Muhammad Arif

TL;DR: A Human Pathology Atlas has been created as part of the Human Protein Atlas program to explore the prognostic role of each protein-coding gene in 17 different cancers, and reveals that gene expression of individual tumors within a particular cancer varied considerably and could exceed the variation observed between distinct cancer types.

TL;DR: In this article, the authors combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution singlecell type map of human tissues, which was used to explore the expression of human protein-coding genes in 192 individual cell type clusters.

TL;DR: A comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle is presented in this article.

TL;DR: The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters.

TL;DR: Biological networks provide new opportunities for understanding the cellular biology in both health and disease states and can be employed in the analysis of omics data, provide detailed insight into disease mechanisms by identifying the key biological components and eventually can be used in the development of efficient treatment strategies.