Dataset Information

Automated cognome construction and semi-automated hypothesis generation.

ABSTRACT: Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contains more than 21 million peer-reviewed articles with 40-50,000 more published every month. Understanding the human brain, cognition, and disease will require integrating facts from dozens of scientific fields spread amongst millions of studies locked away in static documents, making any such integration daunting, at best. The future of scientific progress will be aided by bridging the gap between the millions of published research articles and modern databases such as the Allen brain atlas (ABA). To that end, we have analyzed the text of over 3.5 million scientific abstracts to find associations between neuroscientific concepts. From the literature alone, we show that we can blindly and algorithmically extract a "cognome": relationships between brain structure, function, and disease. We demonstrate the potential of data-mining and cross-platform data-integration with the ABA by introducing two methods for semi-automated hypothesis generation. By analyzing statistical "holes" and discrepancies in the literature we can find understudied or overlooked research paths. That is, we have added a layer of semi-automation to a part of the scientific process itself. This is an important step toward fundamentally incorporating data-mining algorithms into the scientific method in a manner that is generalizable to any scientific or medical field.

SUBMITTER: Voytek JB

PROVIDER: S-EPMC3376233 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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Automated cognome construction and semi-automated hypothesis generation.

Voytek Jessica B JB Voytek Bradley B

Journal of neuroscience methods 20120511 1

Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contains more than 21 million peer-reviewed articles with 40-50,000 more published every month. Understanding the human brain, cognition, and disease will require integrating facts from dozens of scientific fields spread amongst millions of studies locked away in static documents, making any such integration daunting, at best. The future of scientific progress will be aided by bridging the gap between the m ...[more]

PMID: 22584238

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Project description:BackgroundThe haemostatic balance is an equilibrium of pro- and anticoagulant factors that work synergistically to prevent bleeding and thrombosis. As thrombin is the central enzyme in the coagulation pathway, it is desirable to measure thrombin generation (TG) in order to detect possible bleeding or thrombotic phenotypes, as well as to investigate the capacity of drugs affecting the formation of thrombin. By investigating the underlying processes of TG (i.e., prothrombin conversion and inactivation), additional information is collected about the dynamics of thrombin formation.ObjectivesTo obtain reference values for thrombin dynamics (TD) analysis in 112 healthy donors using an automated system for TG.MethodsTG was measured on the ST Genesia, fibrinogen on the Start, anti-thrombin (AT) on the STA R Max and α2Macroglobulin (α2M) with an in-house chromogenic assay.ResultsTG was measured using STG-BleedScreen, STG-ThromboScreen and STG-DrugScreen. The TG data was used as an input for TD analysis, in combination with plasma levels of AT, α2M and fibrinogen that were 113% (108-118%), 2.6 μM (2.2 μM-3.1 μM) and 2.9 g/L (2.6-3.2 g/L), respectively. The maximum rate of the prothrombinase complex (PCmax) and the total amount of prothrombin converted (PCtot) increased with increasing tissue factor (TF) concentration. PCtot increased from 902 to 988 nM, whereas PCmax increased from 172 to 508 nM/min. Thrombin (T)-AT and T-α2M complexes also increased with increasing TF concentration (i.e., from 860 to 955 nM and from 28 to 33 nm, respectively). PCtot, T-AT and T-α2M complex formation were strongly inhibited by addition of thrombomodulin (-44%, -43%, and -48%, respectively), whereas PCmax was affected less (-24%). PCtot, PCmax, T-AT, and T-α2M were higher in women using oral contraceptives (OC) compared to men/women without OC, and inhibition by thrombomodulin was also significantly less in women on OC (p < 0.05).ConclusionsTG measured on the ST Genesia can be used as an input for TD analysis. The data obtained can be used as reference values for future clinical studies as the balance between prothrombin conversion and thrombin inactivation has shown to be useful in several clinical settings.

Project description:Capture and representation of scientific knowledge in a structured format are essential to improve the understanding of biological mechanisms involved in complex diseases. Biological knowledge and knowledge about standardized terminologies are difficult to capture from literature in a usable form. A semi-automated knowledge extraction workflow is presented that was developed to allow users to extract causal and correlative relationships from scientific literature and to transcribe them into the computable and human readable Biological Expression Language (BEL). The workflow combines state-of-the-art linguistic tools for recognition of various entities and extraction of knowledge from literature sources. Unlike most other approaches, the workflow outputs the results to a curation interface for manual curation and converts them into BEL documents that can be compiled to form biological networks. We developed a new semi-automated knowledge extraction workflow that was designed to capture and organize scientific knowledge and reduce the required curation skills and effort for this task. The workflow was used to build a network that represents the cellular and molecular mechanisms implicated in atherosclerotic plaque destabilization in an apolipoprotein-E-deficient (ApoE(-/-)) mouse model. The network was generated using knowledge extracted from the primary literature. The resultant atherosclerotic plaque destabilization network contains 304 nodes and 743 edges supported by 33 PubMed referenced articles. A comparison between the semi-automated and conventional curation processes showed similar results, but significantly reduced curation effort for the semi-automated process. Creating structured knowledge from unstructured text is an important step for the mechanistic interpretation and reusability of knowledge. Our new semi-automated knowledge extraction workflow reduced the curation skills and effort required to capture and organize scientific knowledge. The atherosclerotic plaque destabilization network that was generated is a causal network model for vascular disease demonstrating the usefulness of the workflow for knowledge extraction and construction of mechanistically meaningful biological networks.

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Automated cognome construction and semi-automated hypothesis generation.

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Automated cognome construction and semi-automated hypothesis generation.

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