Protein structure prediction is a challenging task and many different methods have been proposed to address it. More specifically, various computational techniques can be used to provide relations of newly discovered proteins to other proteins with known properties. By determining how amino acid sequences are related to those of known proteins,we can recognize their fold catergory and thus make predictions for their structure and function . HMMs are commonly used in fold recognition and also demontsrate high performance.
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Chromosome analysis is an essential procedure for detecting genetic abnormalities. Traditionally, cells are classified according to their karyotype, which is a tabular array in which the chromosomes are alligned in pairs. Chromosome images are analyzed by experts to obtain vital information about the health of an individual. Normal cells have 22 pairs of chromosomes and 2 sex determinative (XX: women, XY: men). Abnormal cells may have an excess or a deficit of chromosomes and/or structural defects which depict an exchange of genetic material. However, manual examination of these images is a laborious and difficult task requiring skilled lab technicians. Many attempts have been made to automate parts of the chromosome image analysis procedure.
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Microarray technology allows the comprehensive measurement of the expression level of many genes simultaneously on a common substrate. Typical applications of microarrays include the quantification of expression profiles of a system under different experimental conditions, or expression profile comparisons of two systems for one or more conditions. Several types of microarrays have been developed to address different biological processes. cDNA microarrays are used for the monitoring of the gene expression levels to study the effects of certain treatments, diseases, and developmental stages on gene expression. As a result, microarray gene expression profiling can be used to identify disease genes by comparing gene expression in diseased and normal cells. Due to the abundance of experimental data, techniques for automated processing and analysis of microarray images and microarray data are required.
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In peptides and proteins, adjacent amino acids are linked together via a peptide bond. In the majority of the cases the peptide bond is found to be in trans conformation in the majority of the cases. Only a small fraction of peptide bonds in proteins is reported to be in cis conformation. Most of these instances (>90%) occur when the peptide bond is an imide (X-Pro) rather than an amide bond (X-nonPro). Due to the implication of cis/trans isomerization in many biologically significant processes, the accurate prediction of the peptide bond conformation is of high interest.
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