Modeling the mechanism pathways of first line drug in Tuberculosis using Petri nets

• Achieng RL (2016) Factors associated with tuberculosis treatment outcomes in TB-HIV co-infected and TB only patients in Nyando sub-county (Doctoral dissertation (JOOUST)). Jaramogi Oginga Odinga

• Babu GR, Laxminarayan R (2012) The unsurprising story of MDR-TB resistance in India. Tuberculosis 92(4):301–306

  Google Scholar 

• Behinaein B, Rudie K, Sangrar W (2018) Petri net siphon analysis and graph theoretic measures for identifying combination therapies in cancer. IEEE/ACM Trans Comput Biol Bioinform (TCBB) 15(1):231–243

  Google Scholar 

• Brauer W, Reisig W (2009) Carl Adam Petri and Petri nets. Fundam Concepts Comput Sci 3(5):129–139

  Google Scholar 

• Castillo-Chavez C, Song B (2004) Dynamical models of tuberculosis and their applications. Math Biosci Eng 1(2):361–404

  MathSciNet  MATH  Google Scholar 

• Centers for Disease Control and Prevention (CDC) (2006) Emergence of Mycobacterium tuberculosis with extensive resistance to second-line drugs-worldwide, 2000–2004. MMWR 55(11):301

  Google Scholar 

• Cherdal S, Mouline S (2018) Modelling and simulation of biochemical processes using Petri nets. Processes 6(8):97

  Google Scholar 

• Deshmukh RD, Dhande DJ, Sachdeva KS, Sreenivas A, Kumar AMV, Satyanarayana S, Lo TQ (2015) Patient and provider reported reasons for lost to follow up in MDRTB treatment: a qualitative study from a drug resistant TB centre in India. PLoS ONE 10(8):e0135802

  Google Scholar 

• Dewan R, Anuradha S, Khanna A, Garg S, Singla S, Ish P, Agarwal S (2015) Role of cartridge-based nucleic acid amplification test (CBNAAT) for early diagnosis of pulmonary tuberculosis in HIV. J Indian Acad Clin Med 16:114–7

  Google Scholar 

• Dingle NJ, Knottenbelt WJ, Suto T (2009) PIPE2: a tool for the performance evaluation of generalised stochastic Petri Nets. ACM SIGMETRICS Perform Eval Rev 36(4):34–39

  Google Scholar 

• Eckleder A, Freytag T (2008) WoPeD 2.0 goes BPEL 2.0. AWPN 380:75–80

  Google Scholar 

• Ferrara G, Losi M, D’Amico R, Roversi P, Piro R, Meacci M, Mussini C (2006) Use in routine clinical practice of two commercial blood tests for diagnosis of infection with Mycobacterium tuberculosis: a prospective study. The Lancet 367(9519):1328–1334

  Google Scholar 

• Finkel A (1991) The minimal coverability graph for Petri nets. In: International conference on application and theory of Petri nets. Springer, Berlin, pp 210–243

• Gammack D, Ganguli S, Marino S, Segovia-Juarez J, Kirschner DE (2005) Understanding the immune response in tuberculosis using different mathematical models and biological scales. Multiscale Model Simul 3(2):312–345

  MathSciNet  Google Scholar 

• Gilbert D, Heiner M, Ghanbar L, Chodak J (2019) Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking. BMC Bioinform 20(4):173

  Google Scholar 

• Gilpin C, Korobitsyn A, Migliori GB, Raviglione MC, Weyer K (2018) The World Health Organization standards for tuberculosis care and management. Eur Respir J. https://doi.org/10.1183/13993003.00098-2018

  Article  Google Scholar 

• Goldman RC, Plumley KV, Laughon BE (2007) The evolution of extensively drug resistant tuberculosis (XDR-TB): history, status and issues for global control. Infect Disord Drug Targets 7(2):73–91

  Google Scholar 

• Gupta S, Singh GP, Kumawat S (2019) Petri net recommender system to model metabolic pathway of polyhydroxyalkanoates. Int J Knowl Syst Sci (IJKSS) 10(2):42–59

