Intravenous glucose tolerance test metabolic P system implemented using unified combinative technique


Metabolic P (MP) systems are a part of the infobiotics research field. The intravenous glucose tolerance test (IVGTT) MP system models glucose-insulin interactions. MP system implementation in software is well researched, although there is a lack of techniques for hardware implementation, specifically with field programmable gate arrays. In this article the existing techniques are examined first, including combinative, single digital signal processor element, and pipelined. Then the specifics of six different IVGTT MP systems are analyzed. Having in mind these specifics, a new unified combinative IVGTT MP system implementation in field programmable gate arrays is proposed. Carried out experimental investigation results confirm, that the proposed unified system in comparison with single IVGTT MP systems, uses 36% less digital signal processor and 49% less look-up table resources of the field programmable gate arrays.

Article in Lithuanian.

Intraveninio gliukozės tolerancijos testo metabolinės P sistemos įgyvendinimas apibendrintuoju kombinaciniu būdu

Santrauka. Metabolinė P (MP) sistema yra naujos infobiotikos mokslo srities dalis. Intraveninio gliukozės tolerancijos testo (IVGTT) MP sistema modeliuojama gliukozės ir insulino sąveika. MP sistemų įgyvendinimas programinėmis priemonėmis yra gerai ištirtas, tačiau trūksta MP sistemoms įgyvendinti aparatinėje įrangoje, konkrečiai – lauku programuojamose loginėse matricose (LPLM), skirtų metodų. Šiame straipsnyje iš pradžių aptariami taikytini žinomi įgyvendinimo būdai: kombinacinis, vieno skaitmeninio signalų apdorojimo elemento ir srautinis. Vėliau nagrinėjamos šešios skirtingos IVGTT MP sistemos ir nustatomi jų ypatumai. Atsižvelgiant į bendras IVGTT MP sistemų savybes, pasiūlomas naujas apibendrintas kombinacinis IVGTT MP sistemų įgyvendinimo būdas, kuris sujungia visas minėtas sistemas vienoje LPLM. Palyginus apibendrintą sistemą su atskiromis IVGTT MP sistemomis, nustatyta, kad apibendrinta sistema naudoja 36 % mažiau skaitmeninių signalų apdorojimo elementų ir 49 % mažiau peržvalgos lentelių visoms šešioms žinomoms IVGTT MP sistemoms apskaičiuoti.

Reikšminiai žodžiai: lauku programuojama loginė matrica, metabolinė P sistema, infobiotika, intraveninis gliukozės tolerancijos testas, lygiagretieji skaičiavimai, fiksuoto kablelio aritmetika.

Keyword : field programmable gate array, metabolic P system, infobiotics, intravenous glucose tolerance test, parallel computation, fixed point arithmetic

How to Cite
Kulakovskis, D. (2019). Intravenous glucose tolerance test metabolic P system implemented using unified combinative technique. Mokslas – Lietuvos Ateitis / Science – Future of Lithuania, 11.
Published in Issue
Apr 15, 2019
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Bao, B., Mitrea, C., Wijesinghe, P., Marchetti, L., Girsch, E., Farr, R. L., Boerner, J. L., Mohammad, R., Dyson, G., Terlecky, S. R., & Bollig-Fischer, A. (2017). Treating triple negative breast cancer cells with erlotinib plus a select antioxidant overcomes drug resistance by targeting cancer cell heterogeneity. Scientific Reports, 7, 44125.

Bianco, L., Manca, V., Marchetti, L., & Petterlini, M. (2007). Psim: a Simulator for Biomolecular Dynamics Based on P Systems. IEEE Congress on Evolutionary Computation. CEC 2007, Singapore (pp. 883-887).

Bollig-Fischer, A., Marchetti, L., Mitrea, C., Wu, J., Kruger, A., Manca, V., & Draghici, S. (2014). Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion. Bioinformatics, 30(21), 3036-3043.

Byrne, M. (2016). Intel Bets $16.7 Billion on the massively parallel future of computing. Retrieved from

Castellini, A., & Manca, V. (2009). MetaPlab: a Computational Framework for Metabolic P Systems. Membrane Computing. Springer Berlin Heidelberg (pp. 157-168).

Guiraldelli, R. H. G., & Manca, V. (2015). Automatic translation of MP+V systems to register machines. International Conference on Membrane Computing (pp. 185-199). Valencia, Spain.

Kulakovskis, D., Sledevic, T., Gedminas, A., & Navakauskas, D. (2016). Alternative implementations of metabolic P system in FPGA. 2016 IEEE 4th workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), Vilnius (pp. 1-5).

Kulakovskis, D., & Navakauskas, D. (2016). Automated metabolic P system placement in FPGA. Electrical Control and Communication engineering, 10(1), 5-12.

Mametjanov, A., Balaprakash, P., Choudary, C., Hovland, P. D., Wild, S. M., & Sabin, G. (2015). Autotuning FPGA design parameters for performance and power. 2015 IEEE 23rd Annual International Symposium on Field-Programmable Custom Computing Machines, Vancouver, Canada (pp. 84-91).

Manca, V. (2013). Infobiotics: information in biotic systems. Springer.

Manca, V., Marchetti, L., & Pagliarini, R. (2011). MP modeling of glucose-insulin interactions in the intravenous glucose tolerance test. International Journal of Natural Computing Research (IJNCR), 2(3), 13-24.

Paun, G., Rozenberg, G., & Salomaa, A. (2010). The Oxford handbook of membrane computing. Oxford University Press, Inc.

Siddique, N., & Adeli, H. (2015). Nature inspired computing: An overview and some future directions. Cognitive Computation, 7(6), 706-714.

Sledevič, T., & Navakauskas, D. (2015). Towards optimal FPGA implementation of lattice-ladder neuron and its training circuit. 2015 IEEE 3rd workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), Riga, Latvia (pp. 1-4).

Trimberger, S. M. (2018). Three ages of FPGAs: A retrospective on the first thirty years of FPGA technology. IEEE Solid-State Circuits Magazine, 10(2), 16-29.

Xilinx. (2014). 7 Series FPGA DSP48E1 slice, user guide. Retrieved from