Publications by authors named "Tyler Biggs"

Background: Quantification of gene expression from RNA-seq data is a prerequisite for transcriptome analysis such as differential gene expression analysis and gene co-expression network construction. Individual RNA-seq experiments are larger and combining multiple experiments from sequence repositories can result in datasets with thousands of samples. Processing hundreds to thousands of RNA-seq data can result in challenges related to data management, access to sufficient computational resources, navigation of high-performance computing (HPC) systems, installation of required software dependencies, and reproducibility.

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Gene co-expression networks (GCNs) provide multiple benefits to molecular research including hypothesis generation and biomarker discovery. Transcriptome profiles serve as input for GCN construction and are derived from increasingly larger studies with samples across multiple experimental conditions, treatments, time points, genotypes, etc. Such experiments with larger numbers of variables confound discovery of true network edges, exclude edges and inhibit discovery of context (or condition) specific network edges.

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Advanced imaging and DNA sequencing technologies now enable the diverse biology community to routinely generate and analyze terabytes of high resolution biological data. The community is rapidly heading toward the petascale in single investigator laboratory settings. As evidence, the single NCBI SRA central DNA sequence repository contains over 45 petabytes of biological data.

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Specifically designed gene expression studies can be used to prioritize candidate genes and identify novel biomarkers affecting resilience against mastitis and other diseases in dairy cattle. The primary goal of this study was to assess whether specific peripheral leukocyte genes expressed differentially in a previous study of dairy cattle with postpartum disease, also would be expressed differentially in peripheral leukocytes from a diverse set of different dairy cattle with moderate to severe clinical mastitis. Four genes were selected for this study due to their differential expression in a previous transcriptomic analysis of circulating leukocytes from dairy cows with and without evidence of early postpartum disease.

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The formation of S-nitrosothiols (SNO) in protein cysteine residues is an important post-translational modification elicited by nitric oxide (NO). This process is involved in virtually every class of cell signaling and has attracted considerable attention in redox biology. On the other hand, their unique structural characters make SNO potentially useful synthons.

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S-Nitrosothiols (RSNOs) have many biological implications but are rarely used in organic synthesis. In this work we report the development of proline-based phosphoramidite substrates that can effectively convert RSNOs to proline-based sulfenamides through a reductive ligation process. A unique property of this method is that the phosphine oxide moiety on the ligation products can be readily removed under acidic conditions.

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S-Nitrosothiols (SNO) and their biological implications as an important post-translational modification are under active investigation. In our work on bioorthogonal reactions of protein SNO we have uncovered chemistry of this functionality that shows synthetic promise. Herein we report a phosphine-mediated reaction between SNO and aldehydes to form thioimines.

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Hydrogen sulfide (H2S) is a newly recognized signaling molecule with very potent cytoprotective actions. The fields of H2S physiology and pharmacology have been rapidly growing in recent years, but a number of fundamental issues must be addressed to advance our understanding of the biology and clinical potential of H2S in the future. Hydrogen sulfide releasing agents (also known as H2S donors) have been widely used in these fields.

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A proline-based phosphine template enabling a rapid Staudinger ligation of azide-containing substrates under mild conditions is reported. This reaction has a second-order rate constant of 1.12 M(-1) s(-1).

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