Oct. 11, 2016

A Metagenomic Analysis of the Effect of Residual Feed Intake on Rumen Metabolism

Ruminant animals have a symbiotic relationship with gastrointestinal microorganisms in the rumen where microbes degrade compounds that can be used in the host animal’s metabolism. Currently, changes in the diet or feed efficiency of the sheep results in differences to the rumen’s microbiota population. By using a metabolic approach, the effects of differing residual feed intake (RFI) on the rumen’s microbiome are analyzed to determine the network interface between the host’s metabolism and rumen microbiome. These findings demonstrate important network structure differences between low and high RFI animals providing a greater understanding of the complexities in the rumen ecosystem.

Oct. 7, 2016

Big Data Colloquium Distinguished Speaker – Dr. Jianjiong Gao

Thanks to the advancements of technology such as next-generation sequencing, an overwhelming amount of cancer genomics data has been generated by large-scale cancer genomics projects such as The Cancer Genome Atlas (TCGA). This has imposed an increasing challenge in the translation of the wealth of the resulting “big data” into biological discoveries and clinical applications. In this talk, I will present two major platforms we developed at Memorial Sloan Kettering Cancer Center to address this challenge: cBioPortal and OncoKB. The cBioPortal for Cancer Genomics (http://cbioportal.org/) collects, integrates, and visualizes multi-dimensional, high-level cancer genomics and clinical data. It was specifically…

Sep. 19, 2016

Diabetes Self-Management Applications: Focus Group Findings from Elderly Diabetic Patients

The number of mobile diabetes self-management (DSM) apps has risen. However, it is not certain whether these apps provide effective DSM for elderly diabetic patients. The purpose of this study was to identify barriers in functionality and usability related to needs of elderly diabetic patients for DSM apps. We conducted two focus groups with 10 older diabetic patients. Participants completed a set of DSM tasks using nine representative DSM apps on iPads. They answered a questionnaire which included basic information, System Usability Scale (SUS), app specific questions, and open-ended questions. We found DSM apps did not adhere to diabetes guidelines.

Sep. 2, 2016

Big Data Colloquium Distinguished Speaker – Dr. Philip S. Yu

The problem of big data has become increasingly importance in recent years. On the one hand, big data is an asset that potentially can offer tremendous value or reward to the data owners. On the other hand, it poses tremendous challenges to distil the value out of the big data. The very nature of big data poses challenges not only due to its volume, and velocity of being generated, but also its variety, where variety means the data can be collected from various sources with different formats from structured data to text to network/graph data, etc. In this talk, we…

Sep. 1, 2016

MUII’s Data Science and Analytics Master’s Program to Deliver Cutting-Edge Training to the NGA with $12 Million Federal Contract

The University of Missouri College of Engineering has just been awarded a five-year, $12 million contract to deliver a comprehensive data science education program that will provide cutting-edge analytical training for the NGA workforce and potentially other members of the U.S. Intelligence Community (IC). This new program will address key education and training needs identified by NGA. The program is a collaboration between the MU College of Engineering’s Center for Geospatial Intelligence (CGI) and the MU Informatics Institute’s Data Science and Analytics (DSA) master’s degree program. The newly established effort is part of the NGA College’s Learning Outreach program that partners with qualified…

Aug. 24, 2016

Soybean science blooms with supercomputers

Soybean Knowledge Base (SoyKB) project finds and shares comprehensive genetic and genomic soybean data through support of NSF-sponsored XSEDE high performance computing. SoyKB helps scientists improve soybean traits. XSEDE Stampede supercomputer 370,000 core hour allocation used in resequencing of over 1,000 soybean germplasm lines. XSEDE ECSS established Pegasus workflow that optimized SoyKB for supercomputers. SoyKB migrated workflow to XSEDE Wrangler data intensive supercomputer. http://www.nsf.gov/news/news_summ.jsp?cntn_id=189594&WT.mc_id=USNSF_195&WT.mc_ev=click

July 5, 2016

Families In Rural Areas Using Telemedicine For Psychiatric, Specialty Care

Mirna Becevic, PhD, an assistant research professor of telemedicine at the School of Medicine, recently was featured in an article by Forbes. Becevic led a study that shows that video-based mental health services are bridging the gap by providing care to underserved areas   http://www.forbes.com/sites/janetwburns/2016/07/05/families-in-rural-areas-using-telemedicine-for-psychiatric-specialty-care/#2746f6334df0…

April 29, 2016

MUII Defense Announcement – Andrew Hutson

Background: The percentage of patients with polypharmacy needs is increasing among a growing patient population. As a result, the amount of time health care professionals require to make clinical decisions based on current and past medications is increasing. Health care professionals need methods for increasing the speed of clinical decision making without sacrificing the quality of care.  The goal of this study is to demonstrate how modifying the data visualization for patient medication histories will change decision making speed or efficacy. Methods: We compared two groups across five randomized blocks. Group 1 responded to questions based on the control data…

April 15, 2016

MUII Defense Announcement – Ginger Han

Biomedical image data have been growing quickly in volume, speed, and complexity, and there is an increasing reliance on the analysis of these data. Biomedical scientists are in need of efficient and accurate analyses of large-scale imaging data, as well as innovative retrieval methods for visually similar imagery across a large-scale data collection to assist complex study in biological and medical applications. Moreover, biomedical images rely on increased resolution to capture subtle phenotypes of diseases, but this poses a challenge for clinicians to sift through haystacks of visual cues to make informative diagnoses.  To tackle these challenges, we developed computational…