{ "item_title" : "Comprehensive Reanalysis of Genomic Storm (Transcriptomic) Data, Integrating Clinical Varibles and Utilizing New and Old Approaches", "item_author" : [" Deepak Tanwar "], "item_description" : "Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 165/200 (A+), language: English, abstract: Aim: I sought to determine trauma-specific transcriptomic signatures for septic sub-cohorts. Methods: In retrospective large-scale data analysis, I applied (old and new methods), including lagged correlation between transcripts and clinical subtype counts (by integrating over 800 samples from trauma patients). Results: Focussing on novel pathways and correlation methods we revealed (persistently down-regulated) ribosomal genes and changed time profiles of metabolic enzyme precursors /transcripts. Candidates associated to insulin signalling, including HK3, hinted towards metabolic syndrome. Correlation analysis yielded robust results for LCN2 and LTF (r>0.9), but only moderate associations to subtype counts (e.g. top-performing r (Eosinophil, IL5RA)>0.6). Discussion: Gene Centred Normalisation Reduces Ambiguity and Improves Interpretation.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/65/685/845/3656858454_b.jpg", "price_data" : { "retail_price" : "39.50", "online_price" : "39.50", "our_price" : "39.50", "club_price" : "39.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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