Journal Publications

Peer-reviewed Archival Conference Papers

A Singh and P Bokes. Consequences of mRNA transport on stochastic variability in protein levels. Biophysical Journal, 103, 1087-1096, 2012.

RD Dar, B Razooky, A Singh, T Trimeloni, J McCollum, CD Cox, LS Weinberger and ML Simpson. Transcriptional burst frequency and burst size are equally modulated across the human genome. Proceedings of the National Academy of Sciences, 109, 17454 -17459, 2012.

A Singh. Negative feedback through mRNA provides the best control of gene-expression noise. IEEE Transactions on NanoBiosciences, 11, 194-200, 2011.

K Franz, A Singh  and LS Weinberger. Studying noise in gene expression using HIV based lentiviral vectors. Methods in Enzymology, 497, 603-622,  2011.

A Singh  and JP Hespanha. Approximate moment dynamics for chemically reacting systems. IEEE Transactions on Automatic Control, 56, 414-418, 2011.

A Singh  and JP Hespanha. Stochastic hybrid systems for studying biochemical processes. Philosophical Transactions A of the Royal Society, 368, 4995-5011, 2010.

A Singh, B Razooky, CD Cox, ML Simpson and LS Weinberger. Transcriptional bursting in HIV-1 promoter creates high variability in proteins levels.  Biophysical Journal, 98, L32-L34, 2010.

A Singh  and JP Hespanha. Evolution of gene auto-regulation in the presence of noise. IET Systems Biology, 3, 368-378, 2009.

A Singh  and LS Weinberger. Noise in viral gene expression as a molecular switch for viral latency. Current Opinion in Microbiology, 12, 460-466, 2009.

A Singh, WW Murdoch and RM Nisbet. Skewed attacks, stability and host suppression. Ecology, 90, 1679-1686, 2009.

A Singh and JP Hespanha. Optimal feedback strength for noise suppression in auto-regulatory gene networks. Biophysical Journal, 96, 4013-4023, 2009.

A Singh and RM Nisbet. Variation in risk in single-species models. Mathematical Bioscience and Engineering, 5, 859-875, 2008.

A Singh and JP Hespanha. A derivative-matching approach to moment closure for the stochastic logistic model.  Bulletin of Math Biology, 69, 1909-1925, 2007.

A Singh and RM Nisbet. Semi-discrete host-parasitoid models.  Journal of Theoretical Biology, 247, 733-742, 2007.

JP Hespanha and A Singh. Stochastic models for chemically reacting systems using polynomial stochastic hybrid systems.  Int. Journal of Robust and Nonlinear Control, 15, 669-689, 2005.

A Singh  and H. K. Khalil. Regulation of nonlinear systems using conditional integrators. International Journal of Robust and Nonlinear Control, 15, 339-362, 2005.

A Singh , R Mukherjee, K Turner and S Shaw. MEMS implementation of axial and follower end forces. Journal of Sound and Vibration, 286, 637–644, 2005.

A Singh, C Vargas-Garcia and R Karmakar. Stochastic analysis and inference of a two-state genetic promoter model . American Control Conference, Washington, DC, 2013.

A Singh. Quantifying stochasticity in gene-expression models with extrinsic parameter fluctuations. IEEE Conference on Decision and Control, Maui, HI,  2012.

A Singh. Stochastic analysis of genetic feedback circuit controlling cell-fate decision in HIV. IEEE Conference on Decision and Control, Maui, HI,  2012.

A Singh. Genetic negative feedback circuits for filtering stochasticity in gene expression. IEEE Conference on Decision and Control, Orlando, FL, 2011.

A Singh and JP Hespanha. Reducing noise through translational control in an auto-regulatory gene network. American Control Conference, St. Louis, MO, 2009.

A Singh and JP Hespanha. Noise suppression in auto-regulatory gene networks. 47th IEEE Conference on Decision and Control, Cancun, Mexico, 2008.

A Singh and JP Hespanha. Scaling of stochasticity in gene cascades. American Control Conference, Seattle, WA, 2008.

