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Mimics

Software Description: 
Mimics is useful for visualization and segmentation of CT / MR images and 3D rendering of objects. It also provides an interface to create FEM meshes.
MSI currently has the following modules
  • Mimics basic - Allows segmentation, registration and measurement on 3D object
  • STL+ - Allows creation of 3D object for rapid prototyping
  • FEM - Add material property, create FEM mesh and export files to standard FEM packages

 

Software Support Level: 
Primary Support
Software Access Level: 
Open Access
Citrix Documentation: 

To run this software under Windows, connect using instructions provided in our Windows systems page.  Once logged in, navigate to

Start > All Programs > Materialise Software > Mimics x64 15.01 > Mimics

We only have two Mimics licenses. To use Mimics we ask that you reserve time on one the Mimics calendars, calendar one or calendar two using these instructions.  Reservations can be made on a calendar if you have a UMN Google account.  If you have problems, send an email to help@msi.umn.edu with a subject such as 'Add reservations to Mimics calendars'.

 
Running Mimics
Mimics is installed on our Citrix server. Follow the instructions for connecting with Citrix. Select the GPU node. You should see a Windows desktop. It may take a minute to come up. From there you should be able to run Mimics. Let us know if you feel the performance is too slow, there are things we can do to improve that.
 
Issues
We know of the following issues – none of them are show-stoppers, but people should be aware of them:
  • Mimics and 3-Matic may take several minutes to launch, but will start up successfully, given time.
  • When launching 3-Matic, a warning will pop up about a crash report directory. The program will launch normally after clicking OK.
  • Opening the Mimics ‘Options’ window for the first time will cause the program to hang for a minute or two before the window appears.
  • Mimics defaults to using the folder C:\MedData for projects. There is some example data in there to play with, but please save projects to your U: or G: drives, as C: drive space is limited, and files on the C: drive are not guaranteed to be preserved after logout.
  • If all licenses are in use, Mimics will go straight to a screen asking to configure a new license. If this happens, click “Cancel”.
Software Interactive/GUI: 
No

Bowtie

Software Support Level: 
Primary Support
Software Description: 

Bowtie is an ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of over 25 million 35-bp reads per hour. Bowtie indexes the genome with a Burrows-Wheeler index to keep its memory footprint small: typically about 2.2 GB for the human genome (2.9 GB for paired-end).

Software Access Level: 
Open Access
PBS Example: 
Bowtie programs may also be submitted to a queue using PBS script such as the one below:
#PBS -l nodes=3:ppn=8,pmem=1000mb,walltime=8:00:00
#PBS -m abe
#PBS -M sample_email@umn.edu

module load bowtie

bowtie2 -p $PBS_NP reads/e_coli_10000snp.fq ec_snp.sam

Note the use of -p $PBS_NP; this option is used to specify the number of threads used by Bowtie.  Also note that only 0.X versions of Bowtie are available on Itasca and Cascade.

Software Categories: 
Software Interactive/GUI: 
No
General Linux Documentation: 
To run this software interactively in a Linux environment run the commands:
module load bowtie
bowtie ...

For bowtie versions 2.0 and above, use the program "bowtie2" instead of simply "bowtie".

To see a list of available options, type the command

bowtie2 -h
Pre-built bowtie indexes for popular genomes are available at
/project/db/genomes/[species]/[build]/bowtie2
Bowtie programs may also be submitted to a queue using PBS script such as the one below:
#PBS -l nodes=3:ppn=8,pmem=1000mb,walltime=8:00:00
#PBS -m abe
#PBS -M sample_email@umn.edu

module load bowtie

bowtie2 -p $PBS_NP reads/e_coli_10000snp.fq ec_snp.sam

Note the use of -p $PBS_NP; this option is used to specify the number of threads used by Bowtie.  Also note that only 0.X versions of Bowtie are available on Itasca and Cascade.

Compatibility issues:
Bowtie genome indexes built using 0.X versions are not compatible with indexes built using 2.X versions.  Significant changes (improvements) have been made to Bowtie command-line options, and to how Bowtie performs alignments.  To see a list of installed Bowtie versions type the command
module show bowtie
Bowtie 0.X genome indexes are available at
/project/db/genomes/[SPECIES]/[BUILD]/bowtie
Additional Information

Supernovae of Early Supermassive Stars

Most galaxies that we have observed contain at their centers a supermassive black hole. While scientists don’t know how these black holes were formed, they have surmised that they could be the remnants of supermassive stars that, at the end of their lives, collapsed to create the black holes...

The Fungal Microbiome in Infants

Research has shown that the human microbiome - the community of microorganisms that inhabit our bodies - may have health implications. It’s possible, for example, that a certain mixture of these microorganisms may cause certain diseases. Researchers have recently begun to study the microbiome in...

Targeting Drugs to Tumors

One of the most promising methods of treating cancer is called “tumor-homing” or “targeted drug” therapy. In this method, a cancer drug is linked to a kind of peptide called a “tumor-homing” peptide – the tumor-homing peptide recognizes a specific receptor that appears on tumors, thereby guiding...

Large Scale Machine Learning and Its Applications

Abstract: 

Large Scale Machine Learning and Its Applications

This group works on large scale machine learning and data analysis, applied to the problems of climate prediction, anomaly detection and recommendation systems. Each of these problems involves large number of computations as they search through piles of explicit and implicit information, either observed or unobserved. The researchers are working on three projects during 2016, all of which require HPC resources.

