Research Contributions

Research highlights:

*** A quantum network (QN) is a network of entangled states, which can be used for the transmittance of quantum information. Constructing QNs requisites strong entanglement between distant stations to enhance security and efficiency. Real-world noise weakens these links. Combining quantum mechanics with statistical physics, by using percolation theory, can strengthen connections in a network of mostly weak ones. Past methods disconnected intermediate stations. We introduce General Concurrence Percolation, which takes a geometric approach by enhancing entanglement along the shortest paths. It turns a sparse grid into a dense network, decisively mitigating the entanglement threshold needed to connect the entire system.

*** This paper should be of interest to the following communities and disciplines.

Maths / Physics / Computer science (Network science and graph theory): A mathematically rigorous method to compare any two networks (independent of origin, function or kind), with overlapping nodes. This is done by introducing a measure called Shortest Path Alteration Fraction (SPAF), technical details regarding which appear in Theorem 1. SPAF=1 leads us to all shortest paths present in either network but not both.
General biology: This approach immediately presents a fresh and general framework to address mutations from the level of a single protein to an entire organism. In fact, the latter has the potential to deliver systems-level perspectives. We computationally explore phenotypic alterations arising from mutations in five microbes, each from a different taxon. Effects reported in literature are recovered and new predictions made. Differences between a pair of similar networks at any level, including say at the ecological level can be explored by this method.
Microbiology: Phage resistance in mycobacteria is significant in its own right due to the emergence of multidrug resistant strains and the promise of phage therapy. We scrutinise the effectiveness of our procedure through extensive theoretical and experimental tests in such a system. A mutant of Mycobacterium smegmatis mc²155 -- resistant to mycobacteriophage D29 -- is generated and is characterised with significant phenotypic alterations. Whole-genome sequencing identifies mutations, which cannot readily explain the observed phenotypes. We show the utility of SPAF towards mapping the present genotype-phenotype relation.

Popular Coverage at: Research Matters Daily Hunt

Bioinformatics [Oxford] 37 213-220 (2021)

*** Networks with a scale-free degree distribution are widely thought to promote cooperation in various games. We demonstrate that this need not necessarily be true. For the same degree distribution and indeed the very same degree sequence, we present a variety of possible behaviour. We also reevaluate the dependence of cooperation on network clustering and assortativity.

Europhysics Letters, 134 60002 (2021)

*** Experimental validation of predictions from the analyses of Protein Contact Networks or Residue Interaction Graphs is scarce in literature. Our collaborators from Devrani Mitra Lab have directly verified the results predicted earlier by us in Bioinformatics [Oxford] 31 3608-3616 (2015).

Proteins [Wiley], 88, 1660-1674 (2020)

***A Systems Biology approach consisting of an iterative cycle of theoretical techniques (delay differential equations and Monte Carlo simulations), coupled with experiments; which presents new evidence for secondary mechanisms of host lethality in Mycobacteriophage-Mycobacterial host interaction.

Applied and Environmental Microbiology [ASM] 82 124-133 (2016)
Selected as article of significant interest by AEM Editors for Spotlight

*** A fresh, general and simple method of feature extraction (image processing), using networks which can be implemented in form of a smart, fast and portable device. Applications of such a fluctutation based system and method have been demonstrated in non-invasive diagnostics and biometrics.

Scientific Reports (Nature) 5:17271 (2015)

Patent Filing no. IPO 628/KOL/2015

*** A new edge-based metric which demonstrates slow-poisoning in networks and shows how edges and nodes, which are important for infrastructure, biological and other networks, can be identified. Physical Review E 91 022807 (2015)

*** Initiation of a framework towards understanding light-dark transition in photoreceptors. Our approach of introducing differential networks and identifying important residues: (1) minimises extensive photo-cycle kinetics procedures, and, (2) is helpful in providing first-hand information on the fundamentals of photo-adaptation and rational design of photoreceptors in synthetic biology inspired structural optogenetics

Bioinformatics [Oxford] 31 3608-3616 (2015)

Postdoctoral work:

*** The first work in complex network literature outlining how and why multiple metrics (and higher moments of metrics) should be measured simultaneously in networks and procedures to identify informative or redundant metrics. The usefulness of this approach is demonstrated in complex systems with examples from systems biology.

Europhysics Letters 86 (2009) 28003

Physical Review E (Rapid Comunication) 80 040902 (2009)
"Graphlet arrival model" of the EPL paper has been covered in the book: An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks (Chapman & Hall/CRC Computational Biology Series)