Ochs | Gene Function Analysis | Buch | 978-1-58829-734-1 | sack.de

Buch, Englisch, Band 408, 337 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 705 g

Reihe: Methods in Molecular Biology

Ochs

Gene Function Analysis


2007
ISBN: 978-1-58829-734-1
Verlag: Humana Press

Buch, Englisch, Band 408, 337 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 705 g

Reihe: Methods in Molecular Biology

ISBN: 978-1-58829-734-1
Verlag: Humana Press


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 such as BLAST remain a good point of departure, it is often the case that a gene that appears interesting in a hi- throughput experiment shows no obvious similarity to a gene of known fu- tion. In addition, when BLAST does find a similar gene, the process has often only begun.
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Computational Methods I.- Gene Function Inference From Gene Expression of Deletion Mutants.- Association Analysis for Large-Scale Gene Set Data.- Estimating Gene Function With Least Squares Nonnegative Matrix Factorization.- From Promoter Analysis to Transcriptional Regulatory Network Prediction Using PAINT.- Prediction of Intrinsic Disorder and Its Use in Functional Proteomics.- Computational Methods II.- Sybil: Methods and Software for Multiple Genome Comparison and Visualization.- Estimating Protein Function Using Protein-Protein Relationships.- Bioinformatics Tools for Modeling Transcription Factor Target Genes and Epigenetic Changes.- Mining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified Medical Language System (UMLS).- Statistical Methods for Identifying Differentially Expressed Gene Combinations.- Experimental Methods.- Gene Function Analysis Using the Chicken B-Cell Line DT40.- Design and Application of a shRNA-Based Gene Replacement Retrovirus.- Construction of Simple and Efficient DNA Vector-Based Short Hairpin RNA Expression Systems for Specific Gene Silencing in Mammalian Cells.- Selection of Recombinant Antibodies From Antibody Gene Libraries.- A Bacterial/Yeast Merged Two-Hybrid System.- A Bacterial/Yeast Merged Two-Hybrid System.- Engineering Cys2His2 Zinc Finger Domains Using a Bacterial Cell-Based Two-Hybrid Selection System.



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