A Singh and JP Hespanha. Stochastic analysis of gene regulatory networks using moment closure. American Control Conference, New York, NY, 2007.

A Singh and JP Hespanha. Moment closure techniques for stochastic models in population biology. American Control Conference, Minneapolis, MN, 2006.

A Singh and JP Hespanha. Lognormal moment closures for bio-chemical reactions. 45th

IEEE Conference on Decision and Control, San Diego, CA, 2006.

A Singh and JP Hespanha. Models for multi-specie chemical reactions using polynomial stochastic hybrid systems. 44th IEEE Conference on Decision and Control, Spain, 2005.

A Singh and JP Hespanha. Modeling chemical reactions with single reactant specie. In Proc. of the Workshop on Modeling and Control of Complex Systems, Cyprus, 2005.

A Singh and HK Khalil. State feedback regulation of nonlinear systems using conditional integrators. 43rd IEEE Conference on Decision and Control, Bahamas, 2004.

A Singh and JP Hespanha. Stochastic modeling of biochemical reactions. 25th Army Science Conference, Orlando, FL, 2006.

A Singh, B Razooky, RD Dar and LS Weinberger. Dynamics of protein noise can distinguish between alternate sources of gene-expression variability. Nature: Molecular Systems Biology, 8, 607, 2012.

Thesis, Book Chapters and Technical Reports

A Singh. Regulation of nonlinear systems using conditional integrators. MS Thesis in Electrical and Computer Engineering, Michigan State University, 2004.

A Singh. Modeling host-parasitoid dynamics. MA Thesis in Ecology, Evolution and Marine Biology, University of California, Santa Barbara, 2007.

A Singh. Stochastic modeling of chemical reactions and gene regulatory networks. Ph.D. Thesis in Electrical and Computer Engineering, University of California, Santa Barbara, 2008.

A Singh, C Vargas-Garcia and R Karmakar. Stochastic analysis of genetic promoter architectures with memory. IEEE Conference on Decision and Control, Florence, Italy, 2013.

C Vargas-Garcia, R Zurakowski and A Singh. Conditions for invasion of synapse-forming HIV variants. IEEE Conference on Decision and Control, Florence, Italy, 2013.

D Antunes and A Singh. Computing mRNA and protein statistical moments for a renewal model of stochastic gene-expression. IEEE Conference on Decision and Control, Florence, Italy, 2013.

A Singh and J Dennehy. Stochastic holin expression can account for lysis time variation in the bacteriophage lambda. Journal of the Royal Society Interface, 11, 20140140, 2014.

Z Fox and A Singh. Stochastic analysis of protein-mediated and microRNA-mediated feedback circuits in HIV. IFAC World Congress, Cape Town, South Africa, 2014.

C Vargas-Garcia, L Cannon, A Singh and R Zurakowski. Optimal multi-drug approaches for reduction of the latent pool in HIV. IFAC World Congress, Cape Town, South Africa, 2014.

K Ghusinga and A Singh. Optimal first passage time in gene regulatory networks. IEEE Conference on Decision and Control, Los Angeles, CA, 2014.

D Antunes and A Singh. Quantifying gene expression variability arising from randomness in cell division times. Journal of Mathematical Biology, 2014. Online publication ahead of print.

B Daigle, M Soltani, L Petzold and A Singh. Inferring single-cell gene expression mechanisms using stochastic simulation. Bioinformatics, 31, 1428-1435, 2015.

M Soltani N. Kumar, R. Kulkarni and A Singh. Moment Closure Approximations in Genetic Negative Feedback Circuits. American Control Conference, Chicago, IL, 2015.

K Ghusinga, PW Fok and A Singh. Optimal feedback regulation for minimizing first-passage time variability in protein level. American Control Conference, Chicago, IL, 2015.

O Padovan-Merhar, G Nair, A Biaesch, A Mayer, S Scarfone, S Foley, A Wu, L Churchman, A Singh and A Raj. Single mammalian cells compensate for differences in cellular volume and DNA copy number through independent global transcriptional mechanisms. Molecular Cell, 58, 339–352, 2015.

