Skip to main content
SpringerLink
Log in

Visual-X2: interactive visualization and analysis tool for protein crystallization

  • Original Article
  • Published:
Network Modeling Analysis in Health Informatics and Bioinformatics Aims and scope Submit manuscript

Abstract

In high-throughput systems, the crystallization experiments require the inspection and analysis of a large number of trial images. The visualization and analysis tools are needed to view and analyze the experimental results, and recommend novel crystalline conditions by analyzing prior results. It is essential to integrate all these components into a single system. Therefore, we developed Visual-X2, an interactive visualization software developed to aid the user for quick and efficient visualization and analysis of the results of the experiments. Visual-X2 has a number of useful features for visualization and analysis: dual plate view (thumbnail and symbolic), detailed well view with scoring option, multiple-scan and time-course views, support for screening analysis based on multiple screens, three novel screen analysis methods (associative experimental design, GenScreen, and novelty methods), and generating pipetting file with a family of conditions varying concentrations based on stock concentration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. Contact Dr. Ramazan Aygun (aygunr@uah.edu) to evaluate Visual-X2 tool.

References

  • Acharya S (2017) GenScreen : A genetic algorithm for protein crystallization screening, Master’s thesis, The University of Alabama in Huntsville, Huntsville, Alabama, USA

  • Acharya S, Pusey M, Aygun R, Dinç I (2016) A genetic algorithm for the optimization of protein crystallization screening. In: International conference on crystallization of biological macromolecules, Praha. http://www.xray.cz/iccbm/files/664.htm, http://www.xray.cz/iccbm/

  • Bhattarai B, Shrestha M, Aygun RS, Pusey ML (2017) Optimizing genetic algorithm for protein crystallization screening using an exploratory fitness function. In: 2017 IEEE international conference on bioinformatics and biomedicine (BIBM), Kansas City, MO, 2017, pp 2083–2090. https://doi.org/10.1109/BIBM.2017.8217981

  • CrystalTrak (2009) X-ray crystallography-crystaltrak software user manual. http://xray.dhvi.duke.edu/files/documents/training%20-%20CrystalTrak.pdf. Accessed 21 Nov 2015

  • Daniel E, Lin B, Diprose JM, Griffiths SL, Morris C, Berry IM, Owens RJ, Blake R, Wilson KS, Stuart DI et al (2011) xtalpims: a pims-based web application for the management and monitoring of crystallization trials. J Struct Biol 175(2):230–235

    Article  Google Scholar 

  • Dinç I, Pusey ML, Aygün RS (2015) Protein crystallization screening using associative experimental design. In: Harrison R, Li Y, Măndoiu I. (eds) Bioinformatics Research and Applications. ISBRA 2015. Lecture Notes in Computer Science, vol 9096. Springer, Cham

  • Dinç İ, Pusey ML, Aygün RS (2016a) Optimizing associative experimental design for protein crystallization screening. IEEE Trans Nanobiosci 15(2):101–112. https://doi.org/10.1109/TNB.2016.2536030

    Article  Google Scholar 

  • Dinc I, Pusey M, Aygun RS (2016b) Visual-x2: scoring and symbolic visualization tool for analysis of protein crystallization trial images. In: Frontiers in structural biology of membrane protein & Pittsburgh Diffraction Conference, Huntsville, AL

  • Dinç I, Dinç S, Sigdel M, Sigdel MS, Pusey ML, Aygun RS (2017) Super-thresholding: supervised thresholding of protein crystal images. IEEE/ACM Trans Comput Biol Bioinform 14(4):986–998. https://doi.org/10.1109/TCBB.2016.2542811

    Article  Google Scholar 

  • Esser L, Xia D (2011) Cryspage: a program for displaying images of crystallization trials, rapid comparisons and analysis. J Appl Crystallogr 44(5):1130–1131

    Article  Google Scholar 

  • Formulatrix (2002) Rock maker official website. http://formulatrix.com/protein-crystallization/products/rock-maker/index.html. Accessed 13 Jan 2016

  • Hiraki M, Kato R, Nagai M, Satoh T, Hirano S, Ihara K, Kudo N, Nagae M, Kobayashi M, Inoue M et al (2006) Development of an automated large-scale protein-crystallization and monitoring system for high-throughput protein-structure analyses. Acta Crystallogr Sect D Biol Crystallogr 62(9):1058–1065

    Article  Google Scholar 

  • Juttu MK, Pusey ML, Aygun RS (2019) Protein crystallization screening using enhanced associative experimental design. Netw Model Anal Health Inform Bioinform 8(1):17

    Article  Google Scholar 

  • Luft JR, Collins RJ, Fehrman NA, Lauricella AM, Veatch CK, DeTitta GT (2003) A deliberate approach to screening for initial crystallization conditions of biological macromolecules. J Struct Biol 142(1):170–179

