Publications by authors named "Henry Paik"
Article Synopsis
- The study evaluated an algorithmic testing approach in hematopathology to enhance cost-effectiveness in test selection at Brigham and Women's Hospital and Dana-Farber Cancer Institute, especially for expensive molecular assays.
- Researchers developed standard ordering protocols (SOPs) for 17 disease categories, comparing data from six months of beta testing to actual testing practices, along with two years of prospective data from a community site.
- Results showed a massive improvement in test concordance after implementing SOPs, with a decrease in overordered tests and significant potential annual savings of over $1.3 million, indicating that algorithmic testing can streamline procedures without compromising vital information.
Alternative splicing (AS) allows increased diversity and orthogonal regulation of the transcriptional products of mammalian genomes. To assess the distribution and variation of alternative splicing across cell lineages of the immune system, we comprehensively analyzed RNA sequencing and microarray data generated by the Immunological Genome Project Consortium. AS is pervasive: 60% of genes showed frequent AS isoforms in T or B lymphocytes, with 7,599 previously unreported isoforms.
View Article and Find Full Text PDFThe development of targeted therapies for antiestrogen-resistant breast cancer requires a detailed understanding of its molecular characteristics. To further elucidate the molecular events underlying acquired resistance to the antiestrogens tamoxifen and fulvestrant, we established drug-resistant sublines from a single colony of hormone-dependent breast cancer MCF7 cells. These model systems allowed us to examine the cellular and molecular changes induced by antiestrogens in the context of a uniform clonal background.
View Article and Find Full Text PDFMotivation: To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-alpha (ERalpha), we developed an innovative mixture model-based discriminate analysis for identifying ordered TFBS pairs.
Results: Biologically, our proposed new algorithm clearly suggests that TFBSs are not randomly distributed within ERalpha target promoters (P-value < 0.001).
Article Synopsis
- * Using microarray technology and advanced data classification algorithms, researchers identified 220 candidate methylated loci associated with reduced progression-free survival (PFS) in advanced ovarian cancer, with 112 of these being highly predictive of PFS.
- * The findings suggest that these DNA methylation biomarkers could improve the assessment and management of ovarian cancer, demonstrating the effectiveness of innovative classification methods in identifying prognostic indicators.