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33 results on '"Firth, Mike A"'

2. Epigenetic modulators link mitochondrial redox homeostasis to cardiac function in a sex-dependent manner

Author

ElBeck, Zaher, Hossain, Mohammad Bakhtiar, Siga, Humam, Oskolkov, Nikolay, Karlsson, Fredrik, Lindgren, Julia, Walentinsson, Anna, Koppenhöfer, Dominique, Jarvis, Rebecca, Bürli, Roland, Jamier, Tanguy, Franssen, Elske, Firth, Mike, Degasperi, Andrea, Bendtsen, Claus, Menzies, Robert I., Streckfuss-Bömeke, Katrin, Kohlhaas, Michael, Nickel, Alexander G., Lund, Lars H., Maack, Christoph, Végvári, Ákos, and Betsholtz, Christer

Published
2024
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4. An aptamer-mediated base editing platform for simultaneous knockin and multiple gene knockout for allogeneic CAR-T cells generation

Author

Porreca, Immacolata, Blassberg, Robert, Harbottle, Jennifer, Joubert, Bronwyn, Mielczarek, Olga, Stombaugh, Jesse, Hemphill, Kevin, Sumner, Jonathan, Pazeraitis, Deividas, Touza, Julia Liz, Francescatto, Margherita, Firth, Mike, Selmi, Tommaso, Collantes, Juan Carlos, Strezoska, Zaklina, Taylor, Benjamin, Jin, Shengkan, Wiggins, Ceri M., van Brabant Smith, Anja, and Lambourne, John J.

Published
2024
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5. A Type II-B Cas9 nuclease with minimized off-targets and reduced chromosomal translocations in vivo

Author

Bestas, Burcu, Wimberger, Sandra, Degtev, Dmitrii, Madsen, Alexandra, Rottner, Antje K., Karlsson, Fredrik, Naumenko, Sergey, Callahan, Megan, Touza, Julia Liz, Francescatto, Margherita, Möller, Carl Ivar, Badertscher, Lukas, Li, Songyuan, Cerboni, Silvia, Selfjord, Niklas, Ericson, Elke, Gordon, Euan, Firth, Mike, Chylinski, Krzysztof, Taheri-Ghahfarokhi, Amir, Bohlooly-Y, Mohammad, Snowden, Mike, Pangalos, Menelaos, Nuttall, Barrett, Akcakaya, Pinar, Sienski, Grzegorz, and Maresca, Marcello

Published
2023
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6. Simultaneous inhibition of DNA-PK and Polϴ improves integration efficiency and precision of genome editing

Author

Wimberger, Sandra, Akrap, Nina, Firth, Mike, Brengdahl, Johan, Engberg, Susanna, Schwinn, Marie K., Slater, Michael R., Lundin, Anders, Hsieh, Pei-Pei, Li, Songyuan, Cerboni, Silvia, Sumner, Jonathan, Bestas, Burcu, Schiffthaler, Bastian, Magnusson, Björn, Di Castro, Silvio, Iyer, Preeti, Bohlooly-Y, Mohammad, Machleidt, Thomas, Rees, Steve, Engkvist, Ola, Norris, Tyrell, Cadogan, Elaine B., Forment, Josep V., Šviković, Saša, Akcakaya, Pinar, Taheri-Ghahfarokhi, Amir, and Maresca, Marcello

Published
2023
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8. Correction of a urea cycle defect after ex vivo gene editing of human hepatocytes

Author

Zabulica, Mihaela, Srinivasan, Raghuraman C., Akcakaya, Pinar, Allegri, Gabriella, Bestas, Burcu, Firth, Mike, Hammarstedt, Christina, Jakobsson, Tomas, Jakobsson, Towe, Ellis, Ewa, Jorns, Carl, Makris, Georgios, Scherer, Tanja, Rimann, Nicole, van Zuydam, Natalie R., Gramignoli, Roberto, Forslöw, Anna, Engberg, Susanna, Maresca, Marcello, Rooyackers, Olav, Thöny, Beat, Häberle, Johannes, Rosen, Barry, and Strom, Stephen C.

Published
2021
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12. Universal toxin-based selection for precise genome engineering in human cells

Author

Li, Songyuan, Akrap, Nina, Cerboni, Silvia, Porritt, Michelle J., Wimberger, Sandra, Lundin, Anders, Möller, Carl, Firth, Mike, Gordon, Euan, Lazovic, Bojana, Sieńska, Aleksandra, Pane, Luna Simona, Coelho, Matthew A., Ciotta, Giovanni, Pellegrini, Giovanni, Sini, Marcella, Xu, Xiufeng, Mitra, Suman, Bohlooly-Y, Mohammad, Taylor, Benjamin J. M., Sienski, Grzegorz, and Maresca, Marcello

Published
2021
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13. Author Correction: Universal toxin-based selection for precise genome engineering in human cells

Author

Li, Songyuan, Akrap, Nina, Cerboni, Silvia, Porritt, Michelle J., Wimberger, Sandra, Lundin, Anders, Möller, Carl, Firth, Mike, Gordon, Euan, Lazovic, Bojana, Sieńska, Aleksandra, Pane, Luna Simona, Coelho, Matthew A., Ciotta, Giovanni, Pellegrini, Giovanni, Sini, Marcella, Xu, Xiufeng, Mitra, Suman, Bohlooly-Y, Mohammad, Taylor, Benjamin J. M., Sienski, Grzegorz, and Maresca, Marcello

Published
2021
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17. In vivo CRISPR editing with no detectable genome-wide off-target mutations

Author

Akcakaya, Pinar, Bobbin, Maggie L., Guo, Jimmy A., Malagon-Lopez, Jose, Clement, Kendell, Garcia, Sara P., Fellows, Mick D., Porritt, Michelle J., Firth, Mike A., Carreras, Alba, Baccega, Tania, Seeliger, Frank, Bjursell, Mikael, Tsai, Shengdar Q., Nguyen, Nhu T., Nitsch, Roberto, Mayr, Lorenz M., Pinello, Luca, Bohlooly-Y, Mohammad, Aryee, Martin J., Maresca, Marcello, and Joung, J. Keith

Published
2018
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19. 11th German Conference on Chemoinformatics (GCC 2015): Fulda, Germany. 8–10 November 2015

