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Amarnath Gupta

Publications and source records attributed to Amarnath Gupta.

11 recordsLinked to original sources
PubMed2006

BiologicalNetworks: visualization and analysis tool for systems biology.

Systems level investigation of genomic scale information requires the development of truly integrated databases dealing with heterogeneous data, which can be queried for simple properties of genes or other database objects as well as for complex network level properties, for the analysis and modelling of complex biological processes. Towards that goal, we recently constructed PathSys, a data integration platform for systems biology, which provides dynamic integration over a diverse set of databases [Baitaluk et al. (2006) BMC Bioinformatics 7, 55]. Here we describe a server, BiologicalNetworks, which provides visualization, analysis services and an information management framework over PathSys. The server allows easy retrieval, construction and visualization of complex biological networks, including genome-scale integrated networks of protein-protein, protein-DNA and genetic interactions. Most importantly, BiologicalNetworks addresses the need for systematic presentation and analysis of high-throughput expression data by mapping and analysis of expression profiles of genes or proteins simultaneously on to regulatory, metabolic and cellular networks. BiologicalNetworks Server is available at http://brak.sdsc.edu/pub/BiologicalNetworks.

Computer Graphics↗
PubMed2006

PathSys: integrating molecular interaction graphs for systems biology.

BACKGROUND: The goal of information integration in systems biology is to combine information from a number of databases and data sets, which are obtained from both high and low throughput experiments, under one data management scheme such that the cumulative information provides greater biological insight than is possible with individual information sources considered separately. RESULTS: Here we present PathSys, a graph-based system for creating a combined database of networks of interaction for generating integrated view of biological mechanisms. We used PathSys to integrate over 14 curated and publicly contributed data sources for the budding yeast (S. cerevisiae) and Gene Ontology. A number of exploratory questions were formulated as a combination of relational and graph-based queries to the integrated database. Thus, PathSys is a general-purpose, scalable, graph-data warehouse of biological information, complete with a graph manipulation and a query language, a storage mechanism and a generic data-importing mechanism through schema-mapping. CONCLUSION: Results from several test studies demonstrate the effectiveness of the approach in retrieving biologically interesting relations between genes and proteins, the networks connecting them, and of the utility of PathSys as a scalable graph-based warehouse for interaction-network integration and a hypothesis generator system. The PathSys's client software, named BiologicalNetworks, developed for navigation and analyses of molecular networks, is available as a Java Web Start application at http://brak.sdsc.edu/pub/BiologicalNetworks.

Computer Graphics↗
PubMed2005

Kinetics of phase separation in systems exhibiting simple coacervation.

The kinetics of phase separation of a homogeneous polyelectrolytic solution into a dense polymer-rich coacervate and the dilute supernatant phase is discussed through statistical thermodynamics. It has been shown that the coacervate phase is associated with higher internal pressure, consequently giving rise to syneresis. Physical conditions for phase separations has been deduced explicitly which reveals that sigma(2)/qrt[I] > or = constant (where sigma is polyelectrolyte charge density and I is solution ionic strength), consistent with experimental observations. In the lattice model, r is the number of sites occupied by the polymer having a volume critical fraction psi(2c), it was found that phase separation would ensue when sigma(3)r > or = (64/9 alpha(2)) [psi(2c)/(1 - omega(2c))(2)], which reduces to (sigma(3)r/psi(2c)) > or = (64/9 alpha(2)) approximately 0.45 at 20 degrees C for psi(2c) < 1. The separation kinetics mimics a spinodal decomposition process. Rate of release of supernatant due to syneresis was found to be independent of the initial coacervate mass. Syneresis results are discussed in the context of temporal evolution of self-organization in polymer melts through Avrami model.

Journal Article↗
PubMed2005

Biomedical informatics research network: building a national collaboratory to hasten the derivation of new understanding and treatment of disease.

Through support from the National Institutes of Health's National Center for Research Resources, the Biomedical Informatics Research Network (BIRN) is pioneering the use of advanced cyberinfrastructure for medical research. By synchronizing developments in advanced wide area networking, distributed computing, distributed database federation, and other emerging capabilities of e-science, the BIRN has created a collaborative environment that is paving the way for biomedical research and clinical information management. The BIRN Coordinating Center (BIRN-CC) is orchestrating the development and deployment of key infrastructure components for immediate and long-range support of biomedical and clinical research being pursued by domain scientists in three neuroimaging test beds.

Biomedical Research↗
PubMed2004

E-neuroscience: challenges and triumphs in integrating distributed data from molecules to brains.

Imaging, from magnetic resonance imaging (MRI) to localization of specific macromolecules by microscopies, has been one of the driving forces behind neuroinformatics efforts of the past decade. Many web-accessible resources have been created, ranging from simple data collections to highly structured databases. Although many challenges remain in adapting neuroscience to the new electronic forum envisioned by neuroinformatics proponents, these efforts have succeeded in formalizing the requirements for effective data sharing and data integration across multiple sources. In this perspective, we discuss the importance of spatial systems and ontologies for proper modeling of neuroscience data and their use in a large-scale data integration effort, the Biomedical Informatics Research Network (BIRN).

Animals↗
PubMed2003

Towards a formalization of disease-specific ontologies for neuroinformatics.

