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

Protein ontology development using OWL

To efficiently represent the protein annotation framework and to integrate all the existing data representations into a standardized protein data specification for the bioinformatics community, the protein ontology need to be represented in a format that not enforce semantic constraints on protein data, but can also facilitate reasoning tasks on protein data using semantic query algebra. This motivates the representation of Protein Ontology (PO) Model in Web Ontology Language (OWL). In this paper we briefly discuss the usage of OWL in achieving the objectives of Protein Ontology Project. We provide a brief overview of Protein Ontology (PO) to start with. In the later sections discuss why OWL was an ideal choice for PO Development

OWL, proteins and data integration

In this paper, we propose an approach to integrate protein information from various data sources by defining a Protein Ontology. 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. Details about Protein Ontology are available online at http://www.proteinontology.info/

Protein Ontology Project: 2006 updates

Protein Ontology (PO) is a means of formalizing protein data and knowledge; protein ontology includes concepts or terms relevant to the domain, definitions of concepts, and defined relationships between the concepts. PO integrates protein data formats and provides a structured and unified vocabulary to represent protein synthesis concepts. PO provides integration of heterogeneous protein and biological data sources. This paper discusses the updates that happened to the Protein Ontology Project since it was last presented at the Data Mining 2005 Conference

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

Numerical Modelling of High Speed Blanking Considering Thermoviscoplastic Effects

To achieve the required specifications of the cut-edge profile of a blank, a time consuming trial and error procedures based on empirical information are utilized. However, the modern industry demands high quality product specifications in the shortest possible production time. Therefore, in order to predict the cut-edge profile and speed up the production process, it is essential to develop a reliable numerical model of the high speed blanking process which can predict the cut-edge profile of the blanks. In this study, the Lagrangian based finite element (FE) approach was used to model large strain deformation that takes place in the shearzone during blanking. However, the large deformation is difficult to model using Lagrangian approach as it leads to a severe distortion of the FE mesh. Therefore, in order to overcome a premature termination of the analysis due to the mesh distortion, an adaptive remeshing and rezoning technique was developed. Furthermore, to model the ductile fracture, the discrete crack propagation method was implemented in the MSC.Marc® Due to high speed of the cutting stamp, thermoviscoplastic material behaviour has to be taken into account. The Johnson-Cook plasticity model was used to model viscoplasticity. The results obtained from the FE analysis are presented in this paper

Audit quality and properties of analysts’ information environment

© 2018 John Wiley & Sons Ltd We consider how audit quality impacts sell-side analysts’ information environment. Using the method outlined by Barron et al., we examine whether higher audit quality is associated with differences in the weight analysts place on common information relative to private information, as well as the extent to which audit quality separately impacts the precision of analysts’ private and common information. Our results show that, in instances where analysts revise their earnings forecasts for year t+1 shortly after the release of year t earnings, higher audit quality results in analysts placing more weight on public information. The precision of private (as well as public) information is improved. These results extend our understanding of how audit quality impacts on attributes of analysts’ forecasts and provides support for the argument that audit quality has important capital market implications

Role of Computer Technology in Changing Smile

In the ever changing complex society, where success has become a mantra for both young and old, facial appearance that includes smile, plays a pivotal role. Among many attractive components in a person’s face, smile reflects the persona of an individual. In the present day next gen age, science in unison with technology and techniques which are rapidly getting ingrained into day to day dental practice, has changed the perception of healthy smile by more effective and less invasive approach. In this scenario, the onus lies on the dentist to give that perfectionist touch to a customised smile using computer aided software and hardware apparatus, and to avail the best state of the art material, equipment and techniques. Hence, it is imperative for us to understand and inculcate the role of modern cutting edge computer-aided technologies used in designing and changing the smile of an individual

Reduced influence of perceptual context in mild traumatic brain injury is not an illusion

Perceptual grouping is impaired following mild traumatic brain injury (mTBI). This may affect visual size perception, a process influenced by perceptual grouping abilities. We conducted two experiments to evaluate visual size perception in people with self-reported history of mTBI, using two different size-contrast illusions: the Ebbinghaus Illusion (Experiment 1) and the Müller-Lyer illusion (Experiment 2). In Experiment 1, individuals with mTBI and healthy controls were asked to compare the size of two target circles that were either the same size or different sizes. The target circles appeared by themselves (no-context condition), or were surrounded by smaller or larger circles (context condition). Similar levels of accuracy were evident between the groups in the no-context condition. However, size judgements by mTBI participants were more accurate in the context condition, suggesting that they processed the target circles separately from the surrounding circles. In Experiment 2, individuals with mTBI and healthy controls judged the length of parallel lines that appeared with arrowheads (context condition) or without arrowheads (no context condition). Consistent with Experiment 1, size judgements by mTBI participants were more accurate than size judgements by control participants in the context condition. These findings suggest that mTBI influences size perception by impairing perceptual grouping of visual stimuli in near proximity