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MedBioinformatics H2020 EU project

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Research Programme on Biomdical Informatics (GRIB) - IMIM and Universitat Pompeu Fabra
Research Programme on Biomdical Informatics (GRIB) - IMIM and Universitat Pompeu Fabra

1) The MedBioinformatics project aims to develop integrative bioinformatics tools to link genotypes and phenotypes for use by clinical practitioners. 2) These tools include a Disease Biomarker Browser, Disease Trajectory Comorbidity Browser, and Cancer Genome Interpreter. 3) The tools will be tested on case studies of major depression, Alzheimer's disease, and comorbidities between cancer and central nervous system diseases.

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Progress in healthcare and biomedical research by necessity involves taking advantage of the huge amount of clinical data and biological knowledge that already exists and is currently being generated. Many of the efforts done for developing bioinformatics methods and applications have not produced the expected societal impact for different reasons, including: 1) the deficit of integrative approaches that effectively combine different types of data from different sources 2) the lack of active involvement of the potential users (from experimental scientists to healthcare professionals) in the process of creating applications that mine, integrate, analyse and display biomedical information in a way that is immediately understandable and useful ('actionable') by end users. Introduction General objectives Case Studies and Integrative Bioinformatics Tools Expected Impacts MedBioinformatics: Developing Integrative Bioinformatics Applications for Personalized Medicine Miguel A. MAYERa,, Laura I. FURLONGa and Ferran SANZa on behalf of the MedBioinformatics Consortium a Research Programme on Biomedical Informatics, IMIM - Universitat Pompeu Fabra, Barcelona, Spain The general objective of the MedBioinformatics project is the development of integrative bioinformatics tools and software applications autonomously usable by translational scientists and clinical practitioners such as: - New Generation Genotype-Phenotype Explorations (GePhEx) - Disease Biomarker Browser (DBB) - Disease Trajectory Comorbidity Browser (DTCB) - Cancer Genome Interpreter (TCGI) Oncology and Central Nervous System (CNS) disorders are the case studies selected based on their big impact in terms of citizens’ wellbeing, diverse comorbidities and their molecular basis being currently an active area of research. MedBioinformatics is funded by the EU’s Horizon 2020 Research & Innovation Programme 2014-2020, under grant agreement no. 634143. Website: http://www.medbioinformatics.eu The expected impacts are: - to accelerate the translation of the results into clinical research, - to facilitate the widespread dissemination of new bioinformatics methods to maximise the accessibility and utility of biomedical data in research and medicine - to increase commercial products in bioinformatics research and innovation opportunities in the Small & Medium Sized (SME) enterprises-intensive field in Europe. - Algorithms linking genotypes and phenotypes, the integration of databases on known genetic interactions and biomarker data will be integrated in a desktop-able application with steep learning curve used by clinicians. - A Disease Trajectory Comorbidity Browser will provide quantitative risk measures for comorbidities based on disease prevalence data, their related molecular features and phenotypic information. Methods and Tools (in development There are several examples of higher than expected co-occurrence of both kinds of diseases in a given patient: - direct comorbidity - lower than expected co-occurrence (inverse comorbidity or protective effect). GePhEx (Genotype-Phenotype Exploration browser) Will carry out complex multi-variant association tests, to annotate variants and to assess the global susceptibility of an individual to any particular phenotype The study of the association between cancer and CNS diseases (both direct and inverse comorbidity) represent an excellent opportunity to unveil both biological and non-biological connections between CNS diseases and cancer. DBB (Disease Biomarker Browser) will gather information about disease biomarkers from public sources allowing the user to easily assess the translational potential of these biomarkers. DTCB (Disease Trajectory Comorbidity Browser) will alert, given a disease diagnosed to a patient, on possible comorbidities ranked according to different level of evidence. Cancer Genome Interpreter that will integrate updated knowledge in cancer genomics and pharmacogenomics to help oncologists and cancer researchers in the task of interpreting the genome, transcriptome and epigenome of tumours for more accurate decision-making. CNS disorders comprise a variety of diseases, including neurodevelopmental and neurodegenerative ones, caused by genetic, epigenetic and environmental factors. Case studies: - Major Depression (MD): MD without other diseases or addictions and Alcohol-Induced MD - Analysis of the comorbidity of MD with Alzheimer Disease on the basis of the analysis of disease trajectories and biological information. User needs and Usability The distance between fundamental research and clinical practice is still huge. In consequence, careful investigation on user needs and tools usability assessment are critical success factors. EFMI STC 2016. Transforming Healthcare with the Internet of Things European Federation for Medical Informatics, Special Topic Conference. Paris, April 17-19, 2016 Central Nervous System (CNS) disorders and their comorbidities Comorbidities between Cancer and CNS diseases

