Indiana University-Purdue University Indianapolis (IUPUI) / Drug-Drug Interaction (DDI) is one of the major causes of adverse drug reaction (ADR) and has been demonstrated to threat public health. It causes an estimated 195,000 hospitalizations and 74,000 emergency room visits each year in the USA alone. Current DDI research aims to investigate different scopes of drug interactions: molecular level of pharmacogenetics interaction (PG), pharmacokinetics interaction (PK), and clinical pharmacodynamics consequences (PD). All three types of experiments are important, but they are playing different roles for DDI research. As diverse disciplines and varied studies are involved, interaction evidence is often not available cross all three types of evidence, which create knowledge gaps and these gaps hinder both DDI and pharmacogenetics research. In this dissertation, we proposed to distinguish the three types of DDI evidence (in vitro PK, in vivo PK, and clinical PD studies) and identify all knowledge gaps in experimental evidence for them. This is a collective intelligence effort, whereby a text mining tool will be developed for the large-scale mining and analysis of drug-interaction information such that it can be applied to retrieve, categorize, and extract the information of DDI from published literature available on PubMed. To this end, three tasks will be done in this research work: First, the needed lexica, ontology, and corpora for distinguishing three different types of studies were prepared. Despite the lexica prepared in this work, a comprehensive dictionary for drug metabolites or reaction, which is critical to in vitro PK study, is still lacking in pubic databases. Thus, second, a name entity recognition tool will be proposed to identify drug metabolites and reaction in free text. Third, text mining tools for retrieving DDI articles and extracting DDI evidence are developed. In this work, the knowledge gaps cross all three types of DDI evidence can be identified and the gaps between knowledge of molecular mechanisms underlying DDI and their clinical consequences can be closed with the result of DDI prediction using the retrieved drug gene interaction information such that we can exemplify how the tools and methods can advance DDI pharmacogenetics research. / 2 years

This research investigated issues related to normalizing punctuation marks from a text retrieval perspective. A punctuated-centric approach was undertaken by exploring changes in meanings, whitespaces, words retrievability, and other issues related to normalizing punctuation marks. To investigate punctuation normalization issues, various frequency counts of punctuation marks and punctuation patterns were conducted using the text drawn from the Gutenberg Project archive and the Usenet Newsgroup archive. A number of useful punctuation mark types that could aid in analyzing punctuation marks were discovered. This study identified two types of punctuation normalization procedures: (1) lexical independent (LI) punctuation normalization and (2) lexical oriented (LO) punctuation normalization. Using these two types of punctuation normalization procedures, this study discovered various effects of punctuation normalization in terms of different search query types. By analyzing the punctuation normalization problem in this manner, a wide range of issues were discovered such as: the need to define different types of searching, to disambiguate the role of punctuation marks, to normalize whitespaces, and indexing of punctuated terms. This study concluded that to achieve the most positive effect in a text retrieval environment, normalizing punctuation marks should be based on an extensive systematic analysis of punctuation marks and punctuation patterns and their related factors. The results of this study indicate that there were many challenges due to complexity of language. Further, this study recommends avoiding a simplistic approach to punctuation normalization.

My work contains five videos. Installation presents videos on five separate tv screens. Each video duration is max 3 min. Videos are based on text. Text exists as installation in space and continues in form of performance. Content of text is simple wisdom which is twist off into nonsense. Realisation contains element of ephemerality. Former work is destroed by nature or human incidence.

Hedgehog runs across the sidewalk is a collection of texts about the everyday beauty of the world, about slowness and concentration. These are stories seen, perceived, heard by me. Stories where I stopped or they stopped me. About how the sun and the plant create a shadow, how storks fly in a circle over us, how a badger runs in the dark, how a pine cone falls from a tree, how cats sit in the dark, how they caress a plant over leaves, how a night butterfly sits in the corner of the room the dog watches something in the grass, as a rainbow spot lies on the road, as they find that it rains the least of the trees under the pine tree around, as a cloud of steam hovers over the forest, as tamarinds close their leaves at night, ... I write these texts and transfer them to handmade paper, which I made from collected papers and plants. I pin them story after story with a pin. They then meet together on a round table, where people can meet them and experience them with their eyes and touch.

付記する学位プログラム名: グローバル生存学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21735号 / 工博第4552号 / 新制||工||1710(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 堀 智晴, 教授 寶 馨, 准教授 佐山 敬洋, 教授 立川 康人 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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