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An understanding of the roles and interactions of proteins withincells is vital to our understanding of biology. Proteomics hascome a long way, and covers many areas now, since the inventionof 2 dimensional gel electrophoresis in the 1970s, or the coiningof the term proteomics in the 1990s. As more people move intothis important area, there is a need for guides to aid thesemoves. Proteomics for Biological Discovery aims to serve assuch a guide. The format of this multi-author book is well laidout, with fifteen chapters in three main parts: I. Foundationsof Proteomics; II. Functional Proteomics; and III. Novel Approachesin Proteomics. The editors have selected a strong team of respectedexperts in the various proteomics niches to write the fifteenconstituent chapters. The chapters are, for the most part, self-contained,and there is no  相似文献   

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Gastric cancer (GC) has a high rate of morbidity and mortality among various cancers worldwide. The development of noninvasive diagnostic methods or technologies for tracking the occurrence of GC is urgent, and searching reliable biomarkers is considered.This study intended to directly discover differential biomarkers from GC tissues by two-dimension-differential gel electrophoresis (2D-DIGE), and further validate protein expression by western blotting (WB) and immunohistochemistry (IHC).Pairs of GC tissues (gastric cancer tissues and the adjacent normal tissues) obtained from surgery was investigated for 2D-DIEG.Five proteins wereconfirmed by WB and IHC, including glucose-regulated protein 78 (GRP78), glutathione s-transferase pi (GSTpi), apolipoprotein AI (ApoAI), alpha-1 antitrypsin (A1AT) and gastrokine-1 (GKN-1). Among the results, GRP78, GSTpi and A1ATwere significantlyup-regulated and down-regulated respectively in gastric cancer patients. Moreover, GRP78 and ApoAI were correlated with A1AT for protein expressions.This study presumes these proteins could be candidates of reliable biomarkers for gastric cancer.  相似文献   

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Bioinformatics has blossomed in the past decades with the introductionof biological experiments that rapidly produce massive amountsof data (such as the multiple genome projects, the large-scaleanalysis of gene expression, the large-scale analysis of protein–proteininteractions and the large-scale analysis of genome-wide genotype-phenotypeassociations). The resulting bioinformatics tools mainly liein two groups. They may be databases  相似文献   

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A volume in the ‘Cambridge Series in Statistical and ProbabilisticMathematics’, ‘Data Analysis and Graphics UsingR’ is presented as a gentle tour guide for new R users,aiming to help them navigate through many powerful tools thatthe open source R system offers. As the authors point out inthe Preface, the book is ‘aimed at scientists who wishto do statistical analysis on their own’. Every efforthas been made to ensure the book is useful for practical dataanalysis. This book is particularly useful for researchers inthe life science realm who  相似文献   

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