Amandeep S. Sidhu

Protein ontology: vocabulary for protein data

These huge amounts of protein structure data make it difficult to create explanatory and predictive models that are consistent with huge volume of data. Difficulty increase when large variety of heterogeneous approaches gathers data from multiple perspectives. In order to facilitate computational processing data, it is especially critical to develop standardized structured data representation model formats for proteomics data. In this paper, we describe a protein ontology model for integrating protein databases and deduce a structured vocabulary for understanding process of protein synthesis completely. Proposed protein ontology model provides biologists and scientists with a description of sequence, structure and functions of protein and also provides interpretation of various factors on final protein structure conformation. The structured vocabulary for protein data, describing protein ontology is composed of various type definitions for protein entry details, sequence and structural information of proteins, structural domain family of protein, cellular function of protein, chemical bonds present in the protein, and external constraints deciding final protein conformation. The proposed ontology model will provide easier ways to predict and understand proteins.

A review on immobilised aptamers for high throughput biomolecular detection and screening.

The discovery of Systematic Evolution of Ligands by Exponential Enrichment (SELEX) assay has led to the generation of aptamers from libraries of nucleic acids. Concomitantly, aptamer-target recognition and its potential biomedical applications have become a major research endeavour. Aptamers possess unique properties that make them superior biological receptors to antibodies with a plethora of target molecules. Some specific areas of opportunities explored for aptamer-target interactions include biochemical analysis, cell signalling and targeting, biomolecular purification processes, pathogen detection and, clinical diagnosis and therapy. Most of these potential applications rely on the effective immobilisation of aptamers on support systems to probe target species. Hence, recent research focus is geared towards immobilising aptamers as oligosorbents for biodetection and bioscreening. This article seeks to review advances in immobilised aptameric binding with associated successful milestones and respective limitations. A proposal for high throughput bioscreening using continuous polymeric adsorbents is also presented.

Ontological foundation for protein data models

In this paper we proposed a Protein Ontology to integrate protein data and information from various Protein Data Sources. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow description and analysis of relationships between various proteins. Protein Ontology uses relevant protein data sources of information like PDB, SCOP, and OMIM. Protein Ontology describes: Protein Sequence and Structure Information, Protein Folding Process, Cellular Functions of Proteins, Molecular Bindings internal and external to Proteins, and Constraints affecting the Final Protein Conformation. We also created a database of 10 Major Prion Proteins available in various Protein data sources, based on the vocabulary provided by Protein Ontology. Details about Protein Ontology are available online at http://www.proteinontology.info/.

SELEX Modifications and Bioanalytical Techniques for Aptamer–Target Binding Characterization

ABSTRACT The quest to improve the detection of biomolecules and cells in health and life sciences has led to the discovery and characterization of various affinity bioprobes. Libraries of synthetic oligonucleotides (ssDNA/ssRNA) with randomized sequences are employed during Systematic Evolution of Ligands by Exponential Enrichment (SELEX) to select highly specific affinity probes called aptamers. With much focus on the generation of aptamers for a variety of target molecules, conventional SELEX protocols have been modified to develop new and improved SELEX protocols yielding highly specific and stable aptamers. Various techniques have been used to analyze the binding interactions between aptamers and their cognate molecules with associated merits and limitations. This article comprehensively reviews research advancements in the generation of aptamers, analyses physicochemical conditions affecting their binding characteristics to cellular and biomolecular targets, and discusses various field applications of aptameric binding. Biophysical techniques employed in the characterization of the molecular and binding features of aptamers to their cognate targets are also discussed.

An XML based semantic protein map

From the nature of the algorithms for data mining we note that an XML framework can be represented using graph matching algorithms. Various techniques currently exist for graph matching of data structures such as the Adjacency Matrix or Algebraic Representation of Graphs. The Graph Representation can be easily converted to a string representation. Both Graph and String Representations miss semantic relationships that exist in the data. These relationships can be captured by using semi-structured XML as a representation format. We already have an approach to integrate different data formats into a Unified Database. The technique is successfully applied to diverse Protein Databases in a Bioinformatics Domain. An XML representation of this comprehensive database preserving order and semantic relationships is already generated. In this paper we propose an approach to a Semantic Protein Map (PMAP) by building a shared ontology on our structured database model. This ontology can be used by various Bioinformatics researchers from one single site. This site will host mirrors of Protein Databases along with BIODB and have tools on Similarity Searching.

