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Biomedical data analysis in translational research

Gyan Bhanot, Michael Biehl, Thomas Villmann, Zühlke
unpublished
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

Alberto Riva, Angelo Nuzzo, Mario Stefanelli, Riccardo Bellazzi
2010 Journal of Biomedical Informatics  
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

J. Saltz, T. Kurc, S. Hastings, S. Langella, S. Oster, D. Ervin, A. Sharma, T. Pan, M. Gurcan, J. Permar, R. Ferreira, P. Payne (+7 others)
2008 Computer  
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  
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

Dixi Louise Strand
2020 Palgrave Communications  
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

Dietrich Rebholz-Schuhmann, Goran Nenadic
2010 Journal of Biomedical Semantics  
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

Daniel Glez-Peña, Fernando Díaz, Jesús M Hernández, Juan M Corchado, Florentino Fdez-Riverola
2009 BMC Bioinformatics  
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

R. Hoehndorf, M. Dumontier, G. V. Gkoutos
2012 Briefings in Bioinformatics  
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

Mahdi Habibi-Koolaee, Leila Shahmoradi, Sharareh R Niakan Kalhori, Hossein Ghannadan, Erfan Younesi
2021 Neurology and Therapy  
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

Rolando Barajas, Brionna Hair, Gabriel Lai, Melissa Rotunno, Marissa M. Shams-White, Elizabeth M. Gillanders, Leah E. Mechanic, Yi Jiang
2021 PLoS ONE  
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

Daniel W. Byrne, Italo Biaggioni, Gordon R. Bernard, Tara T. Helmer, Leslie R. Boone, Jill M. Pulley, Terri Edwards, Robert S. Dittus
2012 Academic Medicine  
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

Andreas Holzinger, Matthias Dehmer, Igor Jurisica
2014 BMC Bioinformatics  
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

Marta Contreiras Silva, Patrícia Eugénio, Daniel Faria, Catia Pesquita
2022 Cancers  
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

Vivek Navale, Matthew McAuliffe
2018 F1000Research  
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  
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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