Browsing by Author "Le, Huong"

Now showing 1 - 3 of 3
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    Reconstruction of sweep MRI signals
    (University of Minnesota. Institute for Mathematics and Its Applications, 2014-08) Emerson, Tegan; Sun, Yu; Alvarez, Robert; Esteki, Fataneh; Le, Huong; Moeller, Steen
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    Regions of High Confidence in Chinese Hamster and CHO-K1 Genome Assemblies
    (2016-04-20) Vishwanathan, Nandita; Bandyopadhyay, Arpan; Fu, Hsu-Yuan; Sharma, Mohit; Johnson, Kathryn; Mudge, Joann; Ramaraj, Thiruvarangan; Onsongo, Getiria; Silverstein, Kevin A. T.; Jacob, Nitya M.; Le, Huong; Karypis, George; Hu, Wei-Shou; wshu@umn.edu; Hu, Wei-Shou
    Chinese hamster Ovary (CHO) cell lines are the dominant industrial workhorses for therapeutic recombinant protein production. The availability of the genome sequence of Chinese hamster and CHO cells will spur further genome and RNA sequencing of producing cell lines. However, the mammalian genomes assembled using shot-gun sequencing data still contain regions of uncertain quality due to assembly errors. Identifying high confidence regions in the assembled genome will facilitate its use for cell engineering and genome engineering. This dataset includes two genome annotation files that identify the 'high confidence regions' shared by the genome assemblies in comparison. The potential use of these files are to find locations in the publically available genome which are likely to be assembled correctly. These regions can be used confidently for genome engineering.
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    Transcriptome Meta Data Compilation for Chinese hamster tissues and CHO cell lines
    (2016-06-06) Vishwanathan, Nandita; Yongky, Andrew; Johnson, Kathryn C; Fu, Hsu-Yuan; Jacob, Nithya M; Le, Huong; Bandyopadhyay, Arpan; wshu@umn.edu; Hu, Wei-Shou; University of Minnesota Department of Chemical Engineering and Material Sciences, Hu Group
    Transcriptomics is increasingly being used on Chinese hamster ovary (CHO) cells to unveil physiological insights related to their performance during production processes. The rich transcriptome data can be exploited to provide impetus for systems investigation such as modeling the central carbon metabolism or glycosylation pathways, or even building genome-scale models. To harness the power of transcriptome assays, we assembled and annotated a set of RNA-Seq data from multiple CHO cell lines and Chinese hamster tissues, and constructed a DNA microarray. These tools were used to measure the transcript expression of tissues (liver, brain, ovary), 3 parental cell lines (DG44, DXB11, CHO-K1) and 16 recombinant cell lines. Transcript expression levels for tissues and cell lines have been compiled as an excel spreadsheet to allow for a rapid survey of transcript levels of different genes.