Author

Fechner, Uli, de Graaf, Chris, Torda, Andrew E., Güssregen, Stefan, Evers, Andreas, Matter, Hans, Hessler, Gerhard, Richmond, Nicola J., Schmidtke, Peter, Segler, Marwin H. S., Waller, Mark P., Pleik, Stefanie, Shea, Joan-Emma, Levine, Zachary, Mullen, Ryan, van den Broek, Karina, Epple, Matthias, Kuhn, Hubert, Truszkowski, Andreas, Zielesny, Achim, Fraaije, Johannes (Hans), Gracia, Ruben Serral, Kast, Stefan M., Bulusu, Krishna C., Bender, Andreas, Yosipof, Abraham, Nahum, Oren, Senderowitz, Hanoch, Krotzky, Timo, Schulz, Robert, Wolber, Gerhard, Bietz, Stefan, Rarey, Matthias, Zimmermann, Markus O., Lange, Andreas, Ruff, Manuel, Heidrich, Johannes, Onlia, Ionut, Exner, Thomas E., Boeckler, Frank M., Bermudez, Marcel, Firaha, Dzmitry S., Hollóczki, Oldamur, Kirchner, Barbara, Tautermann, Christofer S., Volkamer, Andrea, Eid, Sameh, Turk, Samo, Rippmann, Friedrich, Fulle, Simone, Saleh, Noureldin, Saladino, Giorgio, Gervasio, Francesco L., Haensele, Elke, Banting, Lee, Whitley, David C., Oliveira Santos, Jana Sopkova-de, Bureau, Ronan, Clark, Timothy, Sandmann, Achim, Lanig, Harald, Kibies, Patrick, Heil, Jochen, Hoffgaard, Franziska, Frach, Roland, Engel, Julian, Smith, Steven, Basu, Debjit, Rauh, Daniel, Kohlbacher, Oliver, Boeckler, Frank M., Essex, Jonathan W., Bodnarchuk, Michael S., Ross, Gregory A., Finkelmann, Arndt R., Göller, Andreas H., Schneider, Gisbert, Husch, Tamara, Schütter, Christoph, Balducci, Andrea, Korth, Martin, Ntie-Kang, Fidele, Günther, Stefan, Sippl, Wolfgang, Mbaze, Luc Meva’a, Ntie-Kang, Fidele, Simoben, Conrad V., Lifongo, Lydia L., Ntie-Kang, Fidele, Judson, Philip, Barilla, Jiří, Lokajíček, Miloš V., Pisaková, Hana, Simr, Pavel, Kireeva, Natalia, Petrov, Alexandre, Ostroumov, Denis, Solovev, Vitaly P., Pervov, Vladislav S., Friedrich, Nils-Ole, Sommer, Kai, Rarey, Matthias, Kirchmair, Johannes, Proschak, Eugen, Weber, Julia, Moser, Daniel, Kalinowski, Lena, Achenbach, Janosch, Mackey, Mark, Cheeseright, Tim, Renner, Gerrit, Renner, Gerrit, Schmidt, Torsten C., Schram, Jürgen, Egelkraut-Holtus, Marion, van Oeyen, Albert, Kalliokoski, Tuomo, Fourches, Denis, Ibezim, Akachukwu, Mbah, Chika J., Adikwu, Umale M., Nwodo, Ngozi J., Steudle, Alexander, Masek, Brian B., Nagy, Stephan, Baker, David, Soltanshahi, Fred, Dorfman, Roman, Dubrucq, Karen, Patel, Hitesh, Koch, Oliver, Mrugalla, Florian, Kast, Stefan M., Ain, Qurrat U., Fuchs, Julian E., Owen, Robert M., Omoto, Kiyoyuki, Torella, Rubben, Pryde, David C., Glen, Robert, Bender, Andreas, Hošek, Petr, Spiwok, Vojtěch, Mervin, Lewis H., Barrett, Ian, Firth, Mike, Murray, David C., McWilliams, Lisa, Cao, Qing, Engkvist, Ola, Warszycki, Dawid, Śmieja, Marek, Bojarski, Andrzej J., Aniceto, Natalia, Freitas, Alex, Ghafourian, Taravat, Herrmann, Guido, Eigner-Pitto, Valentina, Naß, Alexandra, Kurczab, Rafał, Bojarski, Andrzej J., Lange, Andreas, Günther, Marcel B., Hennig, Susanne, Büttner, Felix M., Schall, Christoph, Sievers-Engler, Adrian, Ansideri, Francesco, Koch, Pierre, Stehle, Thilo, Laufer, Stefan, Böckler, Frank M., Zdrazil, Barbara, Montanari, Floriane, Ecker, Gerhard F., Grebner, Christoph, Hogner, Anders, Ulander, Johan, Edman, Karl, Guallar, Victor, Tyrchan, Christian, Ulander, Johan, Tyrchan, Christian, Klute, Wolfgang, Bergström, Fredrik, Kramer, Christian, Nguyen, Quoc Dat, Frach, Roland, Kibies, Patrick, Strohfeldt, Steven, Böttcher, Saraphina, Pongratz, Tim, Horinek, Dominik, Kast, Stefan M., Rupp, Bernd, Al-Yamori, Raed, Lisurek, Michael, Kühne, Ronald, Furtado, Filipe, van den Broek, Karina, Wessjohann, Ludger, Mathea, Miriam, Baumann, Knut, Mohamad-Zobir, Siti Zuraidah, Fu, Xianjun, Fan, Tai-Ping, Bender, Andreas, Kuhn, Maximilian A., Sotriffer, Christoph A., Zoufir, Azedine, Li, Xitong, Mervin, Lewis, Berg, Ellen, Polokoff, Mark, Ihlenfeldt, Wolf D., Ihlenfeldt, Wolf D., Pretzel, Jette, Alhalabi, Zayan, Fraczkiewicz, Robert, Waldman, Marvin, Clark, Robert D., Shaikh, Neem, Garg, Prabha, Kos, Alexander, Himmler, Hans-Jürgen, Sandmann, Achim, Jardin, Christophe, Sticht, Heinrich, Steinbrecher, Thomas B., Dahlgren, Markus, Cappel, Daniel, Lin, Teng, Wang, Lingle, Krilov, Goran, Abel, Robert, Friesner, Richard, Sherman, Woody, Pöhner, Ina A., Panecka, Joanna, Wade, Rebecca C., Bietz, Stefan, Schomburg, Karen T., Hilbig, Matthias, Rarey, Matthias, Jäger, Christian, Wieczorek, Vivien, Westerhoff, Lance M., Borbulevych, Oleg Y., Demuth, Hans-Ulrich, Buchholz, Mirko, Schmidt, Denis, Rickmeyer, Thomas, Krotzky, Timo, Kolb, Peter, Mittal, Sumit, Sánchez-García, Elsa, Nogueira, Mauro S., Oliveira, Tiago B., da Costa, Fernando B., and Schmidt, Thomas J.

