[{"ddc":["000"],"related_material":{"link":[{"relation":"software","url":"https://github.com/giang-trinh/trap-mvn"}]},"isi":1,"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"external_id":{"isi":["001027457000060"],"pmid":["37387165"]},"title":"Trap spaces of multi-valued networks: Definition, computation, and applications","ec_funded":1,"doi":"10.1093/bioinformatics/btad262","year":"2023","project":[{"grant_number":"101034413","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020"}],"quality_controlled":"1","oa_version":"Published Version","acknowledgement":"This work was supported by L’Institut Carnot STAR, Marseille, France, and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. [101034413].","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"eissn":["1367-4811"],"issn":["1367-4803"]},"_id":"13263","pmid":1,"article_processing_charge":"Yes","volume":39,"oa":1,"date_updated":"2023-12-13T11:41:52Z","author":[{"first_name":"Van Giang","last_name":"Trinh","full_name":"Trinh, Van Giang"},{"last_name":"Benhamou","full_name":"Benhamou, Belaid","first_name":"Belaid"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","first_name":"Thomas A"},{"first_name":"Samuel","full_name":"Pastva, Samuel","last_name":"Pastva","orcid":"0000-0003-1993-0331","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b"}],"abstract":[{"lang":"eng","text":"Motivation: Boolean networks are simple but efficient mathematical formalism for modelling complex biological systems. However, having only two levels of activation is sometimes not enough to fully capture the dynamics of real-world biological systems. Hence, the need for multi-valued networks (MVNs), a generalization of Boolean networks. Despite the importance of MVNs for modelling biological systems, only limited progress has been made on developing theories, analysis methods, and tools that can support them. In particular, the recent use of trap spaces in Boolean networks made a great impact on the field of systems biology, but there has been no similar concept defined and studied for MVNs to date.\r\n\r\nResults: In this work, we generalize the concept of trap spaces in Boolean networks to that in MVNs. We then develop the theory and the analysis methods for trap spaces in MVNs. In particular, we implement all proposed methods in a Python package called trapmvn. Not only showing the applicability of our approach via a realistic case study, we also evaluate the time efficiency of the method on a large collection of real-world models. The experimental results confirm the time efficiency, which we believe enables more accurate analysis on larger and more complex multi-valued models."}],"citation":{"ieee":"V. G. Trinh, B. Benhamou, T. A. Henzinger, and S. Pastva, “Trap spaces of multi-valued networks: Definition, computation, and applications,” <i>Bioinformatics</i>, vol. 39, no. Supplement_1. Oxford Academic, pp. i513–i522, 2023.","apa":"Trinh, V. G., Benhamou, B., Henzinger, T. A., &#38; Pastva, S. (2023). Trap spaces of multi-valued networks: Definition, computation, and applications. <i>Bioinformatics</i>. Oxford Academic. <a href=\"https://doi.org/10.1093/bioinformatics/btad262\">https://doi.org/10.1093/bioinformatics/btad262</a>","chicago":"Trinh, Van Giang, Belaid Benhamou, Thomas A Henzinger, and Samuel Pastva. “Trap Spaces of Multi-Valued Networks: Definition, Computation, and Applications.” <i>Bioinformatics</i>. Oxford Academic, 2023. <a href=\"https://doi.org/10.1093/bioinformatics/btad262\">https://doi.org/10.1093/bioinformatics/btad262</a>.","mla":"Trinh, Van Giang, et al. “Trap Spaces of Multi-Valued Networks: Definition, Computation, and Applications.” <i>Bioinformatics</i>, vol. 39, no. Supplement_1, Oxford Academic, 2023, pp. i513–22, doi:<a href=\"https://doi.org/10.1093/bioinformatics/btad262\">10.1093/bioinformatics/btad262</a>.","ama":"Trinh VG, Benhamou B, Henzinger TA, Pastva S. Trap spaces of multi-valued networks: Definition, computation, and applications. <i>Bioinformatics</i>. 