May 1, 2019
Uncovering complex relationships in biomedical data through hierarchical logic pattern contrast mining
Understanding the relationships which exist between features in medical data ranging from electronic health records to genetic variations in sequenced genomes is key to understanding how these features impact the medical condition of an individual. Existing pattern mining methods are unable to discover relationships more complex than co-occurrence which limits their usefulness in searching for patterns associated with medical conditions which may include inhibitory and many-to-one relationships between features. Our algorithm can extract complex nested logical relationships which can provide additional information about how individual features interact to affect medical outcomes. We demonstrate the effectiveness of our algorithm on two…
April 9, 2019
Linking EMR and Exposome Data for Risk Prediction and Interventions: A Translational Approach
Precision medicine (PM) is a medical model that proposes the customization of healthcare, with medical decisions, treatments, practices, or products being tailored to the individual patient. An individual’s “Social Determinants of Health” (SDOH) have been demonstrated as a key factor in obtaining successful clinical outcomes for individual patients which necessitate individualized interventions. Two major problems exist in addressing SDOH within a clinical setting. First, interventions that have shown to be successful in addressing challenges presented by various Social Determinants of Health often scarce and span outside of those services that are available and/or reimbursed within a healthcare setting. Because of this, it is critical…
April 9, 2019
Image Segmentation in Colorectal Tissue Slides Using Denoising Autoencoder
Colorectal cancer (CRC) is a common tumor type with variable treatment course. Given the high availability of histological slides and wealth of the prognostic information the slide images may provide, it is important to conduct corresponding image analysis in high-throughput fashion. In this presentation, we will discuss a segmentation approach based on denoising autoencoder for colorectal whole slide images using annotated image patches.
April 5, 2019
TEACHING FACULTY POSITION OPEN – Join an award-winning, on-line, professional master’s program teaching Data Science and Analytics to working professionals from all around the US
The University of Missouri (MU) Informatics Institute is accepting applications for position of Assistant or Associate Teaching Professor of the Data Science and Analytics (DSA) program. We are looking for data scientists with rich industry experience to work in a vibrant environment to educate working professionals to enter the data science workforce. In today’s information-centric world, data are becoming increasingly important for the success of businesses in every industry. The demand for data scientist in the American workforce is expected to continue to grow at a healthy pace for the next ten years and so is the MU Data Science…
April 3, 2019
Climate-driven urban heat and its adaptation at a large scale
Abstract Among many globally recognized environmental problems such as water scarcity, air pollution, and energy security, heat stress is one of the most severe climate-driven threats to the human society. The situation is further exacerbated in urban areas by urban heat islands (UHIs). Absent measures to ameliorate them, the problems associated with heat stress are expected to intensify due to rapid urban development coupled with climate change. One significant barrier to heat mitigation through urban engineering is the lack of quantitative attribution of the various surface processes toUHI intensity. In this seminar, the intrinsic mechanism of UHI and its quantitative…
March 28, 2019
MUII Core Faculty Lead the Way in Comparative Oncology
Dr. Jeff Bryan, an MUII core faculty member from the College of Veterinary Science, presented preliminary research at the Veterinary Cancer Society Annual Conference in Louisville, KY on his recent research on a canine bone cancer vaccine that could have promising benefits for humans. Click on the link to learn more.
March 27, 2019
DATA MINING FOR GENETIC CONTRIBUTIONS TO THE ETIOLOGY OF AUTISM SUBGROUPS
Autism is a collection complex neurological disorders characterized by behavioral, social, and cognitive deficits. Previous investigation of the etiology of autism reveals it to be a complex disorder with no simple way to identify its root cause in most affected individuals. The difficulty determining causal variation leads to the hypothesis that multiple genetic risk factors are necessary in combination to produce the autistic phenotype. Furthermore, the immense phenotypic heterogeneity seen in autism patients leads to a second hypothesis that there exist multiple subtypes of autism with distinct genetic etiologies. We developed new methods combining strategies from bioinformatics, data science, and…
March 20, 2019
What Can We Learn from a Hundred Thousand E. coli Genomes?
Feb. 27, 2019
Computational prediction of ubiquitination proteins using evolutionary profiles and functional domains
Ubiquitination, as a post-translational modification, is a crucial biological process in cell signaling, apoptosis and localization. Identification of ubiquitination proteins is of fundamental importance for understanding molecular mechanisms in biological systems and diseases. Although high-throughput experimental studies using mass spectrometry have identified many ubiquitination proteins and ubiquitination sites, the vast majority of ubiquitination proteins remain undiscovered, even in well studied model organisms. To reduce experimental costs, computational methods have been introduced to predict ubiquitination sites, but the accuracy is unsatisfactory. If we can predict whether a protein can be ubiquitinated or not, it is meaningful by itself and helpful for…