Through alternative processing of pre-mRNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes based on deep sequencing

types of therapeutically induced tumour regression. It is implicated in both physiological involution and atrophy of various tissues and organs. It can also be triggered by noxious agents, both in the embryo and adult animal. IN recent years it has become widely recognized that spontaneous loss of cells

of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells

of accuracy. Here we investigate the stability of the probe-sensitivity index across different tissue types, the reproducibility of results in replicate experiments, and the use of MBEI in perfect match (PM)-only arrays. Results: Probe-sensitivity indexes are stable across tissue types. The target gene

plasminogen activator. Platelet and vascular function during coronary thrombolysis with tissue-type

be developed to sort out whether cancer tissues have distinctive signatures of gene expression over normal tissues or other types of cancer tissues. In this paper, we address the problem of selection of a small subset of genes from broad patterns of gene expression data, recorded on DNA micro-arrays. Using

We have developed a procedure for preparing extracts from nuclei of human tissue culture cells that directs accurate transcription initiation in vitro from class II promoters. Conditions of extraction and assay have been optimized for maximum activity using the major late promoter of adenovirus 2

, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.

Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However

normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP