Regulatory network discovery using heuristics
- Authors: Zarnegar, Armita
- Date: 2011
- Type: Text , Thesis , PhD
- Full Text:
- Description: This thesis improves the GRN discovery process by integrating heuristic information via a co-regulation function, a post-processing procedure, and a Hub Network algorithm to build the backbone of the network.
- Description: Doctor of Philosophy
- Authors: Zarnegar, Armita
- Date: 2011
- Type: Text , Thesis , PhD
- Full Text:
- Description: This thesis improves the GRN discovery process by integrating heuristic information via a co-regulation function, a post-processing procedure, and a Hub Network algorithm to build the backbone of the network.
- Description: Doctor of Philosophy
Reverse engineering genetic networks using nonlinear saturation kinetics
- Youseph, Ahammed, Chetty, Madhu, Karmakar, Gour
- Authors: Youseph, Ahammed , Chetty, Madhu , Karmakar, Gour
- Date: 2019
- Type: Text , Journal article
- Relation: BioSystems Vol. 182, no. (2019), p. 30-41
- Full Text:
- Reviewed:
- Description: A gene regulatory network (GRN) represents a set of genes along with their regulatory interactions. Cellular behavior is driven by genetic level interactions. Dynamics of such systems show nonlinear saturation kinetics which can be best modeled by Michaelis-Menten (MM) and Hill equations. Although MM equation is being widely used for modeling biochemical processes, it has been applied rarely for reverse engineering GRNs. In this paper, we develop a complete framework for a novel model for GRN inference using MM kinetics. A set of coupled equations is first proposed for modeling GRNs. In the coupled model, Michaelis-Menten constant associated with regulation by a gene is made invariant irrespective of the gene being regulated. The parameter estimation of the proposed model is carried out using an evolutionary optimization method, namely, trigonometric differential evolution (TDE). Subsequently, the model is further improved and the regulations of different genes by a given gene are made distinct by allowing varying values of Michaelis-Menten constants for each regulation. Apart from making the model more relevant biologically, the improvement results in a decoupled GRN model with fast estimation of model parameters. Further, to enhance exploitation of the search, we propose a local search algorithm based on hill climbing heuristics. A novel mutation operation is also proposed to avoid population stagnation and premature convergence. Real life benchmark data sets generated in vivo are used for validating the proposed model. Further, we also analyze realistic in silico datasets generated using GeneNetweaver. The comparison of the performance of proposed model with other existing methods shows the potential of the proposed model.
- Authors: Youseph, Ahammed , Chetty, Madhu , Karmakar, Gour
- Date: 2019
- Type: Text , Journal article
- Relation: BioSystems Vol. 182, no. (2019), p. 30-41
- Full Text:
- Reviewed:
- Description: A gene regulatory network (GRN) represents a set of genes along with their regulatory interactions. Cellular behavior is driven by genetic level interactions. Dynamics of such systems show nonlinear saturation kinetics which can be best modeled by Michaelis-Menten (MM) and Hill equations. Although MM equation is being widely used for modeling biochemical processes, it has been applied rarely for reverse engineering GRNs. In this paper, we develop a complete framework for a novel model for GRN inference using MM kinetics. A set of coupled equations is first proposed for modeling GRNs. In the coupled model, Michaelis-Menten constant associated with regulation by a gene is made invariant irrespective of the gene being regulated. The parameter estimation of the proposed model is carried out using an evolutionary optimization method, namely, trigonometric differential evolution (TDE). Subsequently, the model is further improved and the regulations of different genes by a given gene are made distinct by allowing varying values of Michaelis-Menten constants for each regulation. Apart from making the model more relevant biologically, the improvement results in a decoupled GRN model with fast estimation of model parameters. Further, to enhance exploitation of the search, we propose a local search algorithm based on hill climbing heuristics. A novel mutation operation is also proposed to avoid population stagnation and premature convergence. Real life benchmark data sets generated in vivo are used for validating the proposed model. Further, we also analyze realistic in silico datasets generated using GeneNetweaver. The comparison of the performance of proposed model with other existing methods shows the potential of the proposed model.
