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.

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 laboratory methods and protocols

Klappentext

With the advent of high-throughput technologies, the number of genes of interest has expanded and the traditional methods for gene function analysis cannot achieve the throughput necessary for large-scale exploration. In Gene Function Analysis , a select team of experts bring together a number of recently developed techniques for studying gene function. The volume begins with a variety of computational techniques, which provide an excellent point of departure for the cutting-edge experimental methods that follow. Written in the highly successful Methods in Molecular Biology™ series format, each chapter surveys its subject with readily reproducible laboratory protocols, a list of the necessary materials, and the popular Notes section, which contains tips for troubleshooting and avoiding known pitfalls.

Comprehensive and timely, Gene Function Analysis offers researchers a clear guide and the important tools they need to further study the intricate human genome.

Inhalt
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.