An RNAmazing research breakthrough
December 19, 2017
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.
Dr. Gregory Alexander recently awarded AHRQ grant.
October 9, 2017
Dr. Gregory Alexander, from The Sinclair School of Nursing, was recently awarded a $1,995,522.00 AHRQ grant. This grant will support an interdisciplinary research team who are already contributing to clinical research in long-term care settings. The PI is a doctorally-prepared RN and fellow in the American Academy of Nursing with over two decades of work […]
Dr. Elizabeth King recently awarded National Science Foundation grant
September 13, 2017
Drs. Troy Zars and Elizabeth King, in the Division of Biological Sciences, were recently awarded a $462,900 National Science Foundation grant! This grant will be providing funding for a project which will focus on how genes underlie variation in learning and memory performance in fruit flies. Additionally, this grant will support an outreach program called […]
2206C Student Center
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 interference between the two circuit functions while sharing the same physical implementation of a network of spiking neurons.
We discovered three important differences between the storage and retrieval circuits. First, they had difference in how they produced runaway excitation, an aberrant spread of brain activity leading to seizures. Second, the two circuits had distinct mechanisms to maintain control over runaway excitation spread. These two findings provided the first classification of seizures based on the functional state of the brain, and suggested the need for specific treatments for each type.
Third, we found the two circuits also had unique ways of generating theta rhythmic activity, which is theorized to have a fundamental role in memory storage and retrieval. Our model uncovered an unexpected complexity in theta rhythm generation across functional states of the circuit. These findings can allow for deciphering the computations carried out by the circuit, based on the engaged mechanisms of rhythm generation.
2206A Student Center
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 in the form of relational triples. Relational triples are statements of a single fact composed of subject-relation-object. These triple statements allow the development of knowledge bases, knowledge graphs or the application of inference rules. In our research, we employ Stanford’s CoreNLP engine for information extraction in triple format. This format helps us to develop Resource Description Framework (RDF) networks where each subject and object become nodes and the edges represent the relations between the nodes. However, most of the triples produced by CoreNLP convey multiple facts (compound triple), instead of a single fact (atomic triple). Compound triples produce networks with nodes representing multiple entities instead of a single entity causing issues of network representation of our data. Here, we extend the use of CoreNLP to atomize compound triples. Our approach is based on the N-ary relational schema that links an individual to multiple individuals or values. Our approach includes triple decomposition and ontological modeling.
2205 A&B Student Center
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 frequency similarity” (CUFS), Ka/Ks ratio and gene expression similarity. Our simulation indicates that evolutionary selection pressure of an orthologous pair (Ka/Ks ratio) is more strongly correlated with its histone modification than any other similarity measure. We also found that genes with low Ka/Ks have more similar histone profiles across species than the ones with high Ka/Ks, suggesting more differential regulation for genes with higher selection pressure.