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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...

2018 Research Exhibition

MSI held the ninth annual Research Exhibition on April 17, 2018. The event included a panel discussion about careers in HPC-related fields, presentations by industry representatives about current and emerging technologies, and a judged poster session. A new feature this year was the chance to see...

How do I connect to a Citrix Windows Virtual Machine?

Table of Contents Connection Instructions File Transfer Additional Drive Space Troubleshooting Notes for Linux users Disk-Full Errors Local Disk Access Connection Instructions Note to Google Chrome Users: If you have Citrix Receiver installed but xen.msi.umn.edu continues to ask you to install it,...

How do I get started with NX?

What is NX? For years the X11 Window System (Xwin32/Putty on Windows, X11/Terminal on Mac) has been the defacto standard for remotely displaying a graphical user interface from an MSI workstation or cluster on your local client. The aged X11 technology provides a solid starting point for simple and...

Interactive queue use with isub

Notes on isub Use The command isub is an MSI-written wrapper to ssh and qsub, designed specifically for interactive use. When isub is run with default options, it will ssh to a compute node in a pool of nodes reserved for interactive use. These nodes are the lab back-end, so when your shell starts...

MSI Users Bulletin – June 2018

The Users Bulletin provides a summary of new policies, procedures, and events of interest to MSI users. It is published quarterly. To request technical assistance with your MSI account, please contact help@msi.umn.edu . 1. Leadership Changes at MSI: Director of Research Computing Claudia Neuhauser...

Computational Chemistry

Abstract: 
<div class="node-column-original" style="font-size: 14px; background-color: rgb(255, 255, 255); color: rgb(51, 51, 51);"><div class="view view-access-requests view-id-access_requests view-display-id-by_group_name view-dom-id-1b61323b188b3c0fe150f2683573cccc" style="font-size: 14px;"><div class="view-content" style="font-size: 14px;"><div class="views-row views-row-1" style="font-size: 14px;"><h4 class="views-field views-field-abstract" style="font-size: 14px;">Computational Chemistry</h4><p class="views-field views-field-abstract" style="font-size: 14px;"><span class="field-content" style="font-size: 14px;">This group is using MSI resources to model chemical systems of interest in their research group. These may be conformational studies of molecules, electrochemical, or transition metal species. The researchers seek to gain insights into mechanism and physical properties.</span></p><p class="views-field views-field-abstract" style="font-size: 14px;"><span style="font-size: 14px; line-height: 1.5;">A bibliography of this group&rsquo;s publications is attached.</span></p><p class="views-field views-field-abstract" style="font-size: 14px;">Return to this PI&#39;s <a href="https://www.msi.umn.edu/pi/8341ed7c9e80776ff4842de5b50475eb/17273">main page</a>.</p><p class="views-field views-field-abstract" style="font-size: 14px;">&nbsp;</p></div></div></div></div><p>&nbsp;</p>
Group name: 
douglasc

Computational Biology and Machine Learning

Abstract: 
<h3 class="red">Computational Biology and Machine Learning</h3><p>The Kuang lab is interested in developing general machine learning approaches for integrative analysis of large-scale genomic data to understand the molecular characteristics of biological functions and phenotypes. They design theoretically principled methods in the categories of kernel methods, graph-based learning algorithms, sequence alignment methods and various statistical models for a unified analysis of the biological data in a data-driven perspective. Current projects center around the following topics:</p><ul><li>Cancer genomics: Development of graph-based learning algorithms, sequence alignment algorithms and association rule-mining algorithms for building predictive models and mining biomarkers of cancer phenotypes from microarray gene expressions, ArrayCGH DNA copy number variations, SNPs and protein-protein interactions.</li><li>Phenome-genome association analysis:&nbsp;Development of graph-based learning algorithms for analyzing disease and gene associations in a network context.</li><li>Protein remote homology detection:&nbsp;Development of kernel algorithms and label propagation algorithms to infer the correlation between protein-protein interactions, protein structures and functions.&nbsp;</li><li>Semi-supervised learning algorithms:&nbsp;Graph-based learning, transfer learning, sparse group learning and kernel learning methods.</li></ul><p>Return to this PI&#39;s <a href="https://www.msi.umn.edu/pi/3ab98edd8ff00602cba6be6b4786e55b/13757">main page</a>.</p>
Group name: 
kuangr

Optimization Algorithms for Computer Vision Tasks and POMDP Planning for Environmental Monitoring Projects

Abstract: 
<h3 class="red">Optimization Algorithms for Computer Vision Tasks and POMDP Planning for Environmental Monitoring Projects</h3><p>These researchers are using MSI for two research areas:</p><ul><li>Problems in related environmental monitoring applications such as invasive carp monitoring in Minnesota lakes.&nbsp;In particular, the researchers study the problem of designing search strategies for finding a target that is moving according to a random walk motion model in a square region. They formulate the problem as a Partially Observable Markov Decision Process (POMDP), and use a state-of-the-art toolbox (APPL: Approximate POMDP Planning toolkit developed by D. Hsu et al.) that helps reduce the state space. However, even for relatively small size environments the state space is large, requiring the use of MSI.</li><li>Coordinating an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) for a precision agriculture application in Minnesota apple orchards.&nbsp;The researchers study the problem of reconstructing all apple trees along each row in orchard using cameras mounted on a UGV. The corresponding algorithm for bundle adjustment needs to be tested on Matlab. However, even for a single tree, the total number of images is large. MSI supercomputers are used to get the first result about tree reconstruction in an orchard for further research.</li></ul><p>Return to this PI&#39;s <a href="https://www.msi.umn.edu/pi/8e1f8c80372f55721edf650190dc5e0c/10519">main page</a>.</p>
Group name: 
isleri

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