Jan. 28, 2018
Collaborations across disciplines: MU Thyroid Nodule Electronic Database (MU-TNED), a multidisciplinary informatics approach
Thyroid nodules are common findings and thyroid cancer is projected to be one of the leading causes of cancer in women. The EHR includes the necessary data needed to connect clinical research with patient outcomes. The objective for this project was to develop and validate a usable informatics tool for clinicians and researchers to record, analyze, and be able to manipulate the clinical and research data to benefit all collaborators. The tool was specifically designed to enable follow-up in a longitudinal manner to support multiple aspects of research. The informatics tool MU-TNED was designed with a multidisciplinary team including the…
Dec. 19, 2017
An RNAmazing research breakthrough
Professor of Bioengineering and the Dalton Cardiovascular Research Center Li-Qun (Andrew) Gu and Shi-Jie Chen, joint Professor of Physics, Biochemistry and the MU Informatics Institute and their team recently published “Nanopore electric snapshots of an RNA tertiary folding pathway,” in the prestigious journal Nature Communications.
Dec. 5, 2017
MODELING THE HIPPOCAMUS: FINELY CONTROLLED MEMORY STORAGE USING SPIKING NEURONS
The hippocampus, an area in the temporal lobe of the mammalian brain, participates in the storage of personal memories and life events, including traumatic memories and the consequent symptoms of post-traumatic stress, giving importance to the study of the machinery of hippocampal memory storage and retrieval. The circuit is known to be controlled by the neuromodulator Acetylcholine, which switches the circuit between the memory storage state and the memory retrieval state. We built a computational model of the hippocampus with the ability to perform both memory storage and retrieval functions, controlled by the level of Acetylcholine. This functional separation decrease…
Dec. 1, 2017
Use of the N-ary Relational Schema to Atomize Compound Relational Triples
Electronic medical records document health information in structured format and in unstructured free text format. Health information in structured format contains laboratory results, vital signs, patient demographics etc. The unstructured free text is the prime source of healthcare information documenting providers’ interpretations of health conditions, diagnoses, medical interventions, impressions, etc. In order to uncover unknown information and search for patterns in health data with computational methods, we need to structure the unstructured free text data. For that, we use information extraction, a computational technique for analyzing free text and deriving structured information. Extracted information from free text can be represented…
Nov. 26, 2017
Effects of evolutionary pressure on histone modifications
With the advent of next-generation sequencing technologies, a considerable effort has been put into sequencing the epigenomes of different species. The efforts such as “Encode” and “Roadmap” epigenomics projects provide an opportunity to compare epigenomes across species (especially between human and mouse). This study is an effort to understand how different histone modifications vary/co-appear between orthologous regions of the two species. In this work, we have used various measures of orthologous similarity between each pair of orthologous genes and explore how histone modifications are conserved with respect to changes in these similarity measures. These measures of similarity include “codon usage…
Nov. 15, 2017
An Interventional Informatics Approach to Development and Evaluation of Population-based Health and Web Technologies
Interventional informatics is the use of health information technology (HIT) which drives evidence-based and evidence-generating practices to inform an improved health delivery system. Current HIT lacks movement towards data-driven infrastructures designed to promote information gathering, sharing, and new knowledge discovery in several areas. This thesis undertakes three specific areas where gaps exist. First, in undertaking quality improvement initiatives aligned with fidelity to program models, a web-based practice exchange was designed, built, tested and launched. Second, a systematic review of eHealth technology instruments for outcomes and evaluation components geared towards patient outcomes was conducted, uncovering gaps in the availability of psychometrically…
Nov. 3, 2017
Investigating genome composition in multiple bee species
The honey bee Apis mellifera was the first eusocial animal to have its genome assembled. Analysis of the complete draft sequence of the honey bee genome revealed several interesting features compared with the other metazoan genomes: a low but heterogeneous GC content, an overabundance of CpG dinucleotides and a lack of repetitive elements. The average GC content of the honey bee genome is only 33%, but GC content is highly heterogeneous, ranging from 11% to 67%, with a bimodal distribution. Furthermore, unlike genes in most other metazoans, honey bee genes are overly abundant in regions of low GC content (<30%).
Oct. 23, 2017
A Geospatial Health Context Table for Supporting Public Health Research
This project develops a Big Data table that allows researchers to query across and among multiple data sources integrated by location. The big table created in this way uses location as the fundamental linkage between data sets. This is the power of geospatial analysis and forms the foundation for the development and interaction with the Health Context Table. The approach utilizes a dense point file populated with attribution derived or obtained directly from public data sources and associated geospatial analysis. The database created extends across the entire continental United States comprising over 300 million points. The data table has at…
Oct. 11, 2017
Contrast mining to discover combinations of genetic factors associated with autism subgroups
Autism is characterized by a complex set of behavioral, social, and cognitive deficits. Extensive variation of these phenotypes suggests the existence of autism subtypes that likely have distinct genetic etiologies. The lack of unifying genotypes common to autism patients supports this subtype structure, and suggests that the onset of autism is due to combinations of genetic factors. The ability to precisely diagnose autism subtypes using genetic markers would lead to earlier and more specific treatments and improve outcomes, stressing the need for research which increases our understanding of the genetic etiologies of autism subtypes. In this research, we identify combinations…