UVA School of Medicine

Research Computing

Enabling scientific breakthroughs at scale with advanced computing

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  • Image Processing

    Automatic image processing allows researchers to perform their work faster for large quantities of data. From image denoising to registration to segmentation, SOM Research Computing can help researchers utilize image processing tools to streamline their analyses. Applications for Researchers Preprocessing Image preprocessing can help enhance the quality of your images. Common preprocessing techniques include adjusting brightness and contrast, removing noise, sharpening images, and performing geometric and color transformations.
  • Bioinformatics & Genomics

    School of Medicine Research Computing (SOMRC) provides state-of-the-art resources and expertise in handling and analyzing genomics and metagenomics data. Bioinformatics is a quickly evolving field with new biological and computational techniques being formalized and adopted at a fast pace. Hence, the following is only a brief cross-section of the ways researchers can use SOMRC’s expertise and computing resources for their bioinformatics research. Next-generation sequence data analyis SOMRC can support in-depth analysis of various next-generation sequencing experiment datasets on your desktop/Rivanna/Ivy/Cloud.
  • Bioinformatics Resources on Rivanna

    UVA research community has access to numerous bioinformatics software installed and ready-to-use on Rivanna. They are all available via the LMod module system. In addition, Click here for a comprehensive list. Popular Bioinformatics Software Below are some popular tools and useful links for their documentation and usage: .tg {border-collapse:collapse;border-spacing:0;border-color:#ccc;} .tg td{font-family:Arial, sans-serif;font-size:14px;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#fff;} .tg th{font-family:Arial, sans-serif;font-size:14px;font-weight:normal;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#f0f0f0;} .tg .tg-hy9w{background-color:#eceeef;border-color:inherit;vertical-align:middle;} .tg .tg-dc35{background-color:#f9f9f9;border-color:inherit;vertical-align:middle;} .tg .tg-hy9w-nw{background-color:#eceeef;border-color:inherit;vertical-align:middle;white-space:nowrap;} .tg .tg-dc35-nw{background-color:#f9f9f9;border-color:inherit;vertical-align:middle;white-space:nowrap;} .tg .tg-0qmj{font-weight:bold;background-color:#eceeef;border-color:inherit;vertical-align:middle;} .scroll thead, .
  • Bioinformatics User Guides

    Bioinformatics on Rivanna UVA’s High-performance Computing Cluster All faculty, research staff and graduate students of UVA have access to Rivanna, university’s high-performance computing system with 290+ compute nodes (6500+ cores) for high-throughput multithreaded jobs, parallel jobs as well as memmory intensive large-scale data analyses. The architecture is specifically suited for large scale distributed genomic data analysis, with 100+ bioinformatics software packages installed and ready to use. Learn more Bioinformatics using FireCloud FireCloud Home
  • Data Analysis

    School of Medicine Research Computing can help with accessing, preparing, visualizing and analyzing data. We can assist you by implementing your analysis strategy in an appropriate computing language, including R, Python and Matlab. We will work with you to prepare scripts that are are reproducible, efficient and flexible. Manipulation Data analysis generally involves a significant effort to transform, aggregate, subset or otherwise prepare a dataset. That could include dealing with missing values as well as merging or joining multiple datasets.
  • Scientific Computing

    School of Medicine Research Computing supports SOM and UVa Medical Center researchers who are interested in writing code to address their scientific inquiries. Whether these programming tasks are implemented interactively, in a series of scripts or as an open-source software package, services are available to provide guidance and enable collaborative development. SOMRC has specific expertise in object oriented programming in Matlab, R, and Python. Examples of service areas include: Collaborating on package development Reviewing and debugging code Preparing scripts to automate or expedite tasks Developing web interfaces for interactive data exploration Advising on integration of existing software tools UVA has two local HPC facilities available to researchers: Rivanna and Ivy.