arXiv subjects

Ganesh Bagler

Publications and source records attributed to Ganesh Bagler.

30 records · Page 2Linked to original sources

arXiv2016

A distance constrained synaptic plasticity model of C. elegans neuronal network

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The neuronal architecture forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

q-bio.NC↗

arXiv2016

Network biomarkers of schizophrenia by graph theoretical investigations of Brain Functional Networks

Brain Functional Networks (BFNs), graph theoretical models of brain activity data, provide a systems perspective of complex functional connectivity within the brain. Neurological disorders are known to have basis in abnormal functional activities, that could be captured in terms of network markers. Schizophrenia is a pathological condition characterized with altered brain functional state. We created weighted and binary BFN models of schizophrenia patients as well as healthy subjects starting from fMRI data in an effort to search for network biomarkers of the disease. We investigated 45 topological features of BFNs and their higher order combinations (2 to 8). We find that network features embodying modularity, betweenness, assortativity and edge density emerge as key markers of schizophrenia. Also, features derived from weighted BFNs were observed to be more effective in disease classification as compared to those from binary BFNs. These topological markers may provide insights into mechanisms of functional activity underlying disease phenotype and could further be used for designing algorithms for clinical diagnosis of schizophrenia as well as its early detection.

q-bio.QM↗

arXiv2015

Numerical study of variable lung ventilation strategies

Mechanical ventilation is used for patients with a variety of lung diseases. Traditionally, ventilators have been designed to monotonously deliver equal sized breaths. While it may seem intuitive that lungs may benefit from unvarying and stable ventilation pressure strategy, recently it has been reported that variable lung ventilation is advantageous. In this study, we analyze the mean tidal volume in response to different `variable ventilation pressure' strategies. We found that uniformly distributed variability in pressure gives the best tidal volume as compared to that of normal, scale- free, log normal and linear distributions.

q-bio.QM↗

arXiv2015

Analysis of food pairing in regional cuisines of India

Any national cuisine is a sum total of its variety of regional cuisines, which are the cultural and historical identifiers of their respective regions. India is home to a number of regional cuisines that showcase its culinary diversity. Here, we study recipes from eight different regional cuisines of India spanning various geographies and climates. We investigate the phenomenon of food pairing which examines compatibility of two ingredients in a recipe in terms of their shared flavor compounds. Food pairing was enumerated at the level of cuisine, recipes as well as ingredient pairs by quantifying flavor sharing between pairs of ingredients. Our results indicate that each regional cuisine follows negative food pairing pattern; more the extent of flavor sharing between two ingredients, lesser their co-occurrence in that cuisine. We find that frequency of ingredient usage is central in rendering the characteristic food pairing in each of these cuisines. Spice and dairy emerged as the most significant ingredient classes responsible for the biased pattern of food pairing. Interestingly while individual spices contribute to negative food pairing, dairy products on the other hand tend to deviate food pairing towards positive side. Our data analytical study highlighting statistical properties of the regional cuisines, brings out their culinary fingerprints that could be used to design algorithms for generating novel recipes and recipe recommender systems. It forms a basis for exploring possible causal connection between diet and health as well as prospection of therapeutic molecules from food ingredients. Our study also provides insights as to how big data can change the way we look at food.

physics.soc-ph↗

arXiv2015

Culinary evolution models for Indian cuisines

Culinary systems, the practice of preparing a refined combination of ingredients that is palatable as well as socially acceptable, are examples of complex dynamical systems. They evolve over time and are affected by a large number of factors. Modeling the dynamic nature of evolution of regional cuisines may provide us a quantitative basis and exhibit underlying processes that have driven them into the present day status. This is especially important given that the potential culinary space is practically infinite because of possible number of ingredient combinations as recipes. Such studies also provide a means to compare and contrast cuisines and to unearth their therapeutic value. Herein we provide rigorous analysis of modeling eight diverse Indian regional cuisines, while also highlighting their uniqueness, and a comparison among those models at the level of flavor compounds which opens up molecular level studies associating them especially with non-communicable diseases such as diabetes.