We present issues arising when trying to formalize disease maps, i.e. ontologies to represent the terminological relationships among concepts necessary to construct a knowledge-base of neurological disorders. These disease maps are being created in the context of a large-scale data mediation system being created for the Biomedical Informatics Research Network (BIRN). The BIRN is a multi-university consortium collaborating to establish a large-scale data and computational grid around neuroimaging data, collected across multiple scales. Test bed projects within BIRN involve both animal and human studies of Alzheimer's disease, Parkinson's disease and schizophrenia. Incorporating both the static 'terminological' relationships and dynamic processes, disease maps are being created to encapsulate a comprehensive theory of a disease. Terms within the disease map can also be connected to the relevant terms within other ontologies (e.g. the Unified Medical Language System), in order to allow the disease map management system to derive relationships between a larger set of terms than what is contained within the disease map itself. In this paper, we use the basic structure of a disease map we are developing for Parkinson's disease to illustrate our initial formalization for disease maps.

Electronic Data Processing↗
PubMed2003

The cell-centered database: a database for multiscale structural and protein localization data from light and electron microscopy.

The creation of structured shared data repositories for molecular data in the form of web-accessible databases like GenBank has been a driving force behind the genomic revolution. These resources serve not only to organize and manage molecular data being created by researchers around the globe, but also provide the starting point for data mining operations to uncover interesting information present in the large amount of sequence and structural data. To realize the full impact of the genomic and proteomic efforts of the last decade, similar resources are needed for structural and biochemical complexity in biological systems beyond the molecular level, where proteins and macromolecular complexes are situated within their cellular and tissue environments. In this review, we discuss our efforts in the development of neuroinformatics resources for managing and mining cell level imaging data derived from light and electron microscopy. We describe the main features of our web-accessible database, the Cell Centered Database (CCDB; http://ncmir.ucsd.edu/CCDB/), designed for structural and protein localization information at scales ranging from large expanses of tissue to cellular microdomains with their associated macromolecular constituents. The CCDB was created to make 3D microscopic imaging data available to the scientific community and to serve as a resource for investigating structural and macromolecular complexity of cells and tissues, particularly in the rodent nervous system.

Brain↗
PubMed2002

Modeling shape and topology of low-resolution density maps of biological macromolecules.

In the present work we develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution, aiming at storing and querying them in a database framework. We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data. Connectivity among points is obtained with the use of the alpha shapes theory. This novel data representation has a number of interesting characteristics, such as 1) it allows us to automatically segment and quantify a number of important structural features from low-resolution maps, such as cavities and channels, opening the possibility of querying large collections of maps on the basis of these quantitative structural features; 2) it provides a compact representation in terms of size; 3) it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data; and 4) a general model of the geometry and topology of the macromolecule (as opposite to a spatially unrelated bunch of voxels) is easily obtained by the use of the alpha shapes theory.

Algorithms↗
PubMedDate not supplied

A cell-centered database for electron tomographic data.

Electron tomography is providing a wealth of 3D structural data on biological components ranging from molecules to cells. We are developing a web-accessible database tailored to high-resolution cellular level structural and protein localization data derived from electron tomography. The Cell Centered Database or CCDB is built on an object-relational framework using Oracle 8i and is housed on a server at the San Diego Supercomputer Center at the University of California, San Diego. Data can be deposited and accessed via a web interface. Each volume reconstruction is stored with a full set of descriptors along with tilt images and any derived products such as segmented objects and animations. Tomographic data are supplemented by high-resolution light microscopic data in order to provide correlated data on higher-order cellular and tissue structure. Every object segmented from a reconstruction is included as a distinct entity in the database along with measurements such as volume, surface area, diameter, and length and amount of protein labeling, allowing the querying of image-specific attributes. Data sets obtained in response to a CCDB query are retrieved via the Storage Resource Broker, a data management system for transparent access to local and distributed data collections. The CCDB is designed to provide a resource for structural biologists and to make tomographic data sets available to the scientific community at large.

Animals↗
PubMedDate not supplied

Flory temperature and upper critical solution temperature of gelatin solutions.

The Flory temperatures (theta) measured by turbidity experiments performed on gelatin solutions were found to be 12 +/- 0.3, 13 +/- 0.3, 14 +/- 0.3, 14.5 +/- 0.3, and 15 +/- 0.3 degrees C for salt concentrations 0.1, 0.075, 0.05, 0.025, and 0 M (NaCl), respectively. Estimated persistence length (l(p)) of this weakly charged polyelectrolyte could be deduced from the Benoit and Doty (J. Phys. Chem. 1953, 57, 958) relationship with the approximation that this biopolymer assumes a compact near-globular shape at Flory temperature, implying l(p) = 9(R(h))(2)/(5L(m)), where L(m) is the contour length and R(h) is the hydrodynamic radius. It was found that l(p) approximately 2.2 +/- 0.2 nm at room temperature (20 degrees C), invariant of salt concentration. The Flory expansion factor (alpha= R(h)(T)/R(h)(theta) = 1.5+/-0.2) was found to be almost constant. theta-Composition for this biopolymer was deduced from turbidimitric titration of aqueous gelatin solutions with the alcohols methanol, ethanol, 2-propanol, and tert-butyl alcohol. It appears that hydrophobic interactions play a crucial role in causing chain collapse at theta-temperature and composition.

Gelatin↗