Biomedical Data and Applications

Compared with data from general application domains, modern biological data has many unique characteristics. Biological data are often characterized as having large volumes, complex structures, high dimensionality, evolving biological concepts, and insufficient data modelling practices. Over the past several years, bioinformatics has become an all-encompassing term for everything relating to both computer science and biology. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain. The book will become a useful guide learning state-of-the-art development in biomedical data management, data-intensive bioinformatics systems, and other miscellaneous biological database applications. The book addresses various topics in bioinformatics with varying degrees of balance between biomedical data models and their real-world applications.

Advances in Protein Ontology Project

Advances in proteomics and protein expression techniques have lead to the elucidation of large amounts of protein data. Various data mining algorithms and mathematical models provide methods for analyzing this data; however, there are two issues that need to be addressed: (1) the need for standards for defining protein data description and exchange formats so they can be exchanged across the World Wide Web, and also read into data mining software in a consistent format and (2) eliminating errors which arise with the data integration methodologies for complex queries. Protein ontology is designed to meet these needs by providing a structured protein data specification for protein data representation. Protein ontology is a standard for representing protein data in a way that helps in defining data integration and data mining models for protein structure and function. In this paper we summarize the structure of protein ontology we developed earlier, its current applications to various protein families, and its future development

Ontology-based knowledge representation for protein data

The advances in information and communication technologies coupled with increased knowledge about genes and proteins have opened new perspectives for study of protein complexes. There is a growing need to integrate the knowledge about various protein complexes for effective disease prevention mechanisms, individualized medicines and treatments and other accepts of healthcare. In this paper we propose a protein ontology that handles the following computational challenges in the area proteomics and systems biology in general: (1) it provides more accurate interpretations and associations as conclusions are based on data and semantics. (2) It makes it possible to study relationships among proteins, protein folding, behaviour of protein under various environments, and most importantly cellular function of protein. This protein ontology is a unified terminology description integrating various protein database schemas and provides a easier way to predict and understand proteins.

Cloud computing for energy management in smart grid - an application survey

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid.

Deploying aptameric sensing technology for rapid pandemic monitoring

Abstract The genome of virulent strains may possess the ability to mutate by means of antigenic shift and/or antigenic drift as well as being resistant to antibiotics with time. The outbreak and spread of these virulent diseases including avian influenza (H1N1), severe acute respiratory syndrome (SARS-Corona virus), cholera (Vibrio cholera), tuberculosis (Mycobacterium tuberculosis), Ebola hemorrhagic fever (Ebola Virus) and AIDS (HIV-1) necessitate urgent attention to develop diagnostic protocols and assays for rapid detection and screening. Rapid and accurate detection of first cases with certainty will contribute significantly in preventing disease transmission and escalation to pandemic levels. As a result, there is a need to develop technologies that can meet the heavy demand of an all-embedded, inexpensive, specific and fast biosensing for the detection and screening of pathogens in active or latent forms to offer quick diagnosis and early treatments in order to avoid disease aggravation and unnecessary late treatment costs. Nucleic acid aptamers are short, single-stranded RNA or DNA sequences that can selectively bind to specific cellular and biomolecular targets. Aptamers, as new-age bioaffinity probes, have the necessary biophysical characteristics for improved pathogen detection. This article seeks to review global pandemic situations in relation to advances in pathogen detection systems. It particularly discusses aptameric biosensing and establishes application opportunities for effective pandemic monitoring. Insights into the application of continuous polymeric supports as the synthetic base for aptamer coupling to provide the needed convective mass transport for rapid screening is also presented.