92,647 research outputs found

    The Informational Model of Consciousness: Mechanisms of Embodiment/Disembodiment of Information

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    It was shown recently that information is the central concept which it is to be considered to understand consciousness and its properties. Arguing that consciousness is a consequence of the operational activity of the informational system of the human body, it was shown that this system is composed by seven informational components, reflected in consciousness by corresponding cognitive centers. It was argued also that consciousness can be connected to the environment not only by the common senses, but also by a special connection pole to the bipolar properties of the universe, allowing to explain the associated phenomena of the near-death experiences and other special phenomena. Starting from the characteristics of this model, defined as the Informational Model of Consciousness and to complete the info-communication panorama, in this paper it is analyzed the info-connectivity of the informational system with the body itself. The brain areas where the activity of each informational component are identified, and a definition of consciousness in terms of information is proposed. As the electrical connectivity by means of the nervous system was already proved, allowing the application of the analysis and developing tools of the information science, a particular attention is paid to the non-electrical mechanisms implied in the internal communication. For this, it is shown that the key mechanisms consists in embodiment/disembodiment processes of information during the inter and intra communication of the cells. This process can be modeled also by means of, and in correlation with specific concepts of the science and technology of information, referred to network communication structures, and is represented by epigenetic mechanisms, allowing the acquired trait transmission to the offspring generation. From the perspective of the informational model of consciousness, the human organism appears therefore as a dynamic reactive informational system, actuating in correlation with matter for adaptation, by embodiment/disembodiment processes of information

    Natural Language Query in the Biochemistry and Molecular Biology Domains Based on Cognition Search™

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    Motivation: With the tremendous growth in scientific literature, it is necessary to improve upon the standard pattern matching style of the available search engines. Semantic NLP may be the solution to this problem. Cognition Search (CSIR) is a natural language technology. It is best used by asking a simple question that might be answered in textual data being queried, such as MEDLINE. CSIR has a large English dictionary and semantic database. Cognition’s semantic map enables the search process to be based on meaning rather than statistical word pattern matching and, therefore, returns more complete and relevant results. The Cognition Search engine uses downward reasoning and synonymy which also improves recall. It improves precision through phrase parsing and word sense disambiguation.
Result: Here we have carried out several projects to "teach" the CSIR lexicon medical, biochemical and molecular biological language and acronyms from curated web-based free sources. Vocabulary from the Alliance for Cell Signaling (AfCS), the Human Genome Nomenclature Consortium (HGNC), the United Medical Language System (UMLS) Meta-thesaurus, and The International Union of Pure and Applied Chemistry (IUPAC) was introduced into the CSIR dictionary and curated. The resulting system was used to interpret MEDLINE abstracts. Meaning-based search of MEDLINE abstracts yields high precision (estimated at >90%), and high recall (estimated at >90%), where synonym information has been encoded. The present implementation can be found at http://MEDLINE.cognition.com. 
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    Metrology and Molecular Diagnosis of Infection

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    Metrology, the study of measurement, is an emerging concept within molecular diagnosis of infection. Metrology promotes high-quality, reproducible data to be used in clinical management of infection, through characterisation of technical error and measurement harmonisation. This influences measurement accuracy, which has implications for setting thresholds between healthy and disease states, monitoring disease progression, and establishing cures. This thesis examines the placing of metrology in molecular diagnosis of infectious diseases. Sources of experimental error in advanced methodologies – dPCR and MALDI-TOF MS – that can influence measurement accuracy for RNA, DNA and protein biomarkers were investigated for HIV-1, methicillin-resistant Staphylococcus spp and organisms associated with hospital transmission. Measurement error introduced at different stages of a method can directly impact upon clinical results. A 30% bias was introduced between dPCR and qPCR quantification of HIV-1 DNA in clinical samples, owing to instability in the qPCR calibration material. In addition, experimental variability was found to influence classification of protein profiles which can limit the resolution of MALDI-TOF MS for strain typing bacteria. This thesis also addresses the prospective role of these advanced methods in supporting accurate clinical measurements. dPCR offers precise measurements of RNA and DNA targets and could be used to support qPCR, or for value assignment of reference materials to harmonise inter-laboratory results. MALDI-TOF MS demonstrated potential for strain typing Acinetobacter baumannii; results correlated with epidemiological data and WGS, although were not consistent with reference typing. Further work should examine the extent to which MALDI-TOF MS can support or replace contemporary strain typing methods for identifying nosocomial outbreaks. Molecular approaches possess a crucial role in the detection, quantification and characterisation of pathogens, and are invaluable tools for managing emerging diseases. Supporting accuracy and reproducibility in molecular measurements could help to strengthen diagnostic efforts, streamline clinical pathways and provide overall benefit to patient care

    Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

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    Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

    How do Ontology Mappings Change in the Life Sciences?

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    Mappings between related ontologies are increasingly used to support data integration and analysis tasks. Changes in the ontologies also require the adaptation of ontology mappings. So far the evolution of ontology mappings has received little attention albeit ontologies change continuously especially in the life sciences. We therefore analyze how mappings between popular life science ontologies evolve for different match algorithms. We also evaluate which semantic ontology changes primarily affect the mappings. We further investigate alternatives to predict or estimate the degree of future mapping changes based on previous ontology and mapping transitions.Comment: Keywords: mapping evolution, ontology matching, ontology evolutio
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