MolEvolvR: A webapp for characterizing proteins using molecular evolution and phylogeny

Studying how bacterial pathogenic proteins evolve can help identify lineage-specific and pathogen-specific signatures and variants, and consequently, their functions. We have developed a streamlined computational approach for characterizing the …

Using a computational molecular evolution and phylogeny to study pathogenic proteins

Background: Studying bacterial physiology, adaptation, and pathogenicity through the lens of evolution requires delineating the phylogenetic history of bacterial proteins and genomes. Moreover, delineating this history of proteins is best done at all …

S-layers: the proteinaceous multifunctional armours of Gram-positive pathogens

MolEvolvR: a web-app for molecular evolution and phylogeny

We will discuss the alpha version of their new easy-to-use interactive webapp: MolEvolvR, for characterizing proteins using molecular evolution and phylogeny. We will begin by demonstrating the power of MolEvolvR using the panbacterial stress response system, PSP (phage shock protein), as an example. Then, we will anyone can use this app to study their protein(s) of interest. PSP app: (bioRxiv 2020) MolEvolvR app: (currently, alpha-version)

Discovery of a predominant and distinct lineage of Mycobacterium tuberculosis in Brazilian indigenous population

After nearly a century of vaccination and six decades of drug therapy, tuberculosis (TB) kills more people annually than any other infectious disease. Substantial challenges to disease eradication remain among vulnerable and underserved populations. …

Computational evolutionary approaches

Integrating molecular evolution and comparative genomics to achieve comprehensive, multiscale characterization of bacterial proteins and genomic features.

sRNA discovery

Discovering unique pathogenic sRNA in infected hosts

Phage-shock-protein (Psp) Envelope Stress Response: Evolutionary History & Discovery of Novel Players

Phylogenetics & Comparative Genomics | MMG801

Computational evolutionary approaches for understanding pathogen proteins and genomes