Introduction to Statistical Methods for Gene Mapping | KyotoUx on edX | Course About Video

Introduction to Statistical Methods for Gene Mapping | KyotoUx on edX | Course About Video


RYO YAMADA: Hello, everyone. I’m Ryo Yamada, professor
of statistical genetics. Welcome to our lecture
course, Introduction to Statistical Methods for Gene Mapping,
provided by [INAUDIBLE] Statistical Genetics, Center for Genetic
Medicine, Graduate School of Medicine, Kyoto University. Statistical genetics is a study field
to apply statistics and mathematics to understand the hetereogeneity in
[INAUDIBLE] phenomena in general. The heterogeneity is one of the
fundamental features in biology. As we can see, the variation
among various species, and also we can see the heterogeneity
in individuals of human beings. We can see variations in
appearance, but variation is also present in non-visible
functions, and all these features are called phenotypes. These phenotypic variations are
rooted through various patterns of protein expression. And proteins variation is based on
the variation in RNA expression, and RNA’s variations are linked
to DNA sequence variation. These days, various [INAUDIBLE]
experimental technologies enables us to evaluate all of these
variations in multiple layers– DNA layer, RNA layer, and
protein layer all together. We call this kind of approach to
handle the whole set for each layer as genome, transcriptome, and proteome. When we try to understand these complex
heterogeneities, these large amounts of data sets, or big data,
statistical genetics is a must. Because statistical genetics
provides various methods to struggle with these data sets. We hope many students find our
introductory lecture interesting, and get motivated to study further
topics in statistical genetics to understand better about heterogeneity
from a statistical standpoint.

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