Introduces BioMEMS, covering applications like DNA separation, protein analysis, and neuroelectronic implants, along with key numbers in biology and challenges in system integration.
Explores quantile normalization in genomics, emphasizing data preparation, loading, filtering, and the significance of accurate gene expression analysis.
Covers the heterogeneous neuroscience data, techniques like microarrays and gene sequencing, data integration, and the importance of metadata in organizing and sharing data.
Explores the synthesis and applications of polymer brushes, including controlled polymerization techniques and their use in protein microarrays and cell adhesion.
Explores the maternal-to-zygotic transition in early embryonic development, focusing on key processes like zygotic genome activation and cell cycle regulation.
Explores robust regression in genomic data analysis, focusing on downweighting large residuals for improved estimation accuracy and quality assessment metrics like NUSE and RLE.