SA Agrawal, D Anand, AD Siddam, A Kakrana, S Dash, DA Scheiblin, CA Dang, AM Terrell, SM Waters, A Singh, H Motohashi, M Yamamoto, SA Lachke. Compound mouse mutants of bZIP transcription factors Mafg and Mafk reveal a regulatory network of non-crystallin genes associated with cataract. Human Genetics, 134, 717-735, 2015.

M Soltani, C Vargas-Garcia and A Singh. Conditional moment closure schemes for studying stochastic dynamics of genetic circuits. IEEE Trans. on Biomedical Systems and Circuits, 9, 518-526, 2015.

M Soltani, P Bokes, Z Fox and A Singh. Nonspecific transcription factor binding reduces variability in target protein expression for linear dose-response. Physical Biology, 12, 055002, 2015.

N. Kumar, A Singh and R. Kulkarni. Transcriptional bursting in gene expression: analytical results for general stochastic models. PLoS Computational Biology, 11, e1004292, 2015.

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A Borri, P Palumbo and and A Singh. Metabolic noise reduction for enzymatic reactions: the role of a negative feedback. IEEE Conference on Decision and Control, Osaka, Japan  2015.

K Ghusinga and A Singh. First-passage time for a stochastic gene expression model. IEEE Conference on Decision and Control, Osaka, Japan  2015.

P Kulkarni, N Rangarajan, Z Fox, A Singh and G Rangarajan. Disorder, oscillatory dynamics and state switching: the role of c-Myc. Journal of Theoretical Biology, 386, 105–114, 2015.

Please see my Google Scholar homepage for an updated list of publications

M Soltani and A Singh. Stochastic analysis of time-triggered linear stochastic hybrid systems. Technical Report, University of Delaware, 2016.

CA Vargas-Garcia, M Soltani and A Singh. Conditions for cell size homeostasis: A stochastic hybrid systems approach. IEEE Life Science Letters, 2, 47–50, 2016.

M Soltani and A Singh. Effects of cell-cycle-dependent expression on random fluctuations in protein levels. Royal Society Open Science, 3, 2016.

P Bokes and A Singh. Gene expression noise is affected differentially by feedback in burst frequency and burst size. Journal of Mathematical Biology, 74, 1483–1509, 2017.

K Ghusinga, JJ Dennehy and A Singh. First-passage time approach to controlling noise in the timing of intracellular events. Proceedings of the National Academy of Sciences, 114, 693–698, 2017.

A Borri, P Palumbo and A Singh. The impact of negative feedback in metabolic noise propagation. IET Systems Biology, 2016. DOI: 10.1049/iet-syb.2016.0003.

R Dar, S Schaffer, A Singh, B Razooky, M Simpson, A Raj and LS Weinberger. Transcriptional bursting explains the noise-versus-mean relationship in mRNA and protein levels. PLOS One, 11, e0158298, 2016

M Soltani and CA Vargas-Garcia, D Antunes and A Singh. Intercellular variability in protein levels from stochastic expression and noisy cell cycle processes. PLOS Computational Biology, 12, e1004972, 2016.

CA Vargas-Garcia, K Ghusinga and A Singh. A mechanistic stochastic framework for regulating bacterial cell division. Nature: Scientific Reports, 6, 30229, 2016.

B Emerick and A Singh. Host-feeding enhances stability of discrete-time host-parasitoid population dynamic models. Mathematical Bioscience, 272, 54--63, 2016.

M Soltani, T Platini and A Singh. Stochastic analysis of an incoherent feedforward genetic motif. American Control Conference, Boston, MA, 2016.

K Ghusinga and A Singh. Optimal regulation of protein degradation to schedule cellular events with precision. American Control Conference, Boston, MA, 2016.

J Conway, JJ Dennehy and A Singh. Optimizing phage lambda survival in a changing environment: stochastic model predictions. IEEE Conference on Decision and Control, Las Vegas, NV, 2016.