Published
2016
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20. Engineered Cas9 extracellular vesicles as a novel gene editing tool.

Author

Osteikoetxea, Xabier, Silva, Andreia, Lázaro‐Ibáñez, Elisa, Salmond, Nikki, Shatnyeva, Olga, Stein, Josia, Schick, Jan, Wren, Stephen, Lindgren, Julia, Firth, Mike, Madsen, Alexandra, Mayr, Lorenz M., Overman, Ross, Davies, Rick, and Dekker, Niek

Subjects
EXTRACELLULAR vesicles, GENOME editing, GENE delivery techniques, GEL permeation chromatography, TRANSMISSION electron microscopy, WESTERN immunoblotting, CRISPRS
Abstract

Extracellular vesicles (EVs) have shown promise as biological delivery vehicles, but therapeutic applications require efficient cargo loading. Here, we developed new methods for CRISPR/Cas9 loading into EVs through reversible heterodimerization of Cas9‐fusions with EV sorting partners. Cas9‐loaded EVs were collected from engineered Expi293F cells using standard methodology, characterized using nanoparticle tracking analysis, western blotting, and transmission electron microscopy and analysed for CRISPR/Cas9‐mediated functional gene editing in a Cre‐reporter cellular assay. Light‐induced dimerization using Cryptochrome 2 combined with CD9 or a Myristoylation‐Palmitoylation‐Palmitoylation lipid modification resulted in efficient loading with approximately 25 Cas9 molecules per EV and high functional delivery with 51% gene editing of the Cre reporter cassette in HEK293 and 25% in HepG2 cells, respectively. This approach was also effective for targeting knock‐down of the therapeutically relevant PCSK9 gene with 6% indel efficiency in HEK293. Cas9 transfer was detergent‐sensitive and associated with the EV fractions after size exclusion chromatography, indicative of EV‐mediated transfer. Considering the advantages of EVs over other delivery vectors we envision that this study will prove useful for a range of therapeutic applications, including CRISPR/Cas9 mediated genome editing. [ABSTRACT FROM AUTHOR]

Published
2022
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21. Understanding Cytotoxicity and Cytostaticity in a High-Throughput Screening Collection

Author

Mervin, Lewis H, Cao, Qing, Barrett, Ian P, Firth, Mike A, Murray, David, McWilliams, Lisa, Haddrick, Malcolm, Wigglesworth, Mark, Engkvist, Ola, Bender, Andreas, Mervin, Lewis [0000-0002-7271-0824], Bender, Andreas [0000-0002-6683-7546], and Apollo - University of Cambridge Repository

Subjects
Cell Survival, Cell Cycle, Humans, Cell Line, High-Throughput Screening Assays
Abstract

While mechanisms of cytotoxicity and cytostaticity have been studied extensively from the biological side, relatively little is currently understood regarding areas of chemical space leading to cytotoxicity and cytostasis in large compound collections. Predicting and rationalizing potential adverse mechanism-of-actions (MoAs) of small molecules is however crucial for screening library design, given the link of even low level cytotoxicity and adverse events observed in man. In this study, we analyzed results from a cell-based cytotoxicity screening cascade, comprising 296 970 nontoxic, 5784 cytotoxic and cytostatic, and 2327 cytostatic-only compounds evaluated on the THP-1 cell-line. We employed an in silico MoA analysis protocol, utilizing 9.5 million active and 602 million inactive bioactivity points to generate target predictions, annotate predicted targets with pathways, and calculate enrichment metrics to highlight targets and pathways. Predictions identify known mechanisms for the top ranking targets and pathways for both phenotypes after review and indicate that while processes involved in cytotoxicity versus cytostaticity seem to overlap, differences between both phenotypes seem to exist to some extent. Cytotoxic predictions highlight many kinases, including the potentially novel cytotoxicity-related target STK32C, while cytostatic predictions outline targets linked with response to DNA damage, metabolism, and cytoskeletal machinery. Fragment analysis was also employed to generate a library of toxicophores to improve general understanding of the chemical features driving toxicity. We highlight substructures with potential kinase-dependent and kinase-independent mechanisms of toxicity. We also trained a cytotoxic classification model on proprietary and public compound readouts, and prospectively validated these on 988 novel compounds comprising difficult and trivial testing instances, to establish the applicability domain of models. The proprietary model performed with precision and recall scores of 77.9% and 83.8%, respectively. The MoA results and top ranking substructures with accompanying MoA predictions are available as a platform to assess screening collections.