  Google Scholar 

• He GX, van den Hof S, Borgdorff MW, van der Werf MJ, Cheng SM, Hu YL, Wang LX (2010a) Availability of second-line drugs and anti-tuberculosis drug susceptibility testing in China: a situational analysis. Int J Tuberc Lung Dis 14(7):884–889

  Google Scholar 

• He GX, Xie YG, Wang LX, Borgdorff MW, Van Der Werf MJ, Fan JH et al (2010b) Follow-up of patients with multidrug resistant tuberculosis four years after standardized first-line drug treatment. PLoS ONE 5(5):e10799

  Google Scholar 

• Herajy M, Liu F, Heiner M (2018a) Efficient modelling of yeast cell cycles based on multisite phosphorylation using coloured hybrid Petri nets with marking-dependent arc weights. Nonlinear Anal Hybrid Syst 27:191–212

  MathSciNet  MATH  Google Scholar 

• Herajy M, Liu F, Rohr C, Heiner M (2018b) Coloured Hybrid Petri Nets: an adaptable modelling approach for multi-scale biological networks. Comput Biol Chem 76:87–100

  Google Scholar 

• Jensen K (1983) High-level Petri nets. In: Applications and theory of Petri nets. Springer, Berlin, pp 166–180

• Jensen K, Rozenberg G (2012) High-level Petri nets: theory and application. Springer, New York

  MATH  Google Scholar 

• Jung J, Kwon M, Bae S, Yim S, Lee D (2018) Petri net-based prediction of therapeutic targets that recover abnormally phosphorylated proteins in muscle atrophy. BMC Syst Biol 12(1):26

  Google Scholar 

• Kansal S, Singh GP, Acharya M (2010) On Petri nets generating all the binary n-vectors. Scientiae Mathematicae Japonicae 71(2):209–221

  MathSciNet  MATH  Google Scholar 

• Kansal S, Acharya M, Singh GP (2012) Boolean Petri nets. Petri nets-manufacturing and Computer Science. IntechOpen, London, pp 381–406

  Google Scholar 

• Kleinnijenhuis J, Oosting M, Joosten LA, Netea MG, Van Crevel R (2011) Innate immune recognition of Mycobacterium tuberculosis. Clin Dev Immunol 2011:405310–405312

  Google Scholar 

• Knechel NA (2009) Tuberculosis: pathophysiology, clinical features, and diagnosis. Crit Care Nurse 29(2):34–43

  Google Scholar 

• Kolyva AS, Karakousis PC (2012) Old and new TB drugs: mechanisms of action and resistance. In: Understanding tuberculosis-new approaches to fighting against drug resistance, InTechOpen, London, pp 209–231

• Leung KL, Yip CW, Yeung YL, Wong KL, Chan WY, Chan MY, Kam KM (2010) Usefulness of resistant gene markers for predicting treatment outcome on second-line anti-tuberculosis drugs. J Appl Microbiol 109(6):2087–2094

  Google Scholar 

• Liu F, Heiner M, Gilbert D (2018) Fuzzy Petri nets for modelling of uncertain biological systems. Brief Bioinform 00:1–13

  Google Scholar 

• Manosuthi W, Chottanapand S, Thongyen S, Chaovavanich A, Sungkanuparph S (2006) Survival rate and risk factors of mortality among HIV/tuberculosis-coinfected patients with and without antiretroviral therapy. JAIDS 43(1):42–46

  Google Scholar 

• Murata T (1989) Petri nets: properties, analysis and applications. Proc IEEE 77(4):541–580

  Google Scholar 

• Olszak J, Radom M, Formanowicz P (2018) Some aspects of modeling and analysis of complex biological systems using time Petri nets. Bull Pol Acad Sci Techn Sci 66(1):67–78

  Google Scholar 

• Palomino J, Martin A (2014) Drug resistance mechanisms in Mycobacterium tuberculosis. Antibiotics 3(3):317–340

  Google Scholar 

• Pang Y, Lu J, Wang Y, Song Y, Wang S, Zhao Y (2013) Study of the rifampin monoresistance mechanism in Mycobacterium tuberculosis. Antimicrob Agents Chemother 57(2):893–900

