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Michaela Oswald, PhD

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Research Scientist, The Feinstein Institute for Medical Research

Phone: (516) 562-1607
Email: moswald@nshs.edu

About the Investigator

Dr. Michaela Oswald received her masters degree in Theoretical Physics from the University of Graz, Austria in 2001 and her PhD in Theoretical Physics from the Niels Bohr Institute at the University of Copenhagen, Denmark, in 2004. After that she was recruited for a postdoctoral fellowship in the Physics Department at the University of Virginia in Charlottesville. During that time Dr. Oswald became interested in Biology and Medical Research, and in 2007 she was awarded a Sloan-Swartz fellowship to transition into biological data analysis at Cold Spring Harbor Laboratory (CSHL).

In 2010 she joined the Boas Center for Genomics and Human Genetics as a Research Scientist. She has since established successful collaborations with many of Feinstein’s excellent faculty members and uses her background in quantitative sciences and her data analysis abilities for a multitude of scientific projects.

In addition, Dr. Oswald has also taught in the Genetics Course at the Elmezzi Graduate School of Molecular Medicine and has been a reviewer for the Elsevier journal Computational Biology and Chemistry.

Research Focus

Most recently Dr. Oswald has predominantly worked with micro array, microRNA, and RNA-Seq expression data, as well as with protein quantification data. She uses both existing methods and develops new data analysis pipelines.

Her recent projects include:

miRNAs as biomarkers in Cancer

In collaboration with Dr. Annette Lee and Dr. Iuliana Shapiro, Dr. Michaela Oswald looks at microRNA expression in ovarian and breast cancer patients. An additional network approach that combines gene and miRNA expression information has been applied to ovarian cancer samples.

Together with Dr. Manish Vira from the Urology Department, prostate cancer specimens are investigated with respect to their microRNA expression profiles.

Gene expression and biomarkers in autoimmune diseases

Gene Expression in Systemic Lupus Erythematosus (SLE) is investigated in collaboration with Dr. Betty Diamond and Dr. Meggan Mackay. In particular differences between active and inactive SLE as well as between SLE flare and sepsis are studied for mRNA biomarkers in peripheral blood.

In addition, the effect of Vitamin D treatment on gene expression in SLE patients is analyzed in a project together with Dr. Betty Diamond and Dr. Cynthia Aranow.

Gene Set and modular expression analysis is applied to several projects. Together with Dr. Peter Gregersen, it was found that a modular analysis of peripheral blood gene expression in rheumatoid arthritis (RA) captures reproducible gene expression changes in TNF responders.

Gene expression profiles as markers for new cell types

Together with Dr. Peder Olofsson, within the laboratory of Dr. Kevin Tracey, Dr. Oswald has succeeded in identifying a new cell type based on its transcriptional profile.

In the framework of Accelerating Medicines Partnerships (AMP), more cell type specific biological information is being studied both for SLE and RA.

Education

University of Graz, Austria
Degree: Masters of Natural Sciences
2001
Filed of Study: Theoretical Physics

The Niels Bohr Institute at the University of Copenhagen, Denmark
Degree: PhD
2004
Field of Study: Theoretical Physics

Publications
  1. Oswald M, Curran M, Lamberth S, Townsend R, Hamilton JD, Chernoff DN, Carulli J, Townsend M, Weinblatt M, Kern M, Pond C, Lee A, Gregersen PK. “Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders”. Arthritis Rheumatol. 2014 Nov 4. doi: 10.1002/art.38947
  2. Gregersen PK, Oswald M. “Editorial: the power of a modular approach to transcriptional analysis”. Arthritis Rheumatol. 2014 Jun;66(6):1418-20. doi: 10.1002/art.38629
  3. Shapira I, Oswald M, Lovecchio J, Khalili H, Menzin A, Whyte J, Dos Santos L, Liang S, Bhuiya T, Keogh M, Mason C, Sultan K, Budman D, Gregersen PK, Lee AT. “Circulating biomarkers for detection of ovarian cancer and predicting cancer outcomes.” Br J Cancer. 2014 Feb 18;110(4):976-83. doi: 10.1038/bjc.2013.795

View more at PubMed

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