Published
2016

23. Orthologue chemical space and its influence on target prediction.

Author

Mervin, Lewis H, Bulusu, Krishna C, Kalash, Leen, Afzal, Avid M, Svensson, Fredrik, Firth, Mike A, Barrett, Ian, Engkvist, Ola, and Bender, Andreas

Subjects
DATA mining, TEXT mining, BIOINFORMATICS, COMPUTATIONAL biology, SYSTEMS biology
Abstract

Motivation: In silico approaches often fail to utilize bioactivity data available for orthologous targets due to insufficient evidence highlighting the benefit for such an approach. Deeper investigation into orthologue chemical space and its influence toward expanding compound and target coverage is necessary to improve the confidence in this practice. Results: Here we present analysis of the orthologue chemical space in ChEMBL and PubChem and its impact on target prediction. We highlight the number of conflicting bioactivities between human and orthologues is low and annotations are overall compatible. Chemical space analysis shows orthologues are chemically dissimilar to human with high intra-group similarity, suggesting they could effectively extend the chemical space modelled. Based on these observations, we show the benefit of orthologue inclusion in terms of novel target coverage. We also benchmarked predictive models using a time-series split and also using bioactivities from Chemistry Connect and HTS data available at AstraZeneca, showing that orthologue bioactivity inclusion statistically improved performance. [ABSTRACT FROM AUTHOR]

Published
2018
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26. An incremental, exploratory and transformational environment for lazy functional programming.

Author

Runciman, Colin, Toyn, Ian, and Firth, Mike

Abstract

Most programming environments for functional languages offer a single tool used to evaluate programs – either a batch compiler or an interpreter with a read-eval-print loop. This paper presents a programming environment that supports not only evaluation, but also a range of other programming activities including transformation. The environment is designed to encourage working in an incremental and exploratory style, avoiding constraints on the order in which things must be done yet guarenteeing security. What has already been done towards the development of a program automatically persists, as does information about what has yet to be done. For instance, new laws can be introduced as conjectures and used in program transformation, but full details of proof obligations and dependencies are maintained.The paper outlines the functional language supported by the environment, and uses an extended example to illustrate program construction, execution, tracing, modification and transformation. [ABSTRACT FROM PUBLISHER]

Published
1993
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28. Inbox.

Author

Griffiths, Hugo, Holt, Gavin, Garfield, S., Firth, Mike, Wheatley, David, Simm, Ian, and Underwood, Chris

Subjects
FORD Ranger truck, VOLKSWAGEN automobiles, ELECTRIC vehicles
Published
2018

29. COME OUT WRITING.

Author

Firth, Mike, Hannan, Robert, Taha, Mark, and Colella, Angelo C.

Published
2018

30. Goods and Services Tax reaches a difficult age.

Author

Firth, Mike and Wurts, Brian

Subjects
TAXATION, SALES tax, TAXATION of articles of consumption, PRICE inflation, EXCISE tax
Abstract

The article discusses how the Goods and Services Tax (GST) in Canada has performed since it was implemented in 1991 and how the federal government and the provinces might deal with issues to a national sales tax. The GST was introduced to rectify many of the structural economic defects associated with the Federal Manufacturers Sales Tax. Its implementation resulted to a none detectable price inflation and has performed well. The intention of the federal government to reduce its reliance on the GST has raised issues on the national sales tax and allowed provinces to harmonize their sales tax regimes into a single national sales tax.

Published
2006

31. AR in Your Car: How HUDs Are Changing Driving: VIRTUAL DISPLAY TECHNOLOGY PROMISES TO GIVE DRIVERS INSTANT INFORMATION, WHILE IMPROVING DRIVER SAFETY.

