Get A Practical Approach to Microarray Data Analysis PDF

By Daniel P. Berrar, Werner Dubitzky, Martin Granzow

ISBN-10: 0306478153

ISBN-13: 9780306478154

ISBN-10: 1402072600

ISBN-13: 9781402072604

In the earlier numerous years, DNA microarray expertise has attracted great curiosity in either the clinical group and in undefined. With its skill to concurrently degree the job and interactions of millions of genes, this contemporary know-how offers unheard of new insights into mechanisms of residing structures. at the moment, the first purposes of microarrays contain gene discovery, affliction analysis and diagnosis, drug discovery (pharmacogenomics), and toxicological study (toxicogenomics). regular clinical initiatives addressed via microarray experiments comprise the identity of coexpressed genes, discovery of pattern or gene teams with related expression styles, identity of genes whose expression styles are hugely differentiating with admire to a suite of discerned organic entities (e.g., tumor types), and the examine of gene job styles less than quite a few rigidity stipulations (e.g., chemical treatment). extra lately, the invention, modeling, and simulation of regulatory gene networks, and the mapping of expression info to metabolic pathways and chromosome destinations were further to the record of clinical initiatives which are being tackled via microarray expertise. each one clinical job corresponds to at least one or extra so-called information research projects. types of medical questions require diversified units of information analytical recommendations. mostly, there are sessions of hassle-free info research initiatives, predictive modeling and pattern-detection. Predictive modeling initiatives are all in favour of studying a type or estimation functionality, while pattern-detection tools display the to be had info for attention-grabbing, formerly unknown regularities or relationships.

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Extra resources for A Practical Approach to Microarray Data Analysis

Example text

Therefore, access to databases containing the genomic sequences of organisms is important for designing oligonucleotide arrays. To accomplish this task, appropriate sequence analysis software and retrieval of information from databases with gene and genomic sequence data is mandatory. Using microarrays from an industrial source has some advantages over producing your own. Industry standards ensure high quality of arrays, making the experiments more reliable. However, for unsequenced organisms no sequence is available from existing repositories.

Of course, microarray experiments are often used as high-throughput exploratory tools, and in this case highly focused hypotheses are perhaps not desired, or possible. Furthermore, a number of statistical issues that impact on data analysis creep in at the experimental design stage. The investigator must decide (a) which factors (independent variables) will be varied in the experiment, (b) which factor combinations (experimental conditions) are to be tested, and (c) how many experiment replicas should be done for each tested condition.

These factors include alternative splicing, presence of repetitive sequences that appear in otherwise unrelated genes, and the possibility of highly similar sequences in multiple members of gene families. This implies that the chosen sequences should be unique in the genome. Therefore, access to databases containing the genomic sequences of organisms is important for designing oligonucleotide arrays. To accomplish this task, appropriate sequence analysis software and retrieval of information from databases with gene and genomic sequence data is mandatory.

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A Practical Approach to Microarray Data Analysis by Daniel P. Berrar, Werner Dubitzky, Martin Granzow


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