    Article  Google Scholar 

  • Nagel RM, Luft JR, Snell EH (2008) Autosherlock: a program for effective crystallization data analysis. J Appl Crystallogr 41(6):1173–1176

    Article  Google Scholar 

  • Newman J, Pham TM, Peat TS (2008) Phoenito experiments: combining the strengths of commercial crystallization automation. Acta Crystallogr Sect F Struct Biol Crysta Commun 64(11):991–996

    Article  Google Scholar 

  • Pusey ML, Aygun RS (2017) Data analytics for protein crystallization. Springer, Cham

    Book  Google Scholar 

  • Shrestha M, Tran TX, Bhattarai B, Pusey ML, Aygun RS (2019) Schema matching and data integration with consistent naming on protein crystallization screens. IEEE ACM Trans Comput Biol Bioinform. https://doi.org/10.1109/TCBB.2019.2913368

    Article  Google Scholar 

  • Shrestha M, Bhattarai B, Aygun RS, Pusey ML (2017) Schema matching and data integration on protein crystallization screens. In: IEEE international conference on bioinformatics and biomedicine (BIBM), Kansas City, MO, 2017, USA, pp 2306–2308. https://doi.org/10.1109/BIBM.2017.8218037

  • Sigdel M, Pusey ML, Aygun RS (2013) Real-time protein crystallization image acquisition and classification system. Cryst Growth Des 13(7):2728–2736

    Article  Google Scholar 

  • Sigdel M, Pusey ML, Aygun RS (2015) Crystpro: spatiotemporal analysis of protein crystallization images. Cryst Growth Des 15(11):5254–5262

    Article  Google Scholar 

  • Sigdel MS, Sigdel M, Dinç S, Dinc I, Pusey ML, Aygün RS (2016) Focusall: focal stacking of microscopic images using modified harris corner response measure. IEEE/ACM Trans Comput Biol Bioinform 13(2):326–340

    Article  Google Scholar 

  • Sigdel M, Dinc I, Sigdel MS, Dinc S, Pusey ML, Aygun RS (2017) Feature analysis for classification of trace fluorescent labeled protein crystallization images. Biodata Min 10(1):14

    Article  Google Scholar 

  • Snell EH, Nagel RM, Wojtaszcyk A, O’Neill H, Wolfley JL, Luft JR (2008) The application and use of chemical space mapping to interpret crystallization screening results. Acta Crystallogr Sect D Biol Crystallogr 64(12):1240–1249

    Article  Google Scholar 

  • Subedi S, Pusey ML, Aygun RS (2017) Visual-x2: scoring and visualization tool for analysis of protein crystallization trial images. In: 2017 IEEE international conference on bioinformatics and biomedicine (BIBM), Kansas City, MO, 2017, USA, pp 2316–2318. https://doi.org/10.1109/BIBM.2017.8218041

  • Walter TS, Diprose JM, Mayo CJ, Siebold C, Pickford M G, Carter L, Sutton G C, Berrow N S, Brown J, Berry I M et al (2005) A procedure for setting up high-throughput nanolitre crystallization experiments. Crystallization workflow for initial screening, automated storage, imaging and optimization. Acta Crystallogr Sect D Biol Crystallogr 61(6):651–657

    Article  Google Scholar 

  • Ware C (2012) Information visualization: perception for design. Elsevier, New York

    Google Scholar 

Download references

Acknowledgements

This research was supported by National Institutes of Health (GM116283) Grant. This paper is an expanded version of our paper Subedi et al. (2017). ©2017 IEEE. Reprinted, with permission, from S. Subedi, M. L. Pusey and R. S. Aygun, “Visual-X2: Scoring and visualization tool for analysis of protein crystallization trial images,” 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 2316–2318. https://doi.org/10.1109/BIBM.2017.8218041. An earlier version of the symbolic view interface (Fig. 2) has appeared in (Pusey and Aygun 2017).

Author information

Authors and Affiliations

  1. Data Media Lab, Computer Science Department, University of Alabama in Huntsville, Huntsville, AL, USA

    Suraj Subedi, Truong X. Tran, Diwas Sharma, Buddha R. Shrestha & Ramazan S. Aygun

  2. Troy University, Montgomery, AL, USA

    Imren Dinc

  3. iXpressGenes, Inc., 601 Genome Way, Huntsville, AL, USA

    Marc L. Pusey

  4. Department of Chemistry, University of Alabama in Huntsville, Huntsville, AL, USA

    Marc L. Pusey

Authors
  1. Suraj Subedi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Imren Dinc
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Truong X. Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Diwas Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Buddha R. Shrestha
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marc L. Pusey
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ramazan S. Aygun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ramazan S. Aygun.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Subedi, S., Dinc, I., Tran, T.X. et al. Visual-X2: interactive visualization and analysis tool for protein crystallization. Netw Model Anal Health Inform Bioinforma 9, 15 (2020). https://doi.org/10.1007/s13721-020-0220-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13721-020-0220-6

Keywords

Search

Navigation