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5 results on '"Burtscher, Felicia"'

1. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Author

Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Puniya, Bhanwar Lal, Naldi, Aurélien, Helikar, Tomáš, Singh, Vidisha, Fernández, Marco Fariñas, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce-de-Leon, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert, Phair, Robert, Perfetto, Livia, Matthews, Lisa, Rex, Devasahayam Arokia Balaya, Orlic-Milacic, Marija, Gomez, Luis Cristobal Monraz, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Saez-Rodriguez, Julio, Dopazo, Joaquin, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Puniya, Bhanwar Lal, Naldi, Aurélien, Helikar, Tomáš, Singh, Vidisha, Fernández, Marco Fariñas, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce-de-Leon, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert, Phair, Robert, Perfetto, Livia, Matthews, Lisa, Rex, Devasahayam Arokia Balaya, Orlic-Milacic, Marija, Gomez, Luis Cristobal Monraz, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Saez-Rodriguez, Julio, Dopazo, Joaquin, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Abstract

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies., Peer Reviewed

Published
2024

2. Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias

Author

Teunissen, Charlotte E., Kimble, Leighann, Bayoumy, Sherif, Bolsewig, Katharina, Burtscher, Felicia, Coppens, Salomé, Das, Shreyasee, Gogishvili, Dea, Gomes, Bárbara Fernandes, de San José, Nerea Gómez, Mavrina, Ekaterina, Meda, Francisco J., Mohaupt, Pablo, Mravinacová, Sára, Waury, Katharina, Wojdała, Anna Lidia, Abeln, Sanne, Chiasserini, Davide, Hirtz, Christophe, Gaetani, Lorenzo, Vermunt, Lisa, Bellomo, Giovanni, Halbgebauer, Steffen, Lehmann, Sylvain, Månberg, Anna, Nilsson, Peter, Otto, Markus, Vanmechelen, Eugeen, Verberk, Inge M.W., Willemse, Eline, Zetterberg, Henrik, Teunissen, Charlotte E., Kimble, Leighann, Bayoumy, Sherif, Bolsewig, Katharina, Burtscher, Felicia, Coppens, Salomé, Das, Shreyasee, Gogishvili, Dea, Gomes, Bárbara Fernandes, de San José, Nerea Gómez, Mavrina, Ekaterina, Meda, Francisco J., Mohaupt, Pablo, Mravinacová, Sára, Waury, Katharina, Wojdała, Anna Lidia, Abeln, Sanne, Chiasserini, Davide, Hirtz, Christophe, Gaetani, Lorenzo, Vermunt, Lisa, Bellomo, Giovanni, Halbgebauer, Steffen, Lehmann, Sylvain, Månberg, Anna, Nilsson, Peter, Otto, Markus, Vanmechelen, Eugeen, Verberk, Inge M.W., Willemse, Eline, and Zetterberg, Henrik

Abstract

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer’s disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluidbased biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluidbased biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Published
2023

3. Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias

Author

Sub AI Technology for Life, Dep Informatica, Teunissen, Charlotte E., Kimble, Leighann, Bayoumy, Sherif, Bolsewig, Katharina, Burtscher, Felicia, Coppens, Salomé, Das, Shreyasee, Gogishvili, Dea, Gomes, Bárbara Fernandes, de San José, Nerea Gómez, Mavrina, Ekaterina, Meda, Francisco J., Mohaupt, Pablo, Mravinacová, Sára, Waury, Katharina, Wojdała, Anna Lidia, Abeln, Sanne, Chiasserini, Davide, Hirtz, Christophe, Gaetani, Lorenzo, Vermunt, Lisa, Bellomo, Giovanni, Halbgebauer, Steffen, Lehmann, Sylvain, Månberg, Anna, Nilsson, Peter, Otto, Markus, Vanmechelen, Eugeen, Verberk, Inge M.W., Willemse, Eline, Zetterberg, Henrik, Sub AI Technology for Life, Dep Informatica, Teunissen, Charlotte E., Kimble, Leighann, Bayoumy, Sherif, Bolsewig, Katharina, Burtscher, Felicia, Coppens, Salomé, Das, Shreyasee, Gogishvili, Dea, Gomes, Bárbara Fernandes, de San José, Nerea Gómez, Mavrina, Ekaterina, Meda, Francisco J., Mohaupt, Pablo, Mravinacová, Sára, Waury, Katharina, Wojdała, Anna Lidia, Abeln, Sanne, Chiasserini, Davide, Hirtz, Christophe, Gaetani, Lorenzo, Vermunt, Lisa, Bellomo, Giovanni, Halbgebauer, Steffen, Lehmann, Sylvain, Månberg, Anna, Nilsson, Peter, Otto, Markus, Vanmechelen, Eugeen, Verberk, Inge M.W., Willemse, Eline, and Zetterberg, Henrik

Published
2023

4. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Author

Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, COVID- Disease Map Community the COVID-19 Disease Map Community, Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, and COVID- Disease Map Community the COVID-19 Disease Map Community

Abstract

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing., Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors., Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19., Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Published
2023

5. Multi-Omics Interdisciplinary Research Integration to Accelerate Dementia Biomarker Development (MIRIADE)

Author

Mavrina, Ekaterina, Kimble, Leighann, Waury, Katharina, Gogishvili, Dea, de San Jose, Nerea Gomez, Das, Shreyasee, Coppens, Salome, Fernandes Gomes, Barbara, Mravinacová, Sára, Wojdala, Anna Lidia, Bolsewig, Katharina, Bayoumy, Sherif, Burtscher, Felicia, Mohaupt, Pablo, Willemse, Eline, Teunissen, Charlotte, consortium, MIRIADE, Mavrina, Ekaterina, Kimble, Leighann, Waury, Katharina, Gogishvili, Dea, de San Jose, Nerea Gomez, Das, Shreyasee, Coppens, Salome, Fernandes Gomes, Barbara, Mravinacová, Sára, Wojdala, Anna Lidia, Bolsewig, Katharina, Bayoumy, Sherif, Burtscher, Felicia, Mohaupt, Pablo, Willemse, Eline, Teunissen, Charlotte, and consortium, MIRIADE

Abstract

Proteomics studies have shown differential expression of numerous proteins in dementias but have rarely led to novel biomarker tests for clinical use. The Marie Curie MIRIADE project is designed to experimentally evaluate development strategies to accelerate the validation and ultimate implementation of novel biomarkers in clinical practice, using proteomics-based biomarker development for main dementias as experimental case studies. We address several knowledge gaps that have been identified in the field. First, there is the technology-translation gap of different technologies for the discovery (e.g., mass spectrometry) and the large-scale validation (e.g., immunoassays) of biomarkers. In addition, there is a limited understanding of conformational states of biomarker proteins in different matrices, which affect the selection of reagents for assay development. In this review, we aim to understand the decisions taken in the initial steps of biomarker development, which is done via an interim narrative update of the work of each ESR subproject. The results describe the decision process to shortlist biomarkers from a proteomics to develop immunoassays or mass spectrometry assays for Alzheimer's disease, Lewy body dementia, and frontotemporal dementia. In addition, we explain the approach to prepare the market implementation of novel biomarkers and assays. Moreover, we describe the development of computational protein state and interaction prediction models to support biomarker development, such as the prediction of epitopes. Lastly, we reflect upon activities involved in the biomarker development process to deduce a best-practice roadmap for biomarker development., QC 20220810

Published
2022
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