M Soltani and A Singh. Moment dynamics for a class of time-triggered stochastic hybrid systems. IEEE Conference on Decision and Control, Las Vegas, NV, 2016.

A Lamperski, K Ghusinga and A Singh. Stochastic optimal control using semidefinite programming for moment dynamics. IEEE Conference on Decision and Control, Las Vegas, NV, 2016.

CA Vargas-Garcia and A Singh. Hybrid systems approach to modeling stochastic dynamics of cell size. IEEE Conference on Decision and Control, Las Vegas, NV, 2016.

A Borri, P Palumbo and A Singh. Noise reduction for enzymatic reactions: a case study for stochastic product clearance. IEEE Conference on Decision and Control, Las Vegas, NV, 2016.

E Sontag and A Singh. Exact moment dynamics for feedforward nonlinear chemical reaction networks. IEEE Life Sciences Letters, 1, 26--29, 2015.

K Ghusinga, CA Vargas-Garcia, A Lamperski and A Singh. Exact lower and upper bounds on stationary moments in stochastic biochemical systems. Physical Biology, 2017.

M Soltani and A Singh. Moment-based analysis of stochastic hybrid systems with renewal transitions. Automatica, 84, 62-69, 2017.

A Kakrana, A Yang, D Anand, D Djordjevic, D Ramachandruni, A Singh, H Huang, J Ho and  SA Lachke. iSyTE 2.0: A database for expression-based gene discovery in the eye. Nucleic Acid Research, 2017.

S Modi, CA Vargas-Garcia, K Ghusinga and A Singh. Analysis of noise mechanisms in cell size control. Biophysical Journal, 112, 2408-2418, 2017.

M Soltani and A Singh. Stochastic analysis of linear time-invariant systems with renewal  transitions. American Control Conference, Seattle, WA, 2017.

K Ghusinga and A Singh. Effect of gene-expression bursts on stochastic timing of cellular events. American Control Conference, Seattle, WA, 2017.

CA Vargas-Garcia, C Agemabiese and A Singh. Optimal adsorption rate: Implications of  the shielding effect. American Control Conference, Seattle, WA, 2017.

A Singh and R Grima. Quantitative Biology: Theory, Computational Methods and Examples of Models. Editors: Bill Hlavacek, Brian Munsky and Lev Tsimring, MIT Press, 2017.

X Chen, M Ogura, K Ghusinga, A Singh and VM Preciado. Semidefinite bounds for moment dynamics: Application to epidemics on networks. IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

A Singh. Modeling noise mechanisms in neuronal synaptic transmission. IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

K Ghusinga, M Soltani, A Lamperski, S Dhople and A Singh. Approximate moment dynamics for polynomial and trigonometric stochastic systems. IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

J Blotnick, CA Vargas-Garcia, JJ Dennehy, R Zurakowski and A Singh. The effect of multiplicity of infection on the temperateness of a bacteriophage: Implications for viral fitness. IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

A Borri, P Palumbo and A Singh. Noise propagation in a class of metabolic networks. IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

S Shaffer, M Dunagin, S Torborg, E Torre, B Emert, C Krepler, M Beqiri, K Sproesser, P Brafford, M Xiao, E Eggan, I Anastopoulos, K Nathanson, CA Vargas-Garcia, A Singh, M Herlyn, A Raj. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature, 546, 431 - 435, 2017

A Mena, DA. Medina, J Garcia-Martinez, V Begley, A Singh, S Chavez, MC Munoz-Centeno and JE Perez-Ortin. Asymmetric cell division requires specific mechanisms for adjusting global transcription. Nucleic Acid Research, 2017.

C Vargas-Garcia. Cell size homeostasis and optimal viral strategies for host exploitation. Ph.D. Thesis in Electrical and Computer Engineering, University of Delaware, 2018.

A Singh. A mechanistic approach to tuning MEMS resonators. MS Thesis in Mechanical Engineering, Michigan State University, 2006.