Biswas Nupur, Kumar Krishna, Bose Sarpita, Bera Raisa, Chakrabarti Saikat
Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, India.
Front Genet. 2020 Dec 8;11:589231. doi: 10.3389/fgene.2020.589231. eCollection 2020.
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.
人类相互作用组网络中的泛组学数据分析（APODHIN）是一个用于对转录组学、蛋白质组学、基因组学和代谢组学数据进行综合分析的平台，旨在识别关键分子参与者及其相互联系，以癌症场景为例。APODHIN作用于一个元相互作用组网络，该网络由人类蛋白质-蛋白质相互作用（PPI）、miRNA-靶基因调控相互作用和转录因子-靶基因调控关系组成。在其第一个模块中，APODHIN在其元相互作用组网络中映射来自不同组学数据的蛋白质/基因/miRNA，并提取在给定场景中差异改变的生物分子网络。利用这个上下文特定的、经过筛选的相互作用网络，APODHIN通过基于图论的网络拓扑分析识别拓扑重要节点（TIN），并通过通路和疾病标志物映射进一步验证它们的作用。这些TIN可作为潜在的诊断和/或预后生物标志物和/或潜在的治疗靶点。在其第二个模块中，APODHIN试图通过利用单一组学和/或泛组学数据以及实施数学建模，识别连接信号蛋白、转录因子（TF）和miRNA与代谢酶的跨通路调控和PPI链接。为了理解癌基因和肿瘤抑制因子在癌症期间代谢重编程调控中的作用，需要更详细地阐明信号蛋白/TF/miRNA等调控成分与代谢通路之间的相互联系。APODHIN平台包含一个网络服务器组件，用户可以在其中上传单一组学/多组学数据以识别TIN和跨通路链接。提供已识别的TIN和跨通路链接的表格、图形和3D网络表示，以便更好地理解。此外，该平台还提供了针对宫颈癌、卵巢癌和乳腺癌的癌症特异性单一组学和/或多组学数据集的一些示例数据分析，其中提供了元相互作用组网络、TIN和跨通路链接。APODHIN平台可在http://www.hpppi.iicb.res.in/APODHIN/home.html免费获取。