2023;39(Supplement_1):i513-i522. doi:<a href=\"https://doi.org/10.1093/bioinformatics/btad262\">10.1093/bioinformatics/btad262</a>","short":"V.G. Trinh, B. Benhamou, T.A. Henzinger, S. Pastva, Bioinformatics 39 (2023) i513–i522.","ista":"Trinh VG, Benhamou B, Henzinger TA, Pastva S. 2023. Trap spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics. 39(Supplement_1), i513–i522."},"publication_status":"published","date_created":"2023-07-23T22:01:12Z","file":[{"success":1,"file_id":"13335","creator":"dernst","content_type":"application/pdf","relation":"main_file","date_created":"2023-07-31T11:09:05Z","checksum":"ba3abe1171df1958413b7c7f957f5486","file_name":"2023_Bioinformatics_Trinh.pdf","file_size":641736,"date_updated":"2023-07-31T11:09:05Z","access_level":"open_access"}],"department":[{"_id":"ToHe"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Oxford Academic","article_type":"original","date_published":"2023-06-30T00:00:00Z","month":"06","page":"i513-i522","file_date_updated":"2023-07-31T11:09:05Z","publication":"Bioinformatics","issue":"Supplement_1","status":"public","intvolume":"        39","type":"journal_article","day":"30"},{"issue":"4","publication":"Bioinformatics","file_date_updated":"2023-05-02T07:39:04Z","day":"03","type":"journal_article","intvolume":"        39","status":"public","has_accepted_license":"1","department":[{"_id":"ToHe"}],"date_created":"2023-04-30T22:01:05Z","file":[{"file_name":"2023_Bioinformatics_Benes.pdf","file_size":478740,"date_created":"2023-05-02T07:39:04Z","checksum":"2cb90ddf781baefddf47eac4b54e2a03","date_updated":"2023-05-02T07:39:04Z","access_level":"open_access","success":1,"content_type":"application/pdf","relation":"main_file","file_id":"12886","creator":"dernst"}],"month":"04","date_published":"2023-04-03T00:00:00Z","article_type":"original","publisher":"Oxford Academic","scopus_import":"1","language":[{"iso":"eng"}],"volume":39,"date_updated":"2023-08-01T14:27:28Z","oa":1,"article_processing_charge":"No","pmid":1,"_id":"12876","publication_identifier":{"eissn":["1367-4811"]},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"This work was partially supported by GACR [grant No. GA22-10845S]; and Grant Agency of Masaryk University [grant No. MUNI/G/1771/2020]. This work was partially supported by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie [Grant Agreement No. 101034413 to S.P.].","oa_version":"Published Version","project":[{"grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020"}],"quality_controlled":"1","publication_status":"published","citation":{"chicago":"Beneš, Nikola, Luboš Brim, Ondřej Huvar, Samuel Pastva, and David Šafránek. “Boolean Network Sketches: A Unifying Framework for Logical Model Inference.” <i>Bioinformatics</i>. Oxford Academic, 2023. <a href=\"https://doi.org/10.1093/bioinformatics/btad158\">https://doi.org/10.1093/bioinformatics/btad158</a>.","apa":"Beneš, N., Brim, L., Huvar, O., Pastva, S., &#38; Šafránek, D. (2023). Boolean network sketches: A unifying