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MedBioinformatics H2020 EU project

  • 1. Progress in healthcare and biomedical research by necessity involves taking advantage of the huge amount of clinical data and biological knowledge that already exists and is currently being generated. Many of the efforts done for developing bioinformatics methods and applications have not produced the expected societal impact for different reasons, including: 1) the deficit of integrative approaches that effectively combine different types of data from different sources 2) the lack of active involvement of the potential users (from experimental scientists to healthcare professionals) in the process of creating applications that mine, integrate, analyse and display biomedical information in a way that is immediately understandable and useful ('actionable') by end users. Introduction General objectives Case Studies and Integrative Bioinformatics Tools Expected Impacts MedBioinformatics: Developing Integrative Bioinformatics Applications for Personalized Medicine Miguel A. MAYERa,, Laura I. FURLONGa and Ferran SANZa on behalf of the MedBioinformatics Consortium a Research Programme on Biomedical Informatics, IMIM - Universitat Pompeu Fabra, Barcelona, Spain The general objective of the MedBioinformatics project is the development of integrative bioinformatics tools and software applications autonomously usable by translational scientists and clinical practitioners such as: - New Generation Genotype-Phenotype Explorations (GePhEx) - Disease Biomarker Browser (DBB) - Disease Trajectory Comorbidity Browser (DTCB) - Cancer Genome Interpreter (TCGI) Oncology and Central Nervous System (CNS) disorders are the case studies selected based on their big impact in terms of citizens’ wellbeing, diverse comorbidities and their molecular basis being currently an active area of research. MedBioinformatics is funded by the EU’s Horizon 2020 Research & Innovation Programme 2014-2020, under grant agreement no. 634143. Website: http://www.medbioinformatics.eu The expected impacts are: - to accelerate the translation of the results into clinical research, - to facilitate the widespread dissemination of new bioinformatics methods to maximise the accessibility and utility of biomedical data in research and medicine - to increase commercial products in bioinformatics research and innovation opportunities in the Small & Medium Sized (SME) enterprises-intensive field in Europe. - Algorithms linking genotypes and phenotypes, the integration of databases on known genetic interactions and biomarker data will be integrated in a desktop-able application with steep learning curve used by clinicians. - A Disease Trajectory Comorbidity Browser will provide quantitative risk measures for comorbidities based on disease prevalence data, their related molecular features and phenotypic information. Methods and Tools (in development There are several examples of higher than expected co-occurrence of both kinds of diseases in a given patient: - direct comorbidity - lower than expected co-occurrence (inverse comorbidity or protective effect). GePhEx (Genotype-Phenotype Exploration browser) Will carry out complex multi-variant association tests, to annotate variants and to assess the global susceptibility of an individual to any particular phenotype The study of the association between cancer and CNS diseases (both direct and inverse comorbidity) represent an excellent opportunity to unveil both biological and non-biological connections between CNS diseases and cancer. DBB (Disease Biomarker Browser) will gather information about disease biomarkers from public sources allowing the user to easily assess the translational potential of these biomarkers. DTCB (Disease Trajectory Comorbidity Browser) will alert, given a disease diagnosed to a patient, on possible comorbidities ranked according to different level of evidence. Cancer Genome Interpreter that will integrate updated knowledge in cancer genomics and pharmacogenomics to help oncologists and cancer researchers in the task of interpreting the genome, transcriptome and epigenome of tumours for more accurate decision-making. CNS disorders comprise a variety of diseases, including neurodevelopmental and neurodegenerative ones, caused by genetic, epigenetic and environmental factors. Case studies: - Major Depression (MD): MD without other diseases or addictions and Alcohol-Induced MD - Analysis of the comorbidity of MD with Alzheimer Disease on the basis of the analysis of disease trajectories and biological information. User needs and Usability The distance between fundamental research and clinical practice is still huge. In consequence, careful investigation on user needs and tools usability assessment are critical success factors. EFMI STC 2016. Transforming Healthcare with the Internet of Things European Federation for Medical Informatics, Special Topic Conference. Paris, April 17-19, 2016 Central Nervous System (CNS) disorders and their comorbidities Comorbidities between Cancer and CNS diseases