MU-LOC: A Deep Neural Network Method for Predicting Mitochondrially Localized Proteins in Plants
Targeting and translocation of proteins to the appropriate subcellular compartments is crucial for cell organization and function. Newly synthesized proteins are transported to mitochondria with the assistance of complex targeting sequences containing either an N-terminal pre-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale…
An Analysis of Diabetes Mobile Applications Features Compared to AADE7TM: Addressing Self-Management Behaviors in People with Diabetes
Diabetes Self-management (DSM) applications (apps) have been designed to improve knowledge of diabetes and self-management behaviors. However, few studies have systematically examined if diabetes apps followed the American Association of Diabetes Educators (AADE) Self-Care BehaviorsTM guidelines. The purpose of this study was to compare the features of current DSM apps to the AADE7TM guidelines. In two major app stores, we used three search terms to capture a wide range of diabetes apps. Apps were excluded based on five exclusion criteria. A multidisciplinary team analyzed and classified the features of each app based on the AADE7TM. We conducted interviews with six…
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…
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…
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…
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…
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…
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%).
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…