Delayed self-regulation and time-dependent chemical drive leads to novel states in epigenetic landscapes
- Mitra, Mitra, Taylor, Paul, Hutchison, Chris, McLeish, T. C. B., Chakrabarti, Buddapriya
- Authors: Mitra, Mitra , Taylor, Paul , Hutchison, Chris , McLeish, T. C. B. , Chakrabarti, Buddapriya
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of the Royal Society Interface Vol. 11, no. 100 (2014), p.
- Full Text:
- Reviewed:
- Description: The epigenetic pathway of a cell as it differentiates from a stem cell state to a mature lineage-committed one has been historically understood in terms of Waddington's landscape, consisting of hills and valleys. The smooth top and valley-strewn bottom of the hill represent their undifferentiated and differentiated states, respectively. Although mathematical ideas rooted in nonlinear dynamics and bifurcation theory have been used to quantify this picture, the importance of time delays arising from multistep chemical reactions or cellular shape transformations have been ignored so far.We argue that this feature is crucial in understanding cell differentiation and explore the role of time delay in a model of a single-gene regulatory circuit.We show that the interplay of time-dependent drive and delay introduces a new regime where the system shows sustained oscillations between the two admissible steady states. We interpret these results in the light of recent perplexing experiments on inducing the pluripotent state in mouse somatic cells.We also comment on howsuch an oscillatory state can provide a framework for understanding more general feedback circuits in cell development. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
- Description: The epigenetic pathway of a cell as it differentiates from a stem cell state to a mature lineage-committed one has been historically understood in terms of Waddington's landscape, consisting of hills and valleys. The smooth top and valley-strewn bottom of the hill represent their undifferentiated and differentiated states, respectively. Although mathematical ideas rooted in nonlinear dynamics and bifurcation theory have been used to quantify this picture, the importance of time delays arising from multistep chemical reactions or cellular shape transformations have been ignored so far.We argue that this feature is crucial in understanding cell differentiation and explore the role of time delay in a model of a single-gene regulatory circuit.We showthat the interplay of time-dependent drive and delay introduces a new regime where the system shows sustained oscillations between the two admissible steady states. We interpret these results in the light of recent perplexing experiments on inducing the pluripotent state in mouse somatic cells.We also comment on howsuch an oscillatory state can provide a framework for understanding more general feedback circuits in cell development. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
- Authors: Mitra, Mitra , Taylor, Paul , Hutchison, Chris , McLeish, T. C. B. , Chakrabarti, Buddapriya
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of the Royal Society Interface Vol. 11, no. 100 (2014), p.
- Full Text:
- Reviewed:
- Description: The epigenetic pathway of a cell as it differentiates from a stem cell state to a mature lineage-committed one has been historically understood in terms of Waddington's landscape, consisting of hills and valleys. The smooth top and valley-strewn bottom of the hill represent their undifferentiated and differentiated states, respectively. Although mathematical ideas rooted in nonlinear dynamics and bifurcation theory have been used to quantify this picture, the importance of time delays arising from multistep chemical reactions or cellular shape transformations have been ignored so far.We argue that this feature is crucial in understanding cell differentiation and explore the role of time delay in a model of a single-gene regulatory circuit.We show that the interplay of time-dependent drive and delay introduces a new regime where the system shows sustained oscillations between the two admissible steady states. We interpret these results in the light of recent perplexing experiments on inducing the pluripotent state in mouse somatic cells.We also comment on howsuch an oscillatory state can provide a framework for understanding more general feedback circuits in cell development. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
- Description: The epigenetic pathway of a cell as it differentiates from a stem cell state to a mature lineage-committed one has been historically understood in terms of Waddington's landscape, consisting of hills and valleys. The smooth top and valley-strewn bottom of the hill represent their undifferentiated and differentiated states, respectively. Although mathematical ideas rooted in nonlinear dynamics and bifurcation theory have been used to quantify this picture, the importance of time delays arising from multistep chemical reactions or cellular shape transformations have been ignored so far.We argue that this feature is crucial in understanding cell differentiation and explore the role of time delay in a model of a single-gene regulatory circuit.We showthat the interplay of time-dependent drive and delay introduces a new regime where the system shows sustained oscillations between the two admissible steady states. We interpret these results in the light of recent perplexing experiments on inducing the pluripotent state in mouse somatic cells.We also comment on howsuch an oscillatory state can provide a framework for understanding more general feedback circuits in cell development. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
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