BIOINFORMATICS & COMPUTATIONAL MEDICINE

Bioinformatics uses computation to extract knowledge from biological data. In practice, bioinformatics involves the collection, storage, retrieval, manipulation, and modelling of biological data through software algorithms for the purposes of visualization, analysis, and prediction. Computational medicine uses bioinformatic tools to model the perturbed molecular networks and physiological processes in disease states to develop improved methods for disease diagnosis and treatment. Impactys provides a wide range of bioinformatic & computational medicine solutions, including:

  • Gene Expression Profiling
    • Next-generation RNA sequencing (RNA-Seq)
    • DNA microarray (DNA-chip)
  • Differential Expression Analyses
    • Fold change analysis (limma, DESeq2, sleuth)
    • Log ratio-mean average (MA) plot analysis
    • Principal component analysis (PCA)
    • Visualization (volcano plots, heatmaps, correlation matrices)
  • Network Analyses
    • Weighted gene co-expression network analysis (WGCNA)
    • Mutual information network analysis (MINET)
    • Network robustness, resilience, and vulnerability analysis (NetSwan)
    • Community structure analysis (igraph, Viper)
    • Protein-protein interaction analysis (STRING)
    • Metabolic network analysis (Sybil)
  • Gene Set Enrichment Analyses
    • Overrepresentation analysis (KEGG, Reactome, WkiPathways)
    • Pathway topology (KEGG, Reactome, WkiPathways)
  • ChIP-Seq Pipeline Analyses
    • Alignment (Bowtie2, SOAP, BWA, MAQ)
    • Strand cross-correlation/immunoprecipitation enrichment estimation (CHANCE, MACS)
    • Peak calling (point-source DBPs, broadly-enriched DBPs, mixed-signal DBPs)
    • Assessment of reproducibility
    • Differential binding analysis (DBChIP, MAnorm)
    • Downstream analysis (BEDTools, ChIPpeakAnno, MEME-ChIP, peak-motifs)