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Titlebook: Gene Function Analysis; Michael F. Ochs Book 2007 Humana Press 2007 DNA.Mutant.Promoter.Proteomics.Stefan Dübel.bioinformatics.gene expres

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發(fā)表于 2025-3-21 19:04:04 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Gene Function Analysis
編輯Michael F. Ochs
視頻videohttp://file.papertrans.cn/382/381930/381930.mp4
概述Brings together a number of techniques, both computational and biological, that have developed recently for looking at gene function.Contains Notes sections with troubleshooting guides.Easy-to-follow
叢書名稱Methods in Molecular Biology
圖書封面Titlebook: Gene Function Analysis;  Michael F. Ochs Book 2007 Humana Press 2007 DNA.Mutant.Promoter.Proteomics.Stefan Dübel.bioinformatics.gene expres
描述This volume of Methods in Molecular Biology focuses on techniques to determine the function of a gene. Traditionally, the function of a gene was determined following cloning, which provided its DNA sequence and an ab- ity to modify this sequence. Experiments were performed that looked for p- notypic changes in a cell line or model organism following modifications to the sequence, knocking out of the gene, or enhancing expression of the gene. In the 1990’s, the growing sequence databases and the BLAST algorithm provided additional power by allowing identification of genes with known function that had similar sequences and potentially similar molecular mechanisms. On the experimental side, methods, such as two-hybrid screening that could directly determine the partners of specific proteins and even the domains of interaction, came into widespread use. With the advent of high-throughput technologies following completion of the human genome project and similar projects in model organisms, the n- ber of genes of interest has expanded and the traditional methods for gene fu- tion analysis cannot achieve the throughput necessary for large-scale exploration. Although computational tools su
出版日期Book 2007
關(guān)鍵詞DNA; Mutant; Promoter; Proteomics; Stefan Dübel; bioinformatics; gene expression; genes; genome; molecular bi
版次1
doihttps://doi.org/10.1007/978-1-59745-547-3
isbn_softcover978-1-61737-748-8
isbn_ebook978-1-59745-547-3Series ISSN 1064-3745 Series E-ISSN 1940-6029
issn_series 1064-3745
copyrightHumana Press 2007
The information of publication is updating

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Association Analysis for Large-Scale Gene Set Dataefore, computer-assisted analysis is necessary for the biological interpretation of the gene sets, and for creating working hypotheses, which can be tested experimentally. One obvious way to analyze gene set data is to associate the genes with a particular biological feature, for example, a given pa
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Prediction of Intrinsic Disorder and Its Use in Functional Proteomicsation of a given protein, looking for several key features. However, ID proteins with their dynamic structures that interconvert on a number of time-scales are difficult targets for the majority of traditional biophysical and biochemical techniques. Structural and functional analyses of these protei
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Estimating Protein Function Using Protein-Protein Relationshipsins. In such a scenario, the context of the proteins’ functional associations can be used for annotation; overrepresented functional linkages with a certain class of proteins or members of a pathway allow putative function assignments based on the “guilt-by-association” principle. Two computational
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Mining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified Medical Language System (UMLS) in the Unified Medical Language System using MetaMap Transfer (MMTx). MMTx can be used in applications including mining and inferring relationship between concepts in MEDLINE publications by transforming free text into computable concepts. MMTx is in general not designed to be an end-user program;
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Statistical Methods for Identifying Differentially Expressed Gene Combinations expression regulatory networks. Statistically, the identification of these changes can be viewed as a search for groups (most typically pairs) of genes whose expression provides better phenotype discrimination when considered jointly than when considered individually. Such groups are defined as bei
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