Biology subjects

Singh, R. K. B.

Publications and source records attributed to Singh, R. K. B..

4 recordsLinked to original sources

bioRxiv2019

Identification of key regulators in Prostate cancer from gene expression datasets of patients

Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k[≥]65) were selected from the PCa network, traced, and 19 of them were identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism.

systems biology↗

bioRxiv2019

Interplay of cellular states: Role of delay as control mechanism

Delay is everywhere, no matter how small or big it is. Experimental evidences show the existence and importance of time delayed reactions specially in biological systems. The role of delay is found to be multifunctional and is seemed to be system dependent. The analytically solved P(X, t) of gene regulatory process shows universal class of Poisson process at stationary condition. However, time delay creates a possible condition to the system to impart correlation in the stochastic process as sub-Poissonian or noise enhancement process which could be important in regulating and controlling the system. The results of simulation of few biological systems (gene regulation, circadian rhythm, and repressilator) using delay stochastic simulation algorithm show the possibilities of delay induced onset of oscillating states, which could be the active states of the systems, where, the system can establish coherence among the system variables, enhance the signal processing, optimize the system activities, etc. On the other hand, delay can also induce switching off of the oscillating states, which may correspond to inactive state or system failure. Further, delay can also create coherent bistable states of the system variables, at which the system can stay longer to make decisions about the fate of the system.

systems biology↗

bioRxiv2019

Emergence of Functional Cortical Patterns of neurons characterize the self-organizing way to cognition in brain.

Synaptic plasticity and neuron cross-talk are some of the important key mechanisms underlying formation of dynamic clusters of active neurons. In our proposed neuron activity pattern model assorted range of coupled interactions generated the ordered pattern dynamics, mimicking the functional clusters of neuronal activity. The temporal correlates of neurons at near critical synaptic strength features emergence of functional cortical patterns (FCPs) symbolizing task-specific neuronal activation. We investigated the near critical dynamics of long, critical and short-ranged interactions and lead to interpretation that criticality is a range and not just a point. Our model has deciphered the mechanism of emergence of a complex functional brain network. The range of interaction among neurons play an important role in defining the functional severity of the neuronal circuitry. We have found that the coupling range as a function of synaptic strength could make connections in an augmenting fashion from short to long range, as the synaptic strength increases in the population of neurons. Thus, could give insight towards the intensity of cognitive behaviour, as a symbol of multiple stimulus attempts.

neuroscience↗

bioRxiv2019

Organization in complex brain networks: energy distributions and phase shift

The Hamiltonian function of a network, derived from the intrinsic distributions of nodes and edges, magnified by resolution parameter has information on the distribution of energy in the network. In brain networks, the Hamiltonian function follows hierarchical features reflecting a power-law behavior which can be a signature of self-organization. Further, the transition of three distinct phases driven by resolution parameter is observed which could correspond to various important brain states. This resolution parameter could thus reflect a key parameter that controls and balances the energy distribution in the brain network.

neuroscience↗