physics.soc-ph↗

arXiv2015

Spices form the basis of food pairing in Indian cuisine

Culinary practices are influenced by climate, culture, history and geography. Molecular composition of recipes in a cuisine reveals patterns in food preferences. Indian cuisine encompasses a number of diverse sub-cuisines separated by geographies, climates and cultures. Its culinary system has a long history of health-centric dietary practices focused on disease prevention and promotion of health. We study food pairing in recipes of Indian cuisine to show that, in contrast to positive food pairing reported in some Western cuisines, Indian cuisine has a strong signature of negative food pairing; more the extent of flavor sharing between any two ingredients, lesser their co-occurrence. This feature is independent of recipe size and is not explained by ingredient category-based recipe constitution alone. Ingredient frequency emerged as the dominant factor specifying the characteristic flavor sharing pattern of the cuisine. Spices, individually and as a category, form the basis of ingredient composition in Indian cuisine. We also present a culinary evolution model which reproduces ingredient use distribution as well as negative food pairing of the cuisine. Our study provides a basis for designing novel signature recipes, healthy recipe alterations and recipe recommender systems.

physics.soc-ph↗

arXiv2012

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.

q-bio.MN↗

arXiv2008

Complex Network view of performance and risks on Airport Networks

Air transportation has been becoming a major part of transportation infrastructure worldwide. Hence the study of the Airports Networks, the backbone of air transportation, is becoming increasingly important. In complex systems domain, airport networks are modeled as graphs (networks) comprising of airports (vertices or nodes) that are linked by flight connectivities among the airports. A complex network analysis of such a model offers holistic insight about the performance and risks in such a network. We review the performance and risks of networks with the help of studies that have been done on some of the airport networks. We present various network parameters those could be potentially used as a measure of performance and risks on airport networks. We will also see how various risks, such as break down of airports, spread of diseases across the airport network could be assessed based on the network parameters. Further we review how these insights could possibly be used to shape more efficient and safer airport networks.

physics.soc-ph↗

arXiv2007

Assortative mixing in Protein Contact Networks and protein folding kinetics

Starting from linear chains of amino acids, the spontaneous folding of proteins into their elaborate three-dimensional structures is one of the remarkable examples of biological self-organization. We investigated native state structures of 30 single-domain, two-state proteins, from complex networks perspective, to understand the role of topological parameters in proteins' folding kinetics, at two length scales-- as ``Protein Contact Networks (PCNs)'' and their corresponding ``Long-range Interaction Networks (LINs)'' constructed by ignoring the short-range interactions. Our results show that, both PCNs and LINs exhibit the exceptional topological property of ``assortative mixing'' that is absent in all other biological and technological networks studied so far. We show that the degree distribution of these contact networks is partly responsible for the observed assortativity. The coefficient of assortativity also shows a positive correlation with the rate of protein folding at both short and long contact scale, whereas, the clustering coefficients of only the LINs exhibit a negative correlation. The results indicate that the general topological parameters of these naturally-evolved protein networks can effectively represent the structural and functional properties required for fast information transfer among the residues facilitating biochemical/kinetic functions, such as, allostery, stability, and the rate of folding.

q-bio.MN↗

arXiv2007

Modeling Protein Contact Networks

Proteins are an important class of biomolecules that serve as essential building blocks of the cells. Their three-dimensional structures are responsible for their functions. In this thesis we have investigated the protein structures using a network theoretical approach. While doing so we used a coarse-grained method, viz., complex network analysis. We model protein structures at two length scales as Protein Contact Networks (PCN) and as Long-range Interaction Networks (LINs). We found that proteins by virtue of being characterised by high amount of clustering, are small-world networks. Apart from the small-world nature, we found that proteins have another general property, viz., assortativity. This is an interesting and exceptional finding as all other complex networks (except for social networks) are known to be disassortative. Importantly, we could identify one of the major topological determinant of assortativity by building appropriate controls.

q-bio.MN↗

arXiv2007

Analysis of the Airport Network of India as a complex weighted network

Transportation infrastructure of a country is one of the most important indicators of its economic growth. Here we study the Airport Network of India (ANI), which represents India's domestic civil aviation infrastructure, as a complex network. We find that ANI, a network of domestic airports connected by air links, is a small-world network characterized by a truncated power-law degree distribution, and has a signature of hierarchy. We investigate ANI as a weighted network to explore its various properties and compare them with their topological counterparts. The traffic in ANI, as in the World-wide Airport Network (WAN), is found to be accumulated on interconnected groups of airports and is concentrated between large airports. In contrast to WAN, ANI is found to be having disassortative mixing which is offset by the traffic dynamics. The analysis indicates toward possible mechanism of formation of a national transportation network, which is different from that on a global scale.

cond-mat.other↗

arXiv2004

Network properties of protein structures

Protein structures can be studied as complex networks of interacting amino acids. We study proteins of different structural classes from the network perspective. Our results indicate that proteins, regardless of their structural class, show small-world network property. Various network parameters offer insight into the structural organisation of proteins and provide indications of modularity in protein networks.

q-bio.MN↗