  Google Scholar 

• Peterson JL (1977) Petri nets. ACM Comput Surv (CSUR) 9(3):223–252

  MATH  Google Scholar 

• Rovetto C, Cano E, Ojo K, Tuñon M, Montes H (2018) Coloured Petri net model for remote monitoring of cardiovascular dysfunction. Memorias de Congresos UTP 405–411

• Russo G, Pennisi M, Boscarino R, Pappalardo F (2018) Continuous Petri Nets and microRNA analysis in melanoma. IEEE/ACM Trans Comput Biol Bioinform (TCBB) 15(5):1492–1499

  Google Scholar 

• Shi W, Chen J, Feng J, Cui P, Zhang S, Weng X, Zhang Y (2014) Aspartate decarboxylase (PanD) as a new target of pyrazinamide in Mycobacterium tuberculosis. Emerg Microbes Infect 3(1):1–8

  Google Scholar 

• Singh GP (2013) Some advances in the theory of Petri Nets. Ph.D. thesis, Delhi College of Engineering, Faculty of Technology, University of Delhi, Delhi

• Singh GP (2016) Applications of Petri nets in electrical, electronics and optimizations. In: International conference on electrical, electronics, and optimization techniques (ICEEOT) IEEE, 2180-2184

• Singh GP, Gupta A (2019) A Petri net analysis to study the effects of diabetes on cardiovascular diseases. IEEE Xplore, ISBN: 978-93-80544-36-6.(accepted)

• Singh GP, Kansal S (2016) Basic results on crisp Boolean Petri Nets. In: Modern mathematical methods and high performance computing in science and technology, Springer, Singapore, pp 83–88

• Singh GP, Singh SK (2019) Petri net recommender system for generating of perfect binary tree. Int J Knowl Syst Sci (IJKSS) 10(2):1–12

  Google Scholar 

• Singh GP, Kansal S, Acharya M (2013a) Construction of a crisp Boolean Petri net from a 1-safe Petri net. Int J Comput Appl 73(17):1–4

  Google Scholar 

• Singh GP, Kansal S, Acharya M (2013b) Embedding an Arbitrary 1-safe Petri net into a Boolean Petri Net. Int J Comput Appl 70(6):7–9

  Google Scholar 

• Stanley SA, Raghavan S, Hwang WW, Cox JS (2003) Acute infection and macrophage subversion by Mycobacterium tuberculosis require a specialized secretion system. Proc Nat Acad Sci 100(22):13001–13006

  Google Scholar 

• Telenti A, Philipp WJ, Sreevatsan S, Bernasconi C, Stockbauer KE, Wieles B, Jacobs WR (1997) The emb operon, a gene cluster of Mycobacterium tuberculosis involved in resistance to ethambutol. Nat Med 3(5):567

  Google Scholar 

• Timmins GS, Deretic V (2006) Mechanisms of action of isoniazid. Mol Microbiol 62(5):1220–1227

  Google Scholar 

• van der Heijden YF, Karim F, Mufamadi G, Zako L, Chinappa T, Shepherd BE, Pym AS (2017) Isoniazid-monoresistant tuberculosis is associated with poor treatment outcomes in Durban, South Africa. Int J Tuberc Lung Dis 21(6):670–676

  Google Scholar 

• Vashishtha VM (2009) WHO Global Tuberculosis Control Report 2009: tuberculosis elimination is a distant dream. Indian Pediatr 46(5):401–402

  Google Scholar 

• Wehrli W (1983) Rifampin: mechanisms of action and resistance. Rev Infect Dis 5(Supplement–3):S407–S411

  Google Scholar 

• Weyer K, Mirzayev F, Migliori GB, Van Gemert W, D’Ambrosio L, Zignol M, Gilpin C (2013) Rapid molecular TB diagnosis: evidence, policy making and global implementation of XpertMTB/RIF. Eur Respir J 42(1):252–271

  Google Scholar 

• World Health Organization & Stop TB Initiative (World Health Organization) (2010) Treatment of tuberculosis: guidelines. World Health Organization, Geneva

  Google Scholar 

• Young F, Critchley JA, Johnstone LK, Unwin NC (2009) A review of co-morbidity between infectious and chronic disease in Sub Saharan Africa: TB and diabetes mellitus, HIV and metabolic syndrome, and the impact of globalization. Glob Health 5(9):1–9

  Google Scholar 

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