PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology
Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpoint, we herein feature the applications of contemporary database management to the development of PPDB, a searching and browsing tool for the Plants Physiology Database that is based upon the mining of a large amount of gene ontology data currently available. The working principles and search options associated with the PPDB are publicly available and freely accessible online (http://www.iitr.ac.in/ajayshiv/) through a user-friendly environment generated by means of Drupal-6.24. By knowing that genes are expressed in temporally and spatially characteristic patterns and that their functionally distinct products often reside in specific cellular compartments and may be part of one or more multicomponent complexes, this sort of work is intended to be relevant for investigating the functional relationships of gene products at a system level and, thus, helps us approach to the full physiology.
KeywordsBiology Bioinformatics Database Data mining Functional genomics Gene ontology Gene products Physiology Plant
We acknowledge the gene ontology consortium and open-source community as the source and inspiration for Plants Physiology Database. The authors also acknowledge AmiGO for the sourced term images on PPDB web site. The authors are thankful to Indian Institute of Technology, Roorkee, for providing the facilities to carry out this work. The authors also recognize contributions made by Dr. Petar M. Mitrasinovic. Ajay Shiv Sharma thanks to All India Council for Technical Education, Ministry of Human Resource Development, Government of India, for providing financial assistance.
- 3.Sharma AS, Gupta HO, Prasad R, Mitrasinovic PM (2013) Microarray database bioinformatics usher functional genomics to unveil biological knowledge underlying physiology. In: International conference on recent trends in computing, 4–5 Oct 2013. ICRTC 2013, SRM University, NCR Campus, Ghaziabad, India, pp 218–224Google Scholar
- 7.Wang JZ, Du Z, Yu PS, Chen CF (2007) An efficient online tool to search Top-N genes with similar biological functions in gene ontology database. In: BIBM 2007 international conference on bioinformatics and biomedicine, 2–4 Nov 2007. IEEE, Fremont, CA, USA, pp 406–411Google Scholar
- 22.Tari L, Baral C, Dasgupta P (2005) Understanding the global properties of functionally-related gene networks using the Gene Ontology. In: Pacific symposium on biocomputing 2005. 4–8 Jan 2005, Fairmont Orchid, Big Island of Hawaii. PSB, Stanford, CA, USA, pp 209–220Google Scholar
- 24.Mutowo-Meullenet P, Huntley RP, Dimmer EC, Alam-Faruque Y, Sawford T, Martin MJ, O’Donovan C, Apweiler R (2013) Use of Gene Ontology annotation to understand the peroxisome proteome in humans. Database 2013, bas062Google Scholar
- 26.Ficklin SP, Sanderson LA, Cheng CH, Staton ME, Lee T, Cho IH, Jung S, Bett KE, Main D (2011) Tripal: a construction toolkit for online genome databases. Database 2011, bar044Google Scholar
- 32.Chakrabarti S, Cox E, Frank E, Güting RH, Han J, Jiang X, Kamber M, Lightstone SS, Nadeau TP, Neapolitan RE et al (2008) Data Mining: Know It All: Know It All. Morgan Kaufmann, Burlington, MA, USAGoogle Scholar