George Mias
Assistant Professor, Department of Biochemistry and Molecular Biology Michigan State University
Media
Biography
Current research in his lab focuses on the analysis and integration of existing and developing -omics technologies, their application to monitoring individuals as they transition through various physiological states and their implementation towards personalized health.
Industry Expertise
Areas of Expertise
Education
Yale University
Ph.D.
Physics
2007
Yale University
M.Phil.
Physics
2003
Yale University
B.S. & M.S.
Physics
2001
Magna Cum Laude with Distinction
Affiliations
- Bioinformatics geeks
- Precision Medicine Insight
Links
News
Genomics reveal surprises about Florida Zika Outbreak
Medscape online
2017-03-04
"The take home message is that we need to diagnose or detect much earlier," said George Mias, PhD, of Michigan State University in East Lansing...
MSU student shunned in Egypt wins coveted PD Soros fellowship
MSU Today
2015-04-14
He plans to finish his doctorate at MSU where he is working with George Mias, physicist and geneticist, on research that focuses on “omics” technologies and their applications in personalized/precision medicine...
Journal Articles
MathIOmica: An integrative platform for dynamic omics
NCBI2016
Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.
Transcriptomic Evaluation of CD34+ Marrow Cells from Myelodysplastic Syndrome (MDS) Patients
Blood Journal2014
Prior studies using microarray platforms have shown alterations of gene expression profiles (GEPs) in MDS CD34+ marrow cells related to clinical outcomes (Sridhar et al, Blood 2009, Pellagatti et al, JCO 2013). Given the increased sensitivity and accuracy of high-throughput RNA sequencing (RNA-Seq) (Mortazavi et al, Nat Meth 2008, Soon et al, Mol Syst Bio 2012) for detecting and quantifying mRNA transcripts, we applied this methodology for evaluating differential gene expression between MDS and normal CD34+ marrow cells.
Integrating dynamic omics responses for universal personalized medicine
American Society of Animal Science2013
The advent of readily available omics technologies, and the recent Precision Medicine Initiative announced by the White House and National Institutes of Health are guiding our efforts to make advances in the implementation of personalized medicine. High quality genomes are now complemented with other dynamic omics data (e.g. transcriptomes, proteomes, metabolomes), that may be used to profile temporal patterns of thousands of molecular components in individuals. We are pursuing the profiling of multiple such omics in parallel n=1 studies that extend the pilot integrative Personal Omics Profiling (iPOP) approach to diseases affecting the immune system. In particular, we will describe our investigations that follow longitudinally healthy and asthmatic individuals, and the integration of multiple omics obtained from peripheral blood cells, that we believe may provide novel medical insights.
Toward more transparent and reproducible omics studies through a common metadata checklist and data publications
OMICS2013
Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.
Whole-exome sequencing identifies tetratricopeptide repeat domain 7A (TTC7A) mutations for combined immunodeficiency with intestinal atresias
ScienceDirect2013
Combined immunodeficiency with multiple intestinal atresias (CID-MIA) is a rare hereditary disease characterized by intestinal obstructions and profound immune defects.