  • Anomaly detection: This project is concerned with the analysis of a large flight dataset to discover anomalous aviation situations. The dataset contains about 180,000 flights, each consisting of 186 time-series of various lengths.
  • Recommendation system: The objective of this project is to build a model for news article recommendation. The accuracy of the ranked list of recommended items is expected to be computed in large scale datasets, where at least millions of observations (users who rated/clicked on an article) is given. Although online models will be tested, the researchers also need to compare them with offline models, for which all training data will be needed.
  • Deep learning methods for climate science: This project will train deep networks for prediction tasks on Global Climate Model (GCM) climate datasets. The output of all GCM models combined consist of around 50,000 observations, each of which has 10,000-60,000 dimensions of observations of various climatic parameters like temperature, precipitation etc. The dataset is to be used for two prediction tasks: prediction of Indian summer monsoon rainfall, and prediction of air temperature on nine land locations in different parts of the world. Each of these areas will explore the use of deep learning models like convolutional nets, recurrent nets, restricted Boltzmann machines, auto-encoders, etc. with each model having many parameters to be trained. The researchers believe that this is one of the first applications proposing using deep networks on GCM datasets and as such will require running multiple iterations of these models for tuning and testing.

Return to this PI's main page.

Group name: 
srivbane

2018-20 McKnight Land-Grant Professors Include MSI PIs

Four MSI PIs are among the faculty selected for McKnight Land-Grant Professorships for 2018-20. The goal of this program is to advance the careers of new assistant professors. Ran Blekhman ; Genetics, Cell Biology and Development Project: Using genomics to understand how the microbiome impacts...

New Citizen-Science Project, Snapshot Safari, Launches

Snapshot Safari ( www.snapshotsafari.org ), a citizen-science project created by the University of Minnesota’s Lion Center , launched in February 2018. The Lion Center is headed by MSI PI Craig Packer , a Distinguished McKnight University Professor in the Department of Ecology, Evolution, and...

ProteinPilot

Software Description: 

ProteinPilot™ Software can perform protein identification and quantitation, along with prediction of hundreds of peptide modifications and non-tryptic cleavages simultaneously. The protein grouping algorithm helps in distinguishing protein isoforms and visualize peptide-protein associations and relationships. The new version can take in generic input for non-AB SCIEX instruments via .mgf format. Other features include : Automatic and Rigorous False Discovery Rate (FDR) Analysis; Improved Quantitation for iTRAQ Reagent-Based Workflows; Speed and Scalability Improvements; Extended Gel Workflow Support; Open Control of Parameter Settings; Extended Support for Instruments from Other Vendors; Improved Identification Quality; Command Line Control and Open Results.

Currently, MSI has only one ProteinPilot license. We ask that all users use the calendaring program to sign up for time on ProteinPilot. Please specify your name on the calendar. Prior to using the calendar for the first time please email help@msi.umn.edu to request access to the ProteinPilot calendar. Please limit your ProteinPilot reservation to less than 24 hours at a time. If you need additional time after your 24 hour session has ended and the license is not reserved you may reserve another 24 hour session.  If you are not able to reserve time on the calendar please email help@msi.umn.edu.

You can use the following links to see the ProteinPilot calendar and reserve the license: ProteinPilot Calendar

Follow the instructions at https://www.msi.umn.edu/calendar/instruction.html to add a reservation to the calendar.

 

Software Support Level: 
Primary Support
Software Access Level: 
Limited Licenses
Citrix Documentation: 

ProteinPilot™ Software v. 5.0 is available in the "Node-Locked Software" virtual desktop at xen.msi.umn.edu. Instructions for connecting to xen.msi.umn.edu are available here. There are many new features and performance improvements in this version. Please read the Release Notes carefully to make sure you are aware of the changes.

Restore Files
If you modify the Data Dictionary and Parameter Translation files on the Xen ProteinPilot 4.5 version you must restore these files to the Original Modification Parameters after you complete your search so that the next user can ensure that the Standard, Unmodified Parameters were in use for their own search. We urge everyone to adhere to this policy.

Modifications to these files can drastically affect results outcome, in some cases, depending on exactly what modifications were made.
 

Clean Up Your Files
The C: drive on Xen (with node-locked licenses for ProteinPilot 4.5 version and Scaffold) has been getting full with input MGF files, search databases and output search results. We request that users back up and copy their .group, .sf3, MGF and other files once the searches are complete. Users can back up data to U: drive or any other location. Once you have backed up your files, remove the files from the C: drive so that there is enough space available for any new searches.

 

ProteinPilot is also available on Galaxy-P (https://galaxyp.msi.umn.edu). A screencast for using ProteinPilot within Galaxy-P is available at: http://z.umn.edu/ppingp

A "viewer" version of the software is available on all other MSI Windows systems. Please note that this version of software can be used to view previously generated .group files. This version cannot be used for searching the data. For searching data, use ProteinPilot on the "Node-Locked Software" virtual desktop, or via Galaxy-P as mentioned above.

Some highlights in the new version:
  • Improved quantitation results for SILAC and other survey-level quantitation

  • Improved mass accuracy from better feature detection

  • Improved identification results

  • Support for new AB SCIEX instruments released in 2012, including the TripleTOF® 4600, TripleTOF® 5600+, QTRAP® 4500, and QTRAP® 6500 systems.

  • Peptide shared status is provided for better downstream use of ProteinPilot results with the MS/MSALL with SWATH™ Acquisition MicroApp 1.0 add-in for PeakView® Software (versions 1.2.0.3 or higher)

  • New Spectrum Summary export

  • Reduction in false singleton and blank ratios

A number of tutorial materials and webinars have been created for ProteinPilot users.   You can find a complete list here.

 
 
Software Categories: 
Software Interactive/GUI: 
No

Visit by Representative Erik Paulsen

U.S. Congressman Erik Paulsen, who represents Minnesota's 3rd District, visited the LCSE-MSI Visualization Laboratory on September 26, 2011. Rep. Paulsen was on campus to meet with officials from the Office of Technology Commercialization and a start-up company spun out of the University to talk...

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