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PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology

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Abstract

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.

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References

  1. Banihashemi K (2009) Iranian human genome project: overview of a research process among Iranian ethnicities. Indian J Hum Genet 15:88–92

    Article  Google Scholar 

  2. Katzman S, Capra JA, Haussler D, Pollard KS (2011) Ongoing GC-biased evolution is widespread in the human genome and enriched near recombination hot spots. Genome Biol Evol 3:614–626

    Article  CAS  Google Scholar 

  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 218–224

  4. Lewis SE (2005) Gene ontology: looking backwards and forwards. Genome Biol 6(1):103

    Article  Google Scholar 

  5. Blake JA, Corradi J, Eppig JT, Hill DP, Richardson JE, Ringwald M (2001) Creating the gene ontology resource: design and implementation. Genome Res 11:1425–1433

    Article  Google Scholar 

  6. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT et al (2000) Gene ontology: tool for the unification of biology. Nat Genet 25:25–29

    Article  CAS  Google 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 406–411

  8. McCarthy FM, Mahony TJ, Parcells MS, Burgess SC (2009) Understanding animal viruses using the Gene Ontology. Trends Microbiol 17:328–335

    Article  CAS  Google Scholar 

  9. Jiang W, Li X, Rao S, Wang L, Du L, Li C, Wu C, Wang H, Wang Y, Yang B (2008) Constructing disease-specific gene networks using pair-wise relevance metric: application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements. BMC Syst Biol 2:72

    Article  Google Scholar 

  10. Buza JJ, Burgess SC (2008) Different signaling pathways expressed by chicken naive CD4+ T cells, CD4+ lymphocytes activated with staphylococcal enterotoxin B, and those malignantly transformed by Marek’s disease virus. J Proteome Res 7:2380–2387

    Article  CAS  Google Scholar 

  11. Kumar S, Buza JJ, Burgess SC (2009) Genotype-dependent tumor regression in Marek’s disease mediated at the level of tumor immunity. Cancer Microenviron 2:23–31

    Article  CAS  Google Scholar 

  12. Klein G (2002) Perspectives in studies of human tumor viruses. Front Biosci 7:d268–d274

    Article  CAS  Google Scholar 

  13. Klouche M, Carruba G, Castagnetta L, Rose-John S (2004) Virokines in the pathogenesis of cancer: focus on human herpesvirus 8. Ann Ny Acad Sci 1028:329–339

    CAS  PubMed  Google Scholar 

  14. Smith SA, Kotwal GJ (2001) Virokines: novel immunomodulatory agents. Expert Opin Biol Ther 1:343–357

    Article  CAS  Google Scholar 

  15. Torto-Alalibo T, Collmer C, Gwinn-Giglio M (2009) The plant-associated Microbe Gene Ontology (PAMGO) consortium: community development of new Gene Ontology terms describing biological processes involved in microbe-host interactions. BMC Microbiol 9:S1

    Article  Google Scholar 

  16. Bassingthwaighte JB (2000) Strategies for the physiome project. Ann Biomed Eng 28:1043–1058

    Article  CAS  Google Scholar 

  17. Crampin EJ, Halstead M, Hunter P, Nielsen P, Noble D, Smith N, Tawhai M (2004) Computational physiology and the physiome project. Exp Physiol 89:1–26

    Article  Google Scholar 

  18. Meier S, Gehring C (2008) A guide to the integrated application of on-line data mining tools for the inference of gene functions at the systems level. Biotechnol J 3:1375–1387

    Article  CAS  Google Scholar 

  19. Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R, Eilbeck K, Lewis S, Marshall B, Mungall C et al (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res 32:D258–D261

    Article  CAS  Google Scholar 

  20. Diehl AD, Lee JA, Scheuermann RH, Blake JA (2007) Ontology development for biological systems: immunology. Bioinformatics 23:913–915

    Article  CAS  Google Scholar 

  21. Sharma AS, Gupta HO, Mitrasinovic PM (2012) From ontology-based gene function to physiological model. Curr Bioinform 7:436–446

    Article  CAS  Google 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 209–220

  23. Thomas PD, Mi H, Lewis S (2007) Ontology annotation: mapping genomic regions to biological function. Curr Opin Chem Biol 11:4–11

    Article  CAS  Google 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, bas062

  25. Jaiswal P, Avraham S, Ilic K, Kellogg EA, McCouch S, Pujar A, Reiser L, Rhee SY, Sachs MM, Schaeffer M et al (2005) Plant ontology (PO): a controlled vocabulary of plant structures and growth stages. Comp Funct Genom 6:388–397

    Article  CAS  Google 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, bar044

  27. Papanicolaou A, Heckel DG (2010) The GMOD Drupal bioinformatic server framework. Bioinformatics 26:3119–3124

    Article  CAS  Google Scholar 

  28. Pettifer S, Thorne D, McDermott P, Attwood T, Baran J, Bryne JC, Hupponen T, Mowbray D, Vriend G (2009) An active registry for bioinformatics web services. Bioinformatics 25:2090–2091

    Article  CAS  Google Scholar 

  29. Krupp M, Marquardt JU, Sahin U, Galle PR, Castle J, Teufel A (2012) RNA-Seq Atlas–a reference database for gene expression profiling in normal tissue by next-generation sequencing. Bioinformatics 28:1184–1185

    Article  CAS  Google Scholar 

  30. Smedley D, Schofield P, Chen CK, Aidinis V, Ainali C, Bard J, Balling R, Birney E, Blake A, Bongcam-Rudloff E et al. (2010) Finding and sharing: new approaches to registries of databases and services for the biomedical sciences. Database 2010, baq014

    Article  Google Scholar 

  31. Vanhee P, Reumers J, Stricher F, Baeten L, Serrano L, Schymkowitz J, Rousseau F (2010) PepX: a structural database of non-redundant protein-peptide complexes. Nucleic Acids Res 38:D545–D551

    Article  CAS  Google 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, USA

    Google Scholar 

  33. Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S (2009) AmiGO: online access to ontology and annotation data. Bioinformatics 25:288–289

    Article  CAS  Google Scholar 

  34. Renfro DP, McIntosh BK, Venkatraman A, Siegele DA, Hu JC (2012) GONUTS: the gene ontology normal usage tracking system. Nucleic Acids Res 40:D1262–D1269

    Article  CAS  Google Scholar 

  35. Binns D, Dimmer E, Huntley R, Barrell D, O’Donovan C, Apweiler R (2009) QuickGO: a web-based tool for Gene Ontology searching. Bioinformatics 25:3045–3046

    Article  CAS  Google Scholar 

  36. McIntosh BK, Renfro DP, Knapp GS, Lairikyengbam CR, Liles NM, Niu L, Supak AM, Venkatraman A, Zweifel AE, Siegele DA et al (2012) EcoliWiki: a wiki-based community resource for Escherichia coli. Nucleic Acids Res 40:D1270–D1277

    Article  CAS  Google Scholar 

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Acknowledgments

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.

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  1. Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India

    Ajay Shiv Sharma, Hari Om Gupta & Rajendra Prasad

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  1. Ajay Shiv Sharma
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  2. Hari Om Gupta
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  3. Rajendra Prasad
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Correspondence to Ajay Shiv Sharma.

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Sharma, A.S., Gupta, H.O. & Prasad, R. PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology. Interdiscip Sci Comput Life Sci 7, 295–308 (2015). https://doi.org/10.1007/s12539-015-0017-y

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  • DOI: https://doi.org/10.1007/s12539-015-0017-y

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