framework for logical model inference. <i>Bioinformatics</i>. Oxford Academic. <a href=\"https://doi.org/10.1093/bioinformatics/btad158\">https://doi.org/10.1093/bioinformatics/btad158</a>","ieee":"N. Beneš, L. Brim, O. Huvar, S. Pastva, and D. Šafránek, “Boolean network sketches: A unifying framework for logical model inference,” <i>Bioinformatics</i>, vol. 39, no. 4. Oxford Academic, 2023.","short":"N. Beneš, L. Brim, O. Huvar, S. Pastva, D. Šafránek, Bioinformatics 39 (2023).","ista":"Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. 2023. Boolean network sketches: A unifying framework for logical model inference. Bioinformatics. 39(4), btad158.","mla":"Beneš, Nikola, et al. “Boolean Network Sketches: A Unifying Framework for Logical Model Inference.” <i>Bioinformatics</i>, vol. 39, no. 4, btad158, Oxford Academic, 2023, doi:<a href=\"https://doi.org/10.1093/bioinformatics/btad158\">10.1093/bioinformatics/btad158</a>.","ama":"Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. Boolean network sketches: A unifying framework for logical model inference. <i>Bioinformatics</i>. 2023;39(4). doi:<a href=\"https://doi.org/10.1093/bioinformatics/btad158\">10.1093/bioinformatics/btad158</a>"},"abstract":[{"lang":"eng","text":"Motivation: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only.\r\n\r\nResults: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network’s topology and the update logic (obtained through, e.g. a biological knowledge base or a literature search), as well as further assumptions about the properties of the network’s transitions (e.g. the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an ‘initial’ sketch, which is extended by adding restrictions representing experimental data to a ‘data-informed’ sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data."}],"author":[{"full_name":"Beneš, Nikola","last_name":"Beneš","first_name":"Nikola"},{"full_name":"Brim, Luboš","last_name":"Brim","first_name":"Luboš"},{"first_name":"Ondřej","last_name":"Huvar","full_name":"Huvar, Ondřej"},{"first_name":"Samuel","last_name":"Pastva","full_name":"Pastva, Samuel","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b"},{"first_name":"David","full_name":"Šafránek, David","last_name":"Šafránek"}],"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"isi":1,"article_number":"btad158","related_material":{"link":[{"url":"https://doi.org/10.5281/zenodo.7688740","relation":"software"}]},"ddc":["000"],"doi":"10.1093/bioinformatics/btad158","year":"2023","ec_funded":1,"title":"Boolean network sketches: A unifying framework for logical model inference","external_id":{"pmid":["37004199"],"isi":["000976610800001"]}},{"department":[{"_id":"FrLo"}],"date_created":"2023-08-21T12:28:20Z","month":"12","date_published":"2020-12-01T00:00:00Z","article_type":"original","scopus_import":"1","publisher":"Oxford University Press","language":[{"iso":"eng"}],"publication":"Bioinformatics","issue":"Supplement_2","page":"i919-i927","day":"01","type":"journal_article","intvolume":"        36","status":"public","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1093/bioinformatics/btaa843"}],"related_material":{"link":[{"url":"https://github.com/ratschlab/scim","relation":"software"}]},"doi":"10.1093/bioinformatics/btaa843","year":"2020","title":"SCIM: Universal single-cell matching with unpaired feature sets","external_id":{"pmid":["33381818"]},"article_processing_charge":"No","volume":36,"date_updated":"2023-09-11T10:21:00Z","oa":1,"publication_identifier":{"eissn":["1367-4811"]},"extern":"1","_id":"14125","pmid":1,"oa_version":"Published