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Prof. Matthew He 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. |
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Prof. Sun Kim, Indiana University, Bloomington, IN, USA 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. |
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Prof. Kiyoko F. Aoki-Kinoshita 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. |
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