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Biomedical data analysis in translational research
unpublished
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Biomedical data analysis in translational research: Integration of expert knowledge and interpretable models 1 Introduction New technologies in various fields of biomedical research have led to a dramatic ...
experts from knowledge representation and integration as well as bio-medical and clinical experts who have a strong interest in developing interpretable models. ...
fatcat:pvwzwsw64nbdlhum4a3vkxbqne
An automated reasoning framework for translational research
2010
Journal of Biomedical Informatics
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In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation ...
Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with ...
Acknowledgments The authors thank Alireza Nazarian for his help in analyzing the WTCCC data, and Alberto Malovini for his help in implementing the GWAS analysis pipeline. ...
doi:10.1016/j.jbi.2009.11.005
pmid:19931420
pmcid:PMC2878845
fatcat:2hfq5r76pjhwplrmcctr5jchoe
e-Science, caGrid, and Translational Biomedical Research
2008
Computer
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of biomedical hypotheses, and employ a large assortment of experimental methodologies. ...
Tahsin Kurc[Senior researcher and chief software architect], Tony Pan[Senior research specialist], Abstract Translational research projects target a wide variety of diseases, test many different kinds ...
Our work was supported in part by the NCI caGrid Developer grant 79077CBS10, the State of Ohio BRTT Program grants ODOD AGMT TECH 04-049 and BRTT02-0003, the NHLBI R24 HL085343 grant, the NIH U54 CA113001 ...
doi:10.1109/mc.2008.459
pmid:21311723
pmcid:PMC3035203
fatcat:aqwbedm2kveejallfldacjrpbe
Artificial Intelligence Pipeline to Bridge the Gap between Bench Researchers and Clinical Researchers in Precision Medicine
2020
Med One
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Precision medicine informatics is a field of research that incorporates learning systems that generate new knowledge to improve individualized treatments using integrated data sets and models. ...
This dovetails with precision medicine research, given the information rich multi-omic data that are used in precision medicine analysis pipelines. ...
In this way, the AI pipeline combines the interpretive strength of experts and practitioners in the specific areas of interest while enhancing their models with data-informed AI medical models. ...
doi:10.20900/mo20200001
pmid:33511289
pmcid:PMC7839064
fatcat:aenjk6kpt5gjpmi75pv65aszbu
Everyday characterizations of translational research: researchers' own use of terminology and models in medical research and practice
2020
Palgrave Communications
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Everyday characterizations of translational research Researchers' own use of terminology and models in medical research and practice Strand, Dixi Louise ABSTRACT Biomedical literature and policy are highly ...
The analysis draws on the analytical notion of performativity in order to approach statements and models of TR in the light of their performative dimension. ...
Acknowledgements This study was funded by Data and Development Support, Region Zealand, and hosted by Department of People and Technology, Roskilde University. ...
doi:10.1057/s41599-020-0489-1
fatcat:gnbpc4zbuzbplosqhi5f4ek5qm
Biomedical Semantics: the Hub for Biomedical Research 2.0
2010
Journal of Biomedical Semantics
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The main focus of JBMS is the development and integration of semantics resources into the biomedical research practice. ...
medical treatments, development of therapeutics, translational medicine, food production and others. ...
reasoning systems, etc.) and their use in data and knowledge integration, mining, modelling, interpretation and exploitation in and for biomedical research. ...
doi:10.1186/2041-1480-1-1
pmid:20618983
pmcid:PMC2895735
fatcat:iidmzu5jljdanavpzaxchluppy
geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research
2009
BMC Bioinformatics
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Conclusion: geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. ...
For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. ...
Acknowledgements This work is supported in part by the projects Research on Translational Bioinformatics (ref. 08VIB6) from University of Vigo and Development of computational tools for the classification ...
doi:10.1186/1471-2105-10-187
pmid:19538727
pmcid:PMC2703634
fatcat:vjkesv2nfrfrrps55dz5psyywe
Evaluation of research in biomedical ontologies
2012
Briefings in Bioinformatics
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the objective evaluation and comparison of research results in applied ontology. ...