Author

FIRTH, MIKE

Subjects
AUTOMOTIVE engineering, HEAD-up displays
Abstract

The article discusses how head-up displays (HUDs) are improving driving experience, how virtual display technology promising to provide drivers with instant information thereby improving driver safety and how advanced driver-assistance systems works with HUD.

Published
2019

32. Pre-clinical pharmacology of AZD3965, a selective inhibitor of MCT1: DLBCL, NHL and Burkitt's lymphoma anti-tumor activity.

Author

Curtis NJ, Mooney L, Hopcroft L, Michopoulos F, Whalley N, Zhong H, Murray C, Logie A, Revill M, Byth KF, Benjamin AD, Firth MA, Green S, Smith PD, and Critchlow SE

Abstract

Tumors frequently display a glycolytic phenotype with increased flux through glycolysis and concomitant synthesis of lactate. To maintain glycolytic flux and prevent intracellular acidification, tumors efflux lactate via lactate transporters (MCT1-4). Inhibitors of lactate transport have the potential to inhibit glycolysis and tumor growth. We developed a small molecule inhibitor of MCT1 (AZD3965) and assessed its activity across a panel of cell lines. We explored its antitumor activity as monotherapy and in combination with doxorubicin or rituximab. AZD3965 is a potent inhibitor of MCT1 with activity against MCT2 but selectivity over MCT3 and MCT4. In vitro , AZD3965 inhibited the growth of a range of cell lines especially haematological cells. Inhibition of MCT1 by AZD3965 inhibited lactate efflux and resulted in accumulation of glycolytic intermediates. In vivo , AZD3965 caused lactate accumulation in the Raji Burkitt's lymphoma model and significant tumor growth inhibition. Moreover, AZD3965 can be combined with doxorubicin or rituximab, components of the R-CHOP standard-of-care in DLBCL and Burkitt's lymphoma. Finally, combining lactate transport inhibition by AZD3965 with GLS1 inhibition in vitro , enhanced cell growth inhibition and cell death compared to monotherapy treatment. The ability to combine AZD3965 with novel, and standard-of-care inhibitors offers novel combination opportunities in haematological cancers., Competing Interests: CONFLICTS OF INTEREST All authors are current or former employees of AstraZeneca.

Published
2017
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33. Understanding Cytotoxicity and Cytostaticity in a High-Throughput Screening Collection.

Author

Mervin LH, Cao Q, Barrett IP, Firth MA, Murray D, McWilliams L, Haddrick M, Wigglesworth M, Engkvist O, and Bender A

Subjects
Cell Line, Humans, Cell Cycle drug effects, Cell Survival drug effects, High-Throughput Screening Assays methods
Abstract

While mechanisms of cytotoxicity and cytostaticity have been studied extensively from the biological side, relatively little is currently understood regarding areas of chemical space leading to cytotoxicity and cytostasis in large compound collections. Predicting and rationalizing potential adverse mechanism-of-actions (MoAs) of small molecules is however crucial for screening library design, given the link of even low level cytotoxicity and adverse events observed in man. In this study, we analyzed results from a cell-based cytotoxicity screening cascade, comprising 296 970 nontoxic, 5784 cytotoxic and cytostatic, and 2327 cytostatic-only compounds evaluated on the THP-1 cell-line. We employed an in silico MoA analysis protocol, utilizing 9.5 million active and 602 million inactive bioactivity points to generate target predictions, annotate predicted targets with pathways, and calculate enrichment metrics to highlight targets and pathways. Predictions identify known mechanisms for the top ranking targets and pathways for both phenotypes after review and indicate that while processes involved in cytotoxicity versus cytostaticity seem to overlap, differences between both phenotypes seem to exist to some extent. Cytotoxic predictions highlight many kinases, including the potentially novel cytotoxicity-related target STK32C, while cytostatic predictions outline targets linked with response to DNA damage, metabolism, and cytoskeletal machinery. Fragment analysis was also employed to generate a library of toxicophores to improve general understanding of the chemical features driving toxicity. We highlight substructures with potential kinase-dependent and kinase-independent mechanisms of toxicity. We also trained a cytotoxic classification model on proprietary and public compound readouts, and prospectively validated these on 988 novel compounds comprising difficult and trivial testing instances, to establish the applicability domain of models. The proprietary model performed with precision and recall scores of 77