Version","quality_controlled":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Stark, Stefan G., et al. “SCIM: Universal Single-Cell Matching with Unpaired Feature Sets.” <i>Bioinformatics</i>, vol. 36, no. Supplement_2, Oxford University Press, 2020, pp. i919–27, doi:<a href=\"https://doi.org/10.1093/bioinformatics/btaa843\">10.1093/bioinformatics/btaa843</a>.","ama":"Stark SG, Ficek J, Locatello F, et al. SCIM: Universal single-cell matching with unpaired feature sets. <i>Bioinformatics</i>. 2020;36(Supplement_2):i919-i927. doi:<a href=\"https://doi.org/10.1093/bioinformatics/btaa843\">10.1093/bioinformatics/btaa843</a>","short":"S.G. Stark, J. Ficek, F. Locatello, X. Bonilla, S. Chevrier, F. Singer, R. Aebersold, F.S. Al-Quaddoomi, J. Albinus, I. Alborelli, S. Andani, P.-O. Attinger, M. Bacac, D. Baumhoer, B. Beck-Schimmer, N. Beerenwinkel, C. Beisel, L. Bernasconi, A. Bertolini, B. Bodenmiller, X. Bonilla, R. Casanova, S. Chevrier, N. Chicherova, M. D’Costa, E. Danenberg, N. Davidson, M.-A.D. gan, R. Dummer, S. Engler, M. Erkens, K. Eschbach, C. Esposito, A. Fedier, P. Ferreira, J. Ficek, A.L. Frei, B. Frey, S. Goetze, L. Grob, G. Gut, D. Günther, M. Haberecker, P. Haeuptle, V. Heinzelmann-Schwarz, S. Herter, R. Holtackers, T. Huesser, A. Irmisch, F. Jacob, A. Jacobs, T.M. Jaeger, K. Jahn, A.R. James, P.M. Jermann, A. Kahles, A. Kahraman, V.H. Koelzer, W. Kuebler, J. Kuipers, C.P. Kunze, C. Kurzeder, K.-V. Lehmann, M. Levesque, S. Lugert, G. Maass, M. Manz, P. Markolin, J. Mena, U. Menzel, J.M. Metzler, N. Miglino, E.S. Milani, H. Moch, S. Muenst, R. Murri, C.K. Ng, S. Nicolet, M. Nowak, P.G. Pedrioli, L. Pelkmans, S. Piscuoglio, M. Prummer, M. Ritter, C. Rommel, M.L. Rosano-González, G. Rätsch, N. Santacroce, J.S. del Castillo, R. Schlenker, P.C. Schwalie, S. Schwan, T. Schär, G. Senti, F. Singer, S. Sivapatham, B. Snijder, B. Sobottka, V.T. Sreedharan, S. Stark, D.J. Stekhoven, A.P. Theocharides, T.M. Thomas, M. Tolnay, V. Tosevski, N.C. Toussaint, M.A. Tuncel, M. Tusup, A.V. Drogen, M. Vetter, T. Vlajnic, S. Weber, W.P. Weber, R. Wegmann, M. Weller, F. Wendt, N. Wey, A. Wicki, B. Wollscheid, S. Yu, J. Ziegler, M. Zimmermann, M. Zoche, G. Zuend, G. Rätsch, K.-V. Lehmann, Bioinformatics 36 (2020) i919–i927.","ista":"Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.","ieee":"S. G. Stark <i>et al.</i>, “SCIM: Universal single-cell matching with unpaired feature sets,” <i>Bioinformatics</i>, vol. 36, no. Supplement_2. Oxford University Press, pp. i919–i927, 2020.","apa":"Stark, S. G., Ficek, J., Locatello, F., Bonilla, X., Chevrier, S., Singer, F., … Lehmann, K.-V. (2020). SCIM: Universal single-cell matching with unpaired feature sets. <i>Bioinformatics</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/bioinformatics/btaa843\">https://doi.org/10.1093/bioinformatics/btaa843</a>","chicago":"Stark, Stefan G, Joanna Ficek, Francesco Locatello, Ximena Bonilla, Stéphane Chevrier, Franziska Singer, Rudolf Aebersold, et al. “SCIM: Universal Single-Cell Matching with Unpaired Feature Sets.” <i>Bioinformatics</i>. Oxford University Press, 2020. <a href=\"https://doi.org/10.1093/bioinformatics/btaa843\">https://doi.org/10.1093/bioinformatics/btaa843</a>."