1
|
Chowdhury S, Sinha N, Ganguli P, Bhowmick R, Singh V, Nandi S, Sarkar RR. BIOPYDB: A Dynamic Human Cell Specific Biochemical Pathway Database with Advanced Computational Analyses Platform. J Integr Bioinform 2018; 15:/j/jib.ahead-of-print/jib-2017-0072/jib-2017-0072.xml. [PMID: 29547394 PMCID: PMC6340122 DOI: 10.1515/jib-2017-0072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 01/29/2018] [Indexed: 12/03/2022] Open
Abstract
BIOPYDB: BIOchemical PathwaY DataBase is developed as a manually curated, readily updatable, dynamic resource of human cell specific pathway information along with integrated computational platform to perform various pathway analyses. Presently, it comprises of 46 pathways, 3189 molecules, 5742 reactions and 6897 different types of diseases linked with pathway proteins, which are referred by 520 literatures and 17 other pathway databases. With its repertoire of biochemical pathway data, and computational tools for performing Topological, Logical and Dynamic analyses, BIOPYDB offers both the experimental and computational biologists to acquire a comprehensive understanding of signaling cascades in the cells. Automated pathway image reconstruction, cross referencing of pathway molecules and interactions with other databases and literature sources, complex search operations to extract information from other similar resources, integrated platform for pathway data sharing and computation, etc. are the novel and useful features included in this database to make it more acceptable and attractive to the users of pathway research communities. The RESTful API service is also made available to the advanced users and developers for accessing this database more conveniently through their own computer programmes.
Collapse
Affiliation(s)
- Saikat Chowdhury
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| | - Noopur Sinha
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| | - Piyali Ganguli
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| | - Rupa Bhowmick
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| | - Vidhi Singh
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India
| | - Sutanu Nandi
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| | - Ram Rup Sarkar
- CSIR- National Chemical Laboratory, Chemical Engineering and Process Development Division, Pune, Maharashtra 411008, India.,Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune, Maharashtra 411008, India
| |
Collapse
|
2
|
Liu ZP, Wu C, Miao H, Wu H. RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav095. [PMID: 26424082 PMCID: PMC4589691 DOI: 10.1093/database/bav095] [Citation(s) in RCA: 256] [Impact Index Per Article: 28.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Accepted: 09/04/2015] [Indexed: 01/01/2023]
Abstract
Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org
Collapse
Affiliation(s)
- Zhi-Ping Liu
- Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China and
| | - Canglin Wu
- Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Hongyu Miao
- Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Hulin Wu
- Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| |
Collapse
|
3
|
Kramer F, Bayerlová M, Beißbarth T. R-based software for the integration of pathway data into bioinformatic algorithms. BIOLOGY 2014; 3:85-100. [PMID: 24833336 PMCID: PMC4009765 DOI: 10.3390/biology3010085] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2013] [Revised: 11/29/2013] [Accepted: 01/31/2014] [Indexed: 11/16/2022]
Abstract
Putting new findings into the context of available literature knowledge is one approach to deal with the surge of high-throughput data results. Furthermore, prior knowledge can increase the performance and stability of bioinformatic algorithms, for example, methods for network reconstruction. In this review, we examine software packages for the statistical computing framework R, which enable the integration of pathway data for further bioinformatic analyses. Different approaches to integrate and visualize pathway data are identified and packages are stratified concerning their features according to a number of different aspects: data import strategies, the extent of available data, dependencies on external tools, integration with further analysis steps and visualization options are considered. A total of 12 packages integrating pathway data are reviewed in this manuscript. These are supplemented by five R-specific packages for visualization and six connector packages, which provide access to external tools.
Collapse
Affiliation(s)
- Frank Kramer
- University Medical Center Göttingen, Department of Medical Statistics, Humboldtallee 32, D-37073 Göttingen, Germany.
| | - Michaela Bayerlová
- University Medical Center Göttingen, Department of Medical Statistics, Humboldtallee 32, D-37073 Göttingen, Germany.
| | - Tim Beißbarth
- University Medical Center Göttingen, Department of Medical Statistics, Humboldtallee 32, D-37073 Göttingen, Germany.
| |
Collapse
|
4
|
Jewison T, Su Y, Disfany FM, Liang Y, Knox C, Maciejewski A, Poelzer J, Huynh J, Zhou Y, Arndt D, Djoumbou Y, Liu Y, Deng L, Guo AC, Han B, Pon A, Wilson M, Rafatnia S, Liu P, Wishart DS. SMPDB 2.0: big improvements to the Small Molecule Pathway Database. Nucleic Acids Res 2013; 42:D478-84. [PMID: 24203708 PMCID: PMC3965088 DOI: 10.1093/nar/gkt1067] [Citation(s) in RCA: 285] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
The Small Molecule Pathway Database (SMPDB, http://www.smpdb.ca) is a comprehensive, colorful, fully searchable and highly interactive database for visualizing human metabolic, drug action, drug metabolism, physiological activity and metabolic disease pathways. SMPDB contains >600 pathways with nearly 75% of its pathways not found in any other database. All SMPDB pathway diagrams are extensively hyperlinked and include detailed information on the relevant tissues, organs, organelles, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Since its last release in 2010, SMPDB has undergone substantial upgrades and significant expansion. In particular, the total number of pathways in SMPDB has grown by >70%. Additionally, every previously entered pathway has been completely redrawn, standardized, corrected, updated and enhanced with additional molecular or cellular information. Many SMPDB pathways now include transporter proteins as well as much more physiological, tissue, target organ and reaction compartment data. Thanks to the development of a standardized pathway drawing tool (called PathWhiz) all SMPDB pathways are now much more easily drawn and far more rapidly updated. PathWhiz has also allowed all SMPDB pathways to be saved in a BioPAX format. Significant improvements to SMPDB’s visualization interface now make the browsing, selection, recoloring and zooming of pathways far easier and far more intuitive. Because of its utility and breadth of coverage, SMPDB is now integrated into several other databases including HMDB and DrugBank.
Collapse
Affiliation(s)
- Timothy Jewison
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8, Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8 and National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, AB, Canada T6G 2M9
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|