Sudeepto Bhattacharya

Bio: Sudeepto Bhattacharya is an academic researcher from Shiv Nadar University. The author has contributed to research in topics: Wildlife corridor & Population. The author has an hindex of 5, co-authored 12 publications receiving 62 citations.

Game of coordination for bacterial pattern formation: a finite automata modelling

Abstract: In this paper, we use game theory to describe the emergence of self-organization and consequent pattern formation through communicative cooperation in Bacillus subtilis colonies. The emergence of cooperative regime is modelled as an n-player Assurance game, with the bacterial colonies as individual players. The game is played iteratively through cooperative communication, and mediated by exchange of information about the local environment between the different bacterial colonies comprising the system. The iteration causes the interactive system to grow and produce beautiful complex spatial patterns signaling the emergence of self-organization. In laboratory, we have the bacterial growth environment mimicked in Petri dish, where chemical stress is introduced in a three- fold manner: through modification of nutrition and substrate amounts and introducing an antibiotic in the system. In our model, bacteria colonies, treated asindividual players, interact within the environment and grow according to a set of rules. The rules capture the biotic processes that allow bacteria to grow in the hostile environment, and cope with the stress. We find the effects of sophisticated communications and information-sharing between bacterial colonies to be a vital determinant for bacterial growth, which is manifested in the Petri dish as complex spatial patterns, often at fractal scales. As a formal description of the above game, we model the emergence of this cooperative behaviour as finite deterministic automata, whose transition function is informed by the Assurance game pay-off. Consequently, the exercise allows us to derive a grammar that provides the rules for describing the bacterial interactions leading to the emergence of the spatial structures.

Network measures for chemical library design.

Abstract: In this overview, we examine recent developments in network approaches to drug design. A brief overview of networks is followed by a discussion of how chemical similarity networks and their properties address challenges in drug design. Multiple methods used to assess or enhance chemical diversity for early-stage drug discovery are discussed, as well as methods that can be used for drug repositioning and ligand polypharmacology.

Genetic Algorithms in Drug Design: A Not-So-Old Story in a Newer Bottle

Abstract: The application of computational tools can alleviate the challenges (viz. time consumption and cost intensiveness) in drug design. Metaheuristics, a collection of such diverse computational and mathematical tools, whose first application was dated back to the early 1970s, caters to several expectations of rational drug designing. Among the population-based metaheuristics, genetic algorithms most closely mimic natural selection. As a consequence, they are rapidly garnering popularity over other members of evolutionary computation as the most preferred simulation processes for drug trials and designing. This chapter discusses various applications of genetic algorithms in drug design, from designing a combinatorial library, QSAR/QSPR study, and designing lead candidacy in drug discovery to solutions for genetic disease. Genetic algorithms find their place in all.

Investigation of similarity and diversity threshold networks generated from diversity-oriented and focused chemical libraries

Abstract: Topological properties of chemical library networks, such as the average clustering coefficient, average path length, and existence of hubs, can serve as indicators to describe the inherent complexities of chemical libraries. We have used Diversity-Oriented Synthesis (DOS) and Focussed Libraries to investigate the appearance of scale-free properties and absence of small-world behavior in chemical libraries. DOS aims to elicit structural complexity in small compounds with respect to skeleton, functional groups, appendages and stereochemistry. Complexity here indicates incorporation of $$\hbox {sp}^{3}$$ carbons, hydrogen bond acceptors and donors in the molecule. Biological studies have shown how structural complexity enhances the interaction of molecules with complex biological macromolecules. In contrast, Focussed Libraries concentrate on specific scaffolds against a specific biological target. We have quantified the diversity in several DOS and Focussed Libraries based on properties of similarity and dissimilarity threshold networks formed from them. Similarity and dissimilarity networks were generated from diverse chemical libraries at various Tanimoto similarity coefficients ( $$\hbox {t}_{\mathrm{c}})$$ using FP2 and MACCS fingerprints. The dissimilarity networks at very low $$\hbox {t}_{\mathrm{c}}$$ threshold led to the absence of small-world behaviors, as evidenced by low average clustering coefficient and high average path length in comparison to Erdos–Renyi networks. Dissimilarity networks exhibit scale free topology as evidenced by a power law degree distribution. The similarity networks at high $$\hbox {t}_{\mathrm{c}}$$ threshold have shown high clustering coefficients and low average path lengths, without the appearance of hubs. Combining dissimilarity and similarity threshold graphs revealed assortative and dissortative behaviors in the DOS libraries, leading to the conclusion that the vertices of the dissimilarity communities are more likely to share similarity edges, but it is quite unlikely for the vertices in a similarity community to share dissimilarity edges. We propose a simple and convenient diversity quantification tool, QuaLDI (Quantitative Library Diversity Index) to quantify the diversity in DOS and Focussed libraries. We anticipate that these topological properties can be used as descriptors to quantify the diversity in chemical libraries before proceeding for synthesis.

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Citation classic - optimal foraging - a selective review of theory and tests

Abstract: Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Data from: Prioritizing tiger conservation through landscape genetics and habitat linkages

Abstract: Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km2 of forest habitat was found to be only 21,290 km2. After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.