This book describes novel computational techniques that are used in predicting gene interactions using two main online resources: biomedical literature and sequence data. The co-occurrence method of text mining was extensively explored in this book. The effects of certain parameters on influencing the relevancy of documents in which two genes co-occur were critically examined. The results showed that indeed some parameters, if taken into consideration, can lead to better identification of documents that describe gene interactions. A system was developed as part of the work and can be obtained by contacting the author: [email protected]. The book also describes a novel approach that used an analysis of SAGE and EST sequence libraries using ecological estimation methods. The approach proves that species accumulation theory used in ecology can be applied to tag libraries to predict an upper bound to the number of mRNA transcript species in a tissue. The novel computational analysis provided in this book can be used to extend the body of knowledge and insights relating to gene interactions and, hence, provide better understanding of genes and their functions within gene networks.

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