},"publication_status":"published","abstract":[{"text":"Motivation: Recent technological advances have led to an increase in the production and availability of single-cell data. The ability to integrate a set of multi-technology measurements would allow the identification of biologically or clinically meaningful observations through the unification of the perspectives afforded by each technology. In most cases, however, profiling technologies consume the used cells and thus pairwise correspondences between datasets are lost. Due to the sheer size single-cell datasets can acquire, scalable algorithms that are able to universally match single-cell measurements carried out in one cell to its corresponding sibling in another technology are needed.\r\nResults: We propose Single-Cell data Integration via Matching (SCIM), a scalable approach to recover such correspondences in two or more technologies. SCIM assumes that cells share a common (low-dimensional) underlying structure and that the underlying cell distribution is approximately constant across technologies. It constructs a technology-invariant latent space using an autoencoder framework with an adversarial objective. Multi-modal datasets are integrated by pairing cells across technologies using a bipartite matching scheme that operates on the low-dimensional latent representations. We evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell matches derived by SCIM reflect the same pseudotime on the simulated dataset. Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample and a human bone marrow sample, where we pair cells from a scRNA dataset to their sibling cells in a CyTOF dataset achieving 90% and 78% cell-matching accuracy for each one of the samples, respectively.","lang":"eng"}],"keyword":["Computational Mathematics","Computational Theory and Mathematics","Computer Science Applications","Molecular Biology","Biochemistry","Statistics and Probability"],"author":[{"first_name":"Stefan G","full_name":"Stark, Stefan G","last_name":"Stark"},{"full_name":"Ficek, Joanna","last_name":"Ficek","first_name":"Joanna"},{"first_name":"Francesco","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"first_name":"Ximena","last_name":"Bonilla","full_name":"Bonilla, Ximena"},{"first_name":"Stéphane","full_name":"Chevrier, Stéphane","last_name":"Chevrier"},{"last_name":"Singer","full_name":"Singer, Franziska","first_name":"Franziska"},{"last_name":"Aebersold","full_name":"Aebersold, Rudolf","first_name":"Rudolf"},{"first_name":"Faisal S","last_name":"Al-Quaddoomi","full_name":"Al-Quaddoomi, Faisal S"},{"first_name":"Jonas","last_name":"Albinus","full_name":"Albinus, Jonas"},{"full_name":"Alborelli, Ilaria","last_name":"Alborelli","first_name":"Ilaria"},{"first_name":"Sonali","last_name":"Andani","full_name":"Andani, Sonali"},{"first_name":"Per-Olof","last_name":"Attinger","full_name":"Attinger, Per-Olof"},{"first_name":"Marina","full_name":"Bacac, Marina","last_name":"Bacac"},{"full_name":"Baumhoer, Daniel","last_name":"Baumhoer","first_name":"Daniel"},{"first_name":"Beatrice","full_name":"Beck-Schimmer, Beatrice","last_name":"Beck-Schimmer"},{"first_name":"Niko","last_name":"Beerenwinkel","full_name":"Beerenwinkel, Niko"},{"first_name":"Christian","full_name":"Beisel, Christian","last_name":"Beisel"},{"first_name":"Lara","full_name":"Bernasconi, Lara","last_name":"Bernasconi"},{"first_name":"Anne","full_name":"Bertolini, Anne","last_name":"Bertolini"},{"full_name":"Bodenmiller, Bernd","last_name":"Bodenmiller","first_name":"Bernd"},{"first_name":"Ximena","full_name":"Bonilla, Ximena","last_name":"Bonilla"},{"first_name":"Ruben","last_name":"Casanova","full_name":"Casanova, Ruben"},{"last_name":"Chevrier","full_name":"Chevrier, Stéphane","first_name":"Stéphane"},{"last_name":"Chicherova","full_name":"Chicherova, Natalia","first_name":"Natalia"},{"full_name":"D'Costa, Maya","last_name":"D'Costa","first_name":"Maya"},{"last_name":"Danenberg","full_name":"Danenberg, Esther","first_name":"Esther"},{"last_name":"Davidson","full_name":"Davidson, Natalie","first_name":"Natalie"},{"last_name":"gan","full_name":"gan, Monica-Andreea