor Uncertainty in Health and Disease

These researchers have designed and carried out experiments with human participants that focus on reaching (using a joystick) to targets situated at diverse spatial locations while systematically varying the amount of information available about the possible location of the target's appearance during a cueing period. The brain activity of participants was recorded during these tasks using magnetoencephalography (MEG) - a technique that records magnetic activity in the brain with millisecond resolution at femtotesla intensities.

The researchers are currently using statistical methods that include discriminant analysis and multiple linear regression as well as signal processing metrics such as a variety of Phase Locking Indexes to optimally correlate the MEG signal as it relates to the direction of the upcoming target and the amount of uncertainty about its location. They thus hope to be able to better understand the process by which alternative motor plans are represented in the brain and how ultimately one of them is selected. They use MATLAB to carry out their analyses. Given the computationally intensive nature of these analyses (e.g. discriminant analyses run over sliding windows across hundreds of channels per subject, PLIs calculated across thousand of voxels per subject), the use of MSI resources should help shorten the considerable amount of time required, while also allowing the researchers to rapidly interrogate the data in a variety of different ways.

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Group name: 
pellizze

Functional Genomics

Abstract: 

Functional Genomics

These researchers have five current projects using MSI resources:

  • Mutant mapping studies: Using bulk segregate analysis, useful soybean mutant phenotypes will undergo mapping studies to restrict causative genes to a region of a chromosome. Whole-genome sequencing (WGS) will be generated and analyzed on wild-type and mutant bulks for each phenotype of interest.
  • Comparison of mutation rates: This project is looking at change in mutation rates between standing, irradiated, and transformed genetic variation using soybean WGS. The group will also be looking at differences in large structural variants between these populations as well as various population genetics metrics.
  • Creation and application of soybean co-expression networks: Using publically available soybean RNA-seq expression data, the researchers will generate expression values and build a general co-expression network. Using this network, they will then integrate it with differential expression studies for interesting phenotypes to generate a list of candidate genes.
  • Exploring the soybean germplasm collection: This project uses publicly available climate, soil, and genotypic data to run a mixed linear model of association. With multiple populations and 80 different environmental phenotypes available this will result in large computational use.
  • RNA seq of F1 hybrids: This project explores the soybean transcriptome and how it is affected by parentage and copy number variation. This involves analysis of both WGS and RNA-seq data.

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Group name: 
stuparr

Biomolecular Simulations of Soluble and Membrane-Bound Complexes

Abstract: 

Biomolecular Simulations of Soluble and Membrane-Bound Complexes

This research focuses on the investigation of the molecular mechanisms that regulate cell signaling in multicellular organisms. Signal specificity is encoded into the 3D structure of proteins that transfer specific information from the cell surface to the nucleus, leading to changes in gene expression and cellular biochemistry. This lab studies these signaling processes examining how aberrant protein interactions and structural variation may lead to pathophysiologies of calcium signaling in cardiac and skeletal muscle. Calcium is a central messenger for contractility, and dysfunctional calcium signal transduction is linked to several pathologies including heart failure and muscular dystrophy. There has been a continuous effort to develop small molecules and protein therapies to ameliorate these pathological conditions. To elucidate the biochemical and structural bases for these processes, these researchers determine the 3D structures of protein complexes that are involved in calcium trafficking. Toward this end, the group is developing new structural biology approaches using Nuclear Magnetic Resonance (NMR) spectroscopy to obtain structural information on these large macromolecular complexes. They also study two important post-translational modifications central to calcium signal transduction and protein recognition: phosphorylation and myristoylation. Computational approaches are fundamental to understanding and interpreting the conformational dynamics information obtained from NMR studies. Toward this goal, the researchers have established a strong collaboration with the group of Jiali Gao (Chemistry). The overall goal of this research is to decipher the mechanisms underlying cell signaling and develop new frameworks for innovative therapeutic approaches.

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Group name: 
vegliag

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