Walsh Medical Media

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Editor Interview file: 20064-yixing-han-interview.pdf

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Editor Biography:

Dr. Yixing Han is a highly accomplished scientist with a strong background in developmental biology, computational biology, and bioinformatics.

Dr. Han received her Ph.D. in Developmental Biology and Computational Biology from the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China, in 2011. Her thesis focused on epigenetic landscape changes during primate brain development and aging. She then pursued postdoctoral research at the National Cancer Institute, National Institutes of Health (NIH), from 2012 to 2016.

Dr. Han has held various academic appointments, including Staff Scientist at the National Human Genome Research Institute, NIH, since 2021. She has also worked as a Bioinformatics Scientist III at Ambry Genetics Corporation and a Senior Bioinformatics Scientist at the National Cancer Institute, NIH.

Dr. Han's research expertise spans genomics, bioinformatics, computational biology, and data science. She has published numerous peer-reviewed articles, book chapters, and conference abstracts, and has presented her work at various international conferences. Her research focuses on understanding the genetic and epigenetic mechanisms underlying human diseases, particularly childhood-onset essential hypertension and cancer.

Dr. Han has received several awards and honors, including the Association for Women in Science (AWIS) National STAR Chapter Awards, the Fellows Award for Research Excellence (FARE) at NIH, and the Outstanding Graduate Student Award in Chinese Academy of Sciences. She is a member of several academic societies, including the International Association for Intelligent Biology and Medicine (IAIBM) and the American Society of Human Genetics (ASHG).

In addition to her research, Dr. Han has been involved in various community services, including mentoring students, reviewing grant applications, and organizing seminars and webinars. She has also taught courses on genomics, bioinformatics, and data science, and has developed and instructed career development workshops.

Editor Research Intrest:

<ul>
	<li>
	Epigenetics and Developmental Biology

<ul>
		<li>Study of epigenetic modifications in brain development and aging, particularly in primate models.</li>
		<li>Impact of environmental factors and stress on epigenetic landscapes during development.</li>
	</ul>
	</li>
	<li>
	Genomic and Precision Health Research

<ul>
		<li>Identification of genetic variants associated with childhood-onset diseases like hypertension and cancer.</li>
		<li>Development of precision medicine strategies integrating genomic data and health disparities research.</li>
	</ul>
	</li>
	<li>
	Bioinformatics and Computational Biology

<ul>
		<li>Advancement of bioinformatics methods for large-scale genomic data analysis, including RNA sequencing.</li>
		<li>Application of machine learning and AI techniques to enhance biological insights.</li>
	</ul>
	</li>
	<li>
	Translational Research

<ul>
		<li>Bridging laboratory research and clinical applications to explore the genetic basis of complex diseases.</li>
		<li>Development of novel therapeutic strategies and biomarkers.</li>
	</ul>
	</li>
	<li>
	Data Science in Genomics

<ul>
		<li>Utilization of cloud computing solutions for genomic data analysis and global collaborations.</li>
		<li>Application of data science to understand genetic diversity and its health implications.</li>
	</ul>
	</li>
	<li>
	Childhood Complex Diseases

<ul>
		<li>Investigation of genetic and environmental contributors to childhood complex diseases, focusing on hypertension and cancer survivorship.</li>
		<li>Researching long-term health impacts of childhood illnesses and the role of ancestry in health disparities.</li>
	</ul>
	</li>
	<li>
	Educational and Mentoring Initiatives

<ul>
		<li>Commitment to mentoring emerging scientists in genomics and bioinformatics.</li>
		<li>Development of educational programs to enhance public understanding of genomics and health.</li>
	</ul>
	</li>
</ul>

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