We propose that results in applied ontology must be evaluated within their domain of application, based on some ontology-based task within the domain, and discuss quantitative measures which would facilitate ...
to improve integrative biology and translational research. ...
doi:10.1093/bib/bbs053
pmid:22962340
pmcid:PMC3888109
fatcat:lyepy5en5vfpzgbq6uaaxr7aiu
STO: Stroke Ontology for Accelerating Translational Stroke Research
2021
Neurology and Therapy
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Ontology-based annotation of evidence, using disease-specific ontologies, can accelerate analysis and interpretation of the knowledge domain of diseases. ...
The ontology was evaluated in terms of structural and functional features, expert evaluation, and competency questions. ...
of Health. ...
doi:10.1007/s40120-021-00248-1
pmid:33886080
fatcat:yhig46tqhzbzdakx53bhgo47fa
Facilitating cancer systems epidemiology research
2021
PLoS ONE
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Eight key themes emerged from the discussion: transdisciplinary collaboration and a problem-based approach; methods and modeling considerations; interpretation, validation, and evaluation of models; data ...
needs and opportunities; sharing of data and models; enhanced training practices; dissemination of systems models; and building a systems epidemiology community. ...
Training the next generation of data scientists and integrating these researchers into biomedical and public health fields is a priority within the NIH strategic plan for data science [75] . ...
doi:10.1371/journal.pone.0255328
pmid:34972102
pmcid:PMC8719747
fatcat:hjddvhn4yjhptmbvoioegh3lom
Clinical and Translational Research Studios
2012
Academic Medicine
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To achieve the health goals of the 21st century, researchers from multiple disciplines must bridge their differences and together address the challenging problems that face us. ...
Analysis and interpretation Assists investigators with analyzing and interpreting study data and findings, generating subsequent hypotheses and research questions, and identifying insights that could inform ...
Studio types and expert panels Investigators select one of seven Studio types: hypothesis generation, study design, grant review, implementation, analysis and interpretation, manuscript review, or translation ...
doi:10.1097/acm.0b013e31825d29d4
pmid:22722360
pmcid:PMC3406254
fatcat:5lylenbukbgmrh5kzyuife2x6e
Knowledge Discovery and interactive Data Mining in Bioinformatics - State-of-the-Art, future challenges and research directions
2014
BMC Bioinformatics
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Knowledge Discovery process The traditional method of turning data into knowledge relied on manual analysis and interpretation by a domain expert in order to find useful patterns in data for decision support ...
] , but also the growing need for integrative analysis and modeling [9] [10] [11] [12] [13] [14] . ...
doi:10.1186/1471-2105-15-s6-i1
pmid:25078282
pmcid:PMC4140208
fatcat:nlglc5br5ne3tndf3tljwwwgyu
Ontologies and Knowledge Graphs in Oncology Research
2022
Cancers
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Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph ...
Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. ...
The immense potential of ontologies and the knowledge graph paradigm to support cancer research data management and analysis is increasingly recognized by the oncology research community as an essential ...
doi:10.3390/cancers14081906
pmid:35454813
pmcid:PMC9029532
fatcat:t6erzohmvnextkix4infnk7kza
Long-term preservation of biomedical research data
2018
F1000Research
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Genomics and molecular imaging, along with clinical and translational research have transformed biomedical science into a data-intensive scientific endeavor. ...
Preparing and tracking data provenance, using common data elements and biomedical ontologies are important for standardizing the data description, making the interpretation and reuse of data easier. ...
This is a timely scientific undertaking and stands as an important, original contribution to the body of research on data preservation in the context of big data, biomedical research, and data management ...
doi:10.12688/f1000research.16015.1
fatcat:masj3htmw5ginkkbsa53sps7pm
Structured reviews for data and knowledge-driven research
2020
Database: The Journal of Biological Databases and Curation
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Network data files are at: https://github.com/SuLab/ngly1-graph and source code at: https://github.com/SuLab/bioknowledge-reviewer. ...
Data model The data model represents heterogeneous biomedical knowledge using common controlled vocabularies and ontologies in the Life Sciences to identify nodes and edges. ...
These tools facilitate the integration of data from diverse heterogeneous resources: from manual curation to biomedical databases, to experimental data, to expert knowledge. ...
doi:10.1093/database/baaa015
pmid:32283553
pmcid:PMC7153956
fatcat:sk3sogsf2zdktau7d4d5hmjs6u
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