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Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

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Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.

Protein expression refers to the techniques in which a protein of interest is synthesized, modified or regulated in cells. The blueprints for proteins are stored in DNA which is then transcribed to produce messenger RNA (mRNA). mRNA is then translated into protein. In prokaryotes, this process of mRNA translation occurs simultaneously with mRNA transcription. In eukaryotes, these two processes occur at separate times and in separate cellular regions (transcription in nucleus and translation in the cytoplasm). Recombinant protein expression utilizes cellular machinery to generate proteins, instead of chemical synthesis of proteins as it is very complex. Proteins produced from such DNA templates are called recombinant proteins and DNA templates are simple to construct. Recombinant protein expression involves transfecting cells with a DNA vector that contains the template. The cultured cells can then transcribe and translate the desired protein. The cells can be lysed to extract the expressed protein for subsequent purification. Both prokaryotic and eukaryotic protein expression systems are widely used. The selection of the system depends on the type of protein, the requirements for functional activity and the desired yield. These expression systems include mammalian, insect, yeast, bacterial, algal and cell-free. Each of these has pros and cons. Mammalian expression systems can be used for transient or stable expression, with ultra high-yield protein expression. However, high yields are only possible in suspension cultures and more demanding culture conditions. Insect cultures are the same as mammalian, except that they can be used as both static and suspension cultures. These cultures also have demanding culture conditions and may also be time-consuming. Yeast cultures can produce eukaryotic proteins and are scalable, with minimum culture requirements. Yeast cultures may require growth culture optimization. Bacterial cultures are simple, scalable and low cost, but these may require protein-specific optimization and are not suitable for all mammalian proteins. Algal cultures are optimized for robust selection and expression, but these are less developed than other host platforms. Cell-free systems are open, free of any unnatural compounds, fast and simple. This system is, however, not optimal for scaling up.