Gene Function Analysis

1. Front Matter

   Pages i-xiv

   PDF

2. Computational Methods I

   1. Front Matter

      Pages n1-n1

      PDF

   2. Gene Function Inference From Gene Expression of Deletion Mutants

      • Ghislain Bidaut

      Pages 1-18

   3. Association Analysis for Large-Scale Gene Set Data

      • Stefan A. Kirov, Bing Zhang, Jay R. Snoddy

      Pages 19-33

   4. Estimating Gene Function With Least Squares Nonnegative Matrix Factorization

      • Guoli Wang, Michael F. Ochs

      Pages 35-47

   5. From Promoter Analysis to Transcriptional Regulatory Network Prediction Using PAINT

      • Gregory E. Gonye, Praveen Chakravarthula, James S. Schwaber, Rajanikanth Vadigepalli

      Pages 49-68

   6. Prediction of Intrinsic Disorder and Its Use in Functional Proteomics

      • Vladimir N. Uversky, Predrag Radivojac, Lilia M. Iakoucheva, Zoran Obradovic, A. Keith Dunker

      Pages 69-92

3. Computational Methods II

   1. Front Matter

      Pages n2-n2

      PDF

   2. Sybil: Methods and Software for Multiple Genome Comparison and Visualization

      • Jonathan Crabtree, Samuel V. Angiuoli, Jennifer R. Wortman, Owen R. White

      Pages 93-108

   3. Estimating Protein Function Using Protein-Protein Relationships

      • Shailesh V. Date

      Pages 109-127

   4. Bioinformatics Tools for Modeling Transcription Factor Target Genes and Epigenetic Changes

      • Ramana V. Davuluri

      Pages 129-151

   5. Mining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified Medical Language System (UMLS)

      • John D. Osborne, Simon Lin, Lihua Julie Zhu, Warren A. Kibbe

      Pages 153-169

   6. Statistical Methods for Identifying Differentially Expressed Gene Combinations

      • Yen-Yi Ho, Leslie Cope, Marcel Dettling, Giovanni Parmigiani

      Pages 171-191

4. Experimental Methods

   1. Front Matter

      Pages 192-192

      PDF

   2. Gene Function Analysis Using the Chicken B-Cell Line DT40

      • Randolph B Caldwell, Petra Fiedler, Ulrike Schoetz, Jean-Marie Buerstedde

      Pages 193-210

   3. Design and Application of a shRNA-Based Gene Replacement Retrovirus

      • Rugang Zhang, Peter D. Adams, Xiaofen Ye

      Pages 211-221

   4. Construction of Simple and Efficient DNA Vector-Based Short Hairpin RNA Expression Systems for Specific Gene Silencing in Mammalian Cells

      • Tsung-Lin Cheng, Wen-Tsan Chang

      Pages 223-241

   5. Selection of Recombinant Antibodies From Antibody Gene Libraries

      • Michael Hust, Stefan Dübel, Thomas Schirrmann

      Pages 243-255

   6. A Bacterial/Yeast Merged Two-Hybrid System

      • Nadezhda Y. Tikhmyanova, Eugene A. Izumchenko, Ilya G. Serebriiskii, Erica A. Golemis

      Pages 257-290

   7. A Bacterial/Yeast Merged Two-Hybrid System

      • Ilya G. Serebriiskii, Nadia Milech, Erica A. Golemis

      Pages 291-315

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.

• DNA
• Mutant
• Promoter
• Proteomics
• Stefan Dübel
• bioinformatics
• gene expression
• genes
• genome
• molecular biology
• transcription

From the reviews:

"‘Gene Function Analysis’ is volume 408 of the ‘Methods in Molecular Biology’ series. The aim of the book is to provide both in silico and laboratory methods for the functional analysis of the large amount of gene expression data generated from high throughput technologies such as microarrays. … This book would certainly be a useful addition to a laboratory interested in assessing gene function through both bioinformatic and ‘wet’ approaches. Definitely one for the more (toxico)genomically challenged amongst us." (James Sidaway, British Toxicology Society Newsletter, Summer, 2008)

• The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore

  Michael F. Ochs

Policies and ethics