Search bioRxiv⌕ Search

Biology subjects

Rashed, W. M.

Publications and source records attributed to Rashed, W. M..

2 recordsLinked to original sources

rhinotypeR: An R package for Rhinovirus Genotyping

Rhinoviruses (RV) are common pathogens characterized by extremely high antigenic and genotypic diversity, yet the tools for their genotyping remain limited. We present rhinotypeR, a Bioconductor package designed to streamline the genotyping of RVs using the VP4/2 region by automating sequence comparison against prototype strains and applying predefined pairwise distance thresholds. RhinotypeR offers a comprehensive suite of functions, including sequence alignment, genetic distance calculation, and genotype assignment, which collectively simplify the often convoluted process of RV classification. Additionally, the package supports visualization tools for single-nucleotide polymorphisms (SNPs), amino acid substitutions, and phylogenetic relationships, providing an accessible platform for genetic analysis and evolutionary studies of RV. Comparative analyses demonstrate that genetic distance calculations by rhinotypeR align closely with established software such as MegaX and ape. RhinotypeR addresses the need for accessible and robust genotyping tools by offering a suite of functions that support the workflow of rhinovirus genetic analysis. It empowers researchers with a toolkit that enhances data processing efficiency and provides detailed, actionable insights into the genetic diversity and evolution of rhinoviruses.

bioinformatics↗

MicroRNA childhood Cancer Catalog (M3Cs): A Resource for Translational Bioinformatics Toward Health Informatics in Pediatric Cancer.

BackgroundMicroRNA childhood Cancer Catalog (M3Cs) is high-quality curated collection of published miRNA research studies on 16 pediatric cancer diseases. M3Cs scope was based on two approaches: data-driven clinical significance and data-driven human pediatric cell line models. MethodM3Cs development passed through three phases: 1. Literature Mining: It includes external database search and screening. 2. Data processing that includes 3 steps: a-Data Extraction, b-Data Curation & annotation, c-Web Development. 3. Publishing: Shinyapps.io was used as a web interface for the deployment of M3Cs. M3Cs is now available online and can be accessed through https://m3cs.shinyapps.io/M3Cs/. ResultsFor Data-driven clinical significance Approach, 538 miRNAs from 268 publications were reported in the clinical domain while 7 miRNAs from 5 publications were reported in the clinical & drug domain. For data-driven human pediatric cell line models approach, 538 miRNAs from 1268 publications were reported in cell line domain while 211 miRNAs from 177 publications in cell line & drug domain. ConclusionM3Cs acted to fill the gap by applying translational bioinformatics (TBI) general pathway to transfer data-driven research toward data-driven clinical care and/or hypothesis generation. Aggregated and well-curated data of M3Cs will enable stakeholders in health care to incorporate miRNA in the clinical policy.

bioinformatics↗