By Darius M. Dziuda
Information Mining for Genomics and Proteomics makes use of pragmatic examples and a whole case examine to illustrate step by step how biomedical reports can be utilized to maximise the opportunity of extracting new and worthy biomedical wisdom from info. it's a very good source for college kids and pros concerned with gene or protein expression info in various settings.
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Additional info for Data mining for genomics and proteomics: Analysis of gene and protein expression data
The mRNA travels from the nucleus to the cytoplasm where, in ribosomes, it is translated into a protein. ) Since the concept of a gene has been changed over and over again, we may consider one of two options: (i) stop using this concept at all, or (ii) formulate a gene deﬁnition in a way that is either quite general (and perhaps vague) or deliberately verbose in an attempt to cover all possibilities. ” (Gerstein et al. 4: A human protein-coding gene: an example of alternative splicing. During alternative splicing of the primary RNA transcript, different subsets of exons are joined to create two (or more) different mRNA isoforms.
1. The raw data resulting from each microarray image analysis (such as CEL ﬁles for Affymetrix arrays). 2. The ﬁnal data after preprocessing, for instance the results of MAS5 or RMA preprocessing. This should be the gene expression matrix that is analyzed in the study. 3. The essential information about sample annotation and experimental factors. All information necessary for proper interpretation of the experimental results and for eventual replication of the experiment. 4. The experimental design including relationships between samples, microarrays, and data ﬁles.
For example, transcriptomics is most often deﬁned18 as the area covering analysis of gene expression data (expressed genes are called transcripts). One could then say that the focus of this book is transcriptomics. Nevertheless, we will use the widely recognized term genomics, which has been used for this kind of investigations since the beginning of high-throughput gene expression data analysis. 5 Data Mining We deﬁne data mining as efﬁcient ways of extracting new information or new knowledge from large data sets or databases.
Data mining for genomics and proteomics: Analysis of gene and protein expression data by Darius M. Dziuda