Abstract
The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) continues to be a major resource for mining pancreatic –omics data a decade after its initial release. Here, we present recent updates to PED and describe its evolution into a comprehensive resource for extracting, analysing and integrating publicly available multi-omics datasets. A new analytical module has been implemented to run in parallel with the existing literature mining functions. This analytical module has been created using rich data content derived from pancreas-related specimens available through the major data repositories (GEO, ArrayExpress) and international initiatives (TCGA, GENIE, CCLE). Researchers have access to a host of functions to tailor analyses to meet their needs. Results are presented using interactive graphics that allow the molecular data to be visualized in a user-friendly manner. Furthermore, researchers are provided with the means to superimpose layers of molecular information to gain greater insight into alterations and the relationships between them. The literature-mining module has been improved with a redesigned web appearance, restructured query platforms and updated annotations. These updates to PED are in preparation for its integration with the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), a vital resource of pancreas cancer tissue for researchers to support and promote cutting-edge research.
Highlights
Pancreatic Cancer (PC) is a death sentence for most of its patients and is projected to be one of the leading causes of cancer-related death by 2030, second only to lung cancer [1,2]
The emphasis is on pancreatic malignancies, Pancreatic Expression Database (PED) incorporates published findings on pancreatic precursor lesions, including pancreatic intraepithelial neoplasias (PanINs), intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), as well as benign conditions such as chronic pancreatitis
Using the literature mining module of PED, researchers can quickly search for homozygously co-deleted genes proximal to TSG, and their paralogous isoforms, a task that otherwise involves laborious data retrieval from a number of relevant studies and considerable additional data processing
Summary
Pancreatic Cancer (PC) is a death sentence for most of its patients and is projected to be one of the leading causes of cancer-related death by 2030, second only to lung cancer [1,2]. The Pancreatic Expression Database (PED) [5,6,7] was developed as a data repository to provide researchers with a single-entry point from which to manipulate, mine and integrate these heterogeneous and isolated findings into their own research. Since its inception in 2007, the literature mining module of PED has been enriched through manual selection of pancreas-related papers, followed by data curation and review of the reported findings.
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