MOESM1 of Using biological networks to integrate, visualize and analyze genomics data

Additional file 1: Table S1. Case study gene expression data. Description: 514 genes from Lawless et al. [30] that were found to be significantly up-regulated more than threefold in monocytes isolated from milk at either 36 or 48 h post-infection (hpi) with the pathogen Streptococcus uberis that causes mastitis in cattle

Nuclear receptors in Caenorhabditis elegans: NHR-60 regulates embryonic development

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present <i>HiQuant</i>, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. <i>HiQuant</i> also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. <i>HiQuant</i> may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate <i>HiQuant</i>’s performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate <i>HiQuant</i>’s general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download <i>HiQuant</i>, sample data sets, and supporting documentation at http://hiquant.primesdb.eu

Additional file 1: of Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components

Supplementary Information Main Document. (DOCX 110 kb

Additional file 2: of Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components

Supplementary Tables. (XLS 2823 kb

miRNAs significantly differentially expressed in post-treatment high-risk cases [Post-HR] when compared to post-treatment intermediate-risk cases [Post-IR-NBl].

<p>miRNAs significantly differentially expressed in post-treatment high-risk cases [Post-HR] when compared to post-treatment intermediate-risk cases [Post-IR-NBl].</p

Sample Cohort.

<p>Sample Cohort.</p

miRNAs significantly differentially expressed in both pre-treatment high risk group [Pre-HR] compared to pre-treatment intermediate risk group [Pre-IR], and also in the post-treatment high-risk group [Post-HR] compared to the post-treatment intermediate risk group [Post-IR-NBl].

<p>miRNAs significantly differentially expressed in both pre-treatment high risk group [Pre-HR] compared to pre-treatment intermediate risk group [Pre-IR], and also in the post-treatment high-risk group [Post-HR] compared to the post-treatment intermediate risk group [Post-IR-NBl].</p

miRNAs significantly up-regulated within the blastemal component of post-treatment high risk cases [Post-HR] when compared to post-treatment intermediate risk cases [Post-IR-Bl].

<p>miRNAs significantly up-regulated within the blastemal component of post-treatment high risk cases [Post-HR] when compared to post-treatment intermediate risk cases [Post-IR-Bl].</p