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Tutorials |
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Tutorial 1
Prof. Matthew He
Nova Southeastern University, Florida, USA
Title: Mathematics of Bioinformatics - Theory, Practice, and Applications
Abstract: Modern science connects many basic secrets of living matter with
the genetic codes. Biological organisms belong to a category of very
complex natural systems, which correspond to a huge number of biological
species with inherited properties. But surprisingly, molecular genetics
has discovered that all organisms are identical to each other by their
basic molecular-genetic structures. Due to this revolutionary discovery, a
great unification of all biological organisms has happened in science. The
informationgenetic line of investigations has become one of the most
prospective lines not only in biology, but also in science as a whole.
Recent progress in the determination of genomic sequences has yielded many
millions of gene sequences. But what do these sequences tell us and what
are the generalities and rules that are governed by them ? It seems that
we understand very little about genetic contexts required to read them.
Historically, mathematics, probability and statistics have been widely
used in biological sciences. Science has a challenge to understand a
system organization of molecular genetic ensemble with its unique
properties of reliability and productivity. Disclosing of key secrets of
this organization means a big step in science about nature in a whole and
a big step to create the most productive biotechnologies. Knowledge about
this structural organization should become a part of mathematical natural
science. Recent advances of mathematical methods and techniques in
bioinformatics have been rapidly growing. There is more to life than the
genomic blueprint of each organism. Life functions within the natural laws
that we know and the ones we do not know. Mathematics can be used to
understand life from the molecular to the biosphere level. This tutorial
is devoted to the connection and integration between fundamental mathematical methods and biological
sequences, DNA and protein structures, biological networks, systems
biology, algebraic biology, and cognitive informatics. The materials of
the tutorials are selected from an upcoming book Mathematics of
Bioinformatics by Matthew He and Sergey Petoukhov.
slides - Part 1, Part 2
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Tutorial 2
Prof. Sun Kim, Indiana University, Bloomington, IN, USA
Prof. Michael Chan, National Chung Cheng University, Taiwan
Prof. Alfred Cheng, The Chinese University of Hong Kong, Hong Kong
Prof. Kun Huang, Ohio State University
Title: Epigenomics and Cancer
Abstract: Epigenetics is the study of heritable changes in gene functions without a change in DNA sequence and epigenomics is a study of genome-wide epigenetic
change. Epigenomics involves DNA methylation, histone modification, and microRNA interference and it has a direct impact on the activation of genes. In developmental
biology, it is widely known that epigenomics is an important biological mechanism for the tissue-specific cell development and differentiation. Aberrant epigenomic
changes in cancer cells are also widely known. This important epigenetic information has become available at the global level only recently due to the rapid advances
in instrumentations, biotechnologies, and computational techniques, notably due to the general availability of the next generation sequencing technology to most
cancer researchers. The first half of this 4-hour tutorial starts with overview on the epigenomics, DNA methylation, histone modifications, and microRNA interference.
Then we will summarize computational techniques to process and analyze data from the high throughput instruments including the ultra-deep sequencing platforms. The
second half of the tutorial will summarize recent literature on computational analysis techniques for epigenomics data for cancer research. This includes aberrant DNA
methylation patterns (global hypomethyation and region specific hyermethylation), histone markers and nucleosome positioning in cancer cells, and microRNA
interference. In addition, we will also discuss how we can integrate such diverse data types for cancer research, including the integrated analysis of microRNA and
mRNA expression data.
slides - Part 1, Part 2, Part 3, Part 4
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Tutorial 3
Prof. Kiyoko F. Aoki-Kinoshita
Soka University, Japan
Title: Bioinformatics Approaches in Glycomics Research: An Introduction
Abstract: Carbohydrates are the third class of information-encoding
biological macromolecules. The term glycomics, the scientific attempt of
characterizing and studying carbohydrates, is a rapidly emerging branch of
science, for which informatics is just beginning. Glycomics requires
sophisticated algorithmic approaches. The status of structural encoding,
standardization, databases and applications will be presented.
handout, slides
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