ChIP Human

Cell cycle can be challenging due to difference introduced by sample handling, timing, and difference within the sample. Downstream instriuments to analyse cell cycle (Multicolor flow cytometry and multicolor imaging) can answer these challenges. Relevant markers can be combined with cell phenotyping markers to look at events within subpopulations of cells.

Cell cycle can be challenging due to difference introduced by sample handling, timing, and difference within the sample. Downstream instriuments to analyse cell cycle (Multicolor flow cytometry and multicolor imaging) can answer these challenges. Relevant markers can be combined with cell phenotyping markers to look at events within subpopulations of cells.

The RNA-guided CRISPR-Cas9 nuclease system has revolutionized the genome editing practices. For the most part, the Cas9-mediated genome editing is performed either via nonhomologous end joining (NHEJ) or homology-directed repair (HDR) in mammalian cells, However, designing of specific sgRNAs and minimizing off-target cleavage mediated mutagenesis are the major challenges in CRISPR-Cas based genome editing. To circumvent these issues, we can take advantages of many available tools and approaches for sgRNA construction and delivery.

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.

DNA 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.

DNA 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.

DNA 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.

DNA 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.

DNA 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.

DNA 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.