TMHMM2. 0 both use hid den Markov models based on different training sets to predict membrane topology. SOSUI evaluates proteins for their hydrophobic and amphiphilic properties to make its predictions. concerning The use of all three programs should improve prediction accuracy. We first ran Phobius, which can predict both transmembrane helices and signal peptides. Signal peptide Inhibitors,Modulators,Libraries sequences are similar to transmembrane segments owing to their hydrophobic nature. To avoid false positive predictions, we excluded signal pep tides before running TMHMM2. 0 and SOSUI. There are many different types of cells in the human body, and similar cells group together to form a tissue with a specialized function. Multiple tissues constitute an organ such as brain, heart or liver.

Gene expression variation is the primary determinant of tissue identity and function. Certain genes are expressed specifically or Inhibitors,Modulators,Libraries preferentially in a particular tissue. These genes are broadly called tissue selective genes. Note that tissue specificity is regarded as a special case of tissue selectiv ity, and tissue specific genes are expressed only in a par ticular tissue. It is a fundamental question in biology to understand how selective gene expression underlies tissue development and function. Moreover, tissue selec tive genes are implicated in many complex human dis eases, and identification of these genes may provide valuable information for developing novel biomarkers and drug targets. Tissue selective expression was traditionally studied at the single gene level with time consuming techniques such as Northern blot and in situ hybridization.

With the recent development of high throughput technolo gies, biologists can perform genome wide gene expres sion profiling in various tissues. These high throughput technologies include Expressed Sequence Tag sequencing, Serial Analysis of Gene Expression, and DNA microarrays. Yu et al. analyzed the NCBI EST Inhibitors,Modulators,Libraries database to select a set of human genes that are preferentially expressed in a tissue of interest. The selection was based on the expression enrichment score, which was defined as the ratio between observed and expected number of ESTs for a gene. For the selected tissue selective genes, regulatory modules were detected by examining the promoter motifs and their relationships Inhibitors,Modulators,Libraries with transcription factors.

However, EST data are generated mainly for transcript sequence infor mation, and EST counts can only be used as rough esti mates of gene expression levels. Siu et al. investigated gene expression patterns in different regions of the human brain by using SAGE, and identified Brefeldin_A some brain region selective selleck genes. Kouadjo et al. also used the SAGE strategy to identify housekeeping and tissue selective genes in fifteen mouse tissues. While SAGE tag counts can provide reliable estimation of gene expres sion, it is rather inefficient and expensive to use SAGE for profiling a large number of tissue samples with bio logical replicates. The DNA microarray techno