The emergence of spatial multi-omics has helped address the limitations of single-cell
sequencing, which often leads to the loss of spatial context among cell populations …

Conventional supervised binary classification algorithms have been widely applied to
address significant research questions using biological and biomedical data. This …

Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass
spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we …

Defining protein–protein interactions (PPIs) in their native environment is crucial to
understanding protein structure and function. Cross-linking–mass spectrometry (XL-MS) has …

Protein–protein interactions (PPIs) drive cellular processes and responses to environmental
cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning …

Most proteins are organized in macromolecular assemblies, which represent key functional
units regulating and catalyzing most cellular processes. Affinity purification of the protein of …

Advancements in genomic and proteomic technologies have powered the creation of large
gene and protein networks (“interactomes”) for understanding biological systems. However …

Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful technique for
interactome mapping. However, there is little consensus on optimal strategies for the design …

Host-pathogen interactions are pivotal in regulating establishment, progression, and
outcome of an infection. While affinity-purification mass spectrometry has become …

Cellular activities are carried out vastly by protein complexes but large repertoire of protein
complexes remains functionally uncharacterized which necessitate new strategies to …