Abstract
Analysis of Pan-omics Data in Human Interactome Network (APODHIN) is a platform for integrative analysis of transcriptomics, proteomics, genomics, and metabolomics data for identification of key molecular players and their interconnections exemplified in cancer scenario. APODHIN works on a meta-interactome network consisting of human protein–protein interactions (PPIs), miRNA-target gene regulatory interactions, and transcription factor-target gene regulatory relationships. In its first module, APODHIN maps proteins/genes/miRNAs from different omics data in its meta-interactome network and extracts the network of biomolecules that are differentially altered in the given scenario. Using this context specific, filtered interaction network, APODHIN identifies topologically important nodes (TINs) implementing graph theory based network topology analysis and further justifies their role via pathway and disease marker mapping. These TINs could be used as prospective diagnostic and/or prognostic biomarkers and/or potential therapeutic targets. In its second module, APODHIN attempts to identify cross pathway regulatory and PPI links connecting signaling proteins, transcription factors (TFs), and miRNAs to metabolic enzymes via utilization of single-omics and/or pan-omics data and implementation of mathematical modeling. Interconnections between regulatory components such as signaling proteins/TFs/miRNAs and metabolic pathways need to be elucidated more elaborately in order to understand the role of oncogene and tumor suppressors in regulation of metabolic reprogramming during cancer. APODHIN platform contains a web server component where users can upload single/multi omics data to identify TINs and cross-pathway links. Tabular, graphical and 3D network representations of the identified TINs and cross-pathway links are provided for better appreciation. Additionally, this platform also provides few example data analysis of cancer specific, single and/or multi omics dataset for cervical, ovarian, and breast cancers where meta-interactome networks, TINs, and cross-pathway links are provided. APODHIN platform is freely available at http://www.hpppi.iicb.res.in/APODHIN/home.html.
Highlights
Technological advances have made different types of omics data accessible in large scale
This meta-interactome consists of human protein– protein interaction network (HPPIN), network of human miRNAs and their target genes and network of human transcription factors (TFs) and their target genes
Large-scale genomics, transcriptomics and proteomics approaches have made it possible to characterize different clinical spectra associated with cancers
Summary
Technological advances have made different types of omics data accessible in large scale. Different types of omics data are outcomes of profiling of different bio-entities, namely RNA (RNA transcriptomics), miRNA (miRNA transcriptomics), proteins (proteomics, phosphoproteomics), genes (genomics, epigenomics), metabolites (metabolomics), lipids (lipidomics), and pharmacogenomics. These bio-entities are functionally inter-related in a complex fashion. Because of the heterogeneous nature of the diseases, even if patients having similar pathological features are treated the disease prognosis differs a lot It shows the inadequacy of symptom-based diagnosis and demands patient-specific analysis of omics data. Pan-omics data enable us to predict novel functional interactions between molecular mediators at multiple levels. Patient-specific pan-omics data analysis is going to disclose the genetic, epigenetic, and other functional profiles responsible for the disease of an individual which might eventually lead to the development of individualistic “precision medicine” and will provide right treatment to right patient at right time
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
