- The pancreatic expression database: recent extensions and updates. [PMID: 24163255]
Abu Z Dayem Ullah, Rosalind J Cutts, Millika Ghetia, Emanuela Gadaleta, Stephan A Hahn, Tatjana Crnogorac-Jurcevic, Nicholas R Lemoine, Claude Chelala
Nucleic acids research 2014:42(Database issue)
14 Citations (Google Scholar as of 2016-03-25)
Abstract: The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) is the only device currently available for mining of pancreatic cancer literature data. It brings together the largest collection of multidimensional pancreatic data from the literature including genomic, proteomic, microRNA, methylomic and transcriptomic profiles. PED allows the user to ask specific questions on the observed levels of deregulation among a broad range of specimen/experimental types including healthy/patient tissue and body fluid specimens, cell lines and murine models as well as related treatments/drugs data. Here we provide an update to PED, which has been previously featured in the Database issue of this journal. Briefly, PED data content has been substantially increased and expanded to cover methylomics studies. We introduced an extensive controlled vocabulary that records specific details on the samples and added data from large-scale meta-analysis studies. The web interface has been improved/redesigned with a quick search option to rapidly extract information about a gene/protein of interest and an upload option allowing users to add their own data to PED. We added a user guide and implemented integrated graphical tools to overlay and visualize retrieved information. Interoperability with biomart-compatible data sets was significantly improved to allow integrative queries with pancreatic cancer data.
- The Pancreatic Expression database: 2011 update. [PMID: 20959292]
Rosalind J Cutts, Emanuela Gadaleta, Stephan A Hahn, Tatjana Crnogorac-Jurcevic, Nicholas R Lemoine, Claude Chelala
Nucleic acids research 2011:39(Database issue)
27 Citations (Google Scholar as of 2016-01-17)
Abstract: The Pancreatic Expression database (PED, http://www.pancreasexpression.org) has established itself as the main repository for pancreatic-derived -omics data. For the past 3 years, its data content and access have increased substantially. Here we describe several of its new and improved features, such as data content, which now includes over 60,000 measurements derived from transcriptomics, proteomics, genomics and miRNA profiles from various pancreas-centred reports on a broad range of specimen and experimental types. We also illustrate the capabilities of its interface, which allows integrative queries that can combine PED data with a growing number of biological resources such as NCBI, Ensembl, UniProt and Reactome. Thus, PED is capable of retrieving and integrating different types of -omics, annotations and clinical data. We also focus on the importance of data sharing and interoperability in the cancer field, and the integration of PED into the International Cancer Genome Consortium (ICGC) data portal.
- Pancreatic Expression database: a generic model for the organization, integration and mining of complex cancer datasets. [PMID: 18045474]
Claude Chelala, Stephan A Hahn, Hannah J Whiteman, Sayka Barry, Deepak Hariharan, Tomasz P Radon, Nicholas R Lemoine, Tatjana Crnogorac-Jurcevic
BMC genomics 2007:8
34 Citations (Google Scholar as of 2016-01-18)
Abstract: Pancreatic cancer is the 5th leading cause of cancer death in both males and females. In recent years, a wealth of gene and protein expression studies have been published broadening our understanding of pancreatic cancer biology. Due to the explosive growth in publicly available data from multiple different sources it is becoming increasingly difficult for individual researchers to integrate these into their current research programmes. The Pancreatic Expression database, a generic web-based system, is aiming to close this gap by providing the research community with an open access tool, not only to mine currently available pancreatic cancer data sets but also to include their own data in the database. Currently, the database holds 32 datasets comprising 7636 gene expression measurements extracted from 20 different published gene or protein expression studies from various pancreatic cancer types, pancreatic precursor lesions (PanINs) and chronic pancreatitis. The pancreatic data are stored in a data management system based on the BioMart technology alongside the human genome gene and protein annotations, sequence, homologue, SNP and antibody data. Interrogation of the database can be achieved through both a web-based query interface and through web services using combined criteria from pancreatic (disease stages, regulation, differential expression, expression, platform technology, publication) and/or public data (antibodies, genomic region, gene-related accessions, ontology, expression patterns, multi-species comparisons, protein data, SNPs). Thus, our database enables connections between otherwise disparate data sources and allows relatively simple navigation between all data types and annotations. The database structure and content provides a powerful and high-speed data-mining tool for cancer research. It can be used for target discovery i.e. of biomarkers from body fluids, identification and analysis of genes associated with the progression of cancer, cross-platform meta-analysis, SNP selection for pancreatic cancer association studies, cancer gene promoter analysis as well as mining cancer ontology information. The data model is generic and can be easily extended and applied to other types of cancer. The database is available online with no restrictions for the scientific community at http://www.pancreasexpression.org/.