Dră","first_name":"Monica-Andreea Dră"},{"last_name":"Dummer","full_name":"Dummer, Reinhard","first_name":"Reinhard"},{"first_name":"Stefanie","last_name":"Engler","full_name":"Engler, Stefanie"},{"last_name":"Erkens","full_name":"Erkens, Martin","first_name":"Martin"},{"full_name":"Eschbach, Katja","last_name":"Eschbach","first_name":"Katja"},{"first_name":"Cinzia","full_name":"Esposito, Cinzia","last_name":"Esposito"},{"full_name":"Fedier, André","last_name":"Fedier","first_name":"André"},{"first_name":"Pedro","last_name":"Ferreira","full_name":"Ferreira, Pedro"},{"first_name":"Joanna","full_name":"Ficek, Joanna","last_name":"Ficek"},{"full_name":"Frei, Anja L","last_name":"Frei","first_name":"Anja L"},{"first_name":"Bruno","last_name":"Frey","full_name":"Frey, Bruno"},{"first_name":"Sandra","last_name":"Goetze","full_name":"Goetze, Sandra"},{"first_name":"Linda","full_name":"Grob, Linda","last_name":"Grob"},{"full_name":"Gut, Gabriele","last_name":"Gut","first_name":"Gabriele"},{"first_name":"Detlef","full_name":"Günther, Detlef","last_name":"Günther"},{"last_name":"Haberecker","full_name":"Haberecker, Martina","first_name":"Martina"},{"last_name":"Haeuptle","full_name":"Haeuptle, Pirmin","first_name":"Pirmin"},{"first_name":"Viola","last_name":"Heinzelmann-Schwarz","full_name":"Heinzelmann-Schwarz, Viola"},{"full_name":"Herter, Sylvia","last_name":"Herter","first_name":"Sylvia"},{"first_name":"Rene","full_name":"Holtackers, Rene","last_name":"Holtackers"},{"first_name":"Tamara","full_name":"Huesser, Tamara","last_name":"Huesser"},{"full_name":"Irmisch, Anja","last_name":"Irmisch","first_name":"Anja"},{"first_name":"Francis","full_name":"Jacob, Francis","last_name":"Jacob"},{"first_name":"Andrea","full_name":"Jacobs, Andrea","last_name":"Jacobs"},{"last_name":"Jaeger","full_name":"Jaeger, Tim M","first_name":"Tim M"},{"last_name":"Jahn","full_name":"Jahn, Katharina","first_name":"Katharina"},{"first_name":"Alva R","full_name":"James, Alva R","last_name":"James"},{"last_name":"Jermann","full_name":"Jermann, Philip M","first_name":"Philip M"},{"first_name":"André","last_name":"Kahles","full_name":"Kahles, André"},{"first_name":"Abdullah","last_name":"Kahraman","full_name":"Kahraman, Abdullah"},{"first_name":"Viktor H","last_name":"Koelzer","full_name":"Koelzer, Viktor H"},{"first_name":"Werner","last_name":"Kuebler","full_name":"Kuebler, Werner"},{"full_name":"Kuipers, Jack","last_name":"Kuipers","first_name":"Jack"},{"first_name":"Christian P","full_name":"Kunze, Christian P","last_name":"Kunze"},{"first_name":"Christian","last_name":"Kurzeder","full_name":"Kurzeder, Christian"},{"full_name":"Lehmann, Kjong-Van","last_name":"Lehmann","first_name":"Kjong-Van"},{"last_name":"Levesque","full_name":"Levesque, Mitchell","first_name":"Mitchell"},{"last_name":"Lugert","full_name":"Lugert, Sebastian","first_name":"Sebastian"},{"full_name":"Maass, Gerd","last_name":"Maass","first_name":"Gerd"},{"full_name":"Manz, Markus","last_name":"Manz","first_name":"Markus"},{"full_name":"Markolin, 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