HPiP - Host-Pathogen Interaction Prediction
HPiP (Host-Pathogen Interaction Prediction) uses an ensemble learning algorithm for prediction of host-pathogen protein-protein interactions (HP-PPIs) using structural and physicochemical descriptors computed from amino acid-composition of host and pathogen proteins.The proposed package can effectively address data shortages and data unavailability for HP-PPI network reconstructions. Moreover, establishing computational frameworks in that regard will reveal mechanistic insights into infectious diseases and suggest potential HP-PPI targets, thus narrowing down the range of possible candidates for subsequent wet-lab experimental validations.
Last updated
proteomicssystemsbiologynetworkinferencestructuralpredictiongenepredictionnetwork
5.38 score 4 stars 7 scripts 384 downloadsTENxXeniumData - Collection of Xenium spatial data by 10X genomics
Collection of Xenium spatial transcriptomics datasets provided by 10x Genomics, formatted into the Bioconductor classes, the SpatialExperiment or SpatialFeatureExperiment (SFE), to facilitate seamless integration into various applications, including examples, demonstrations, and tutorials. The constructed data objects include gene expression profiles, per-transcript location data, centroid, segmentation boundaries (e.g., cell or nucleus boundaries), and image.
Last updated
experimentdataexperimenthubspatialdatadatapkg
4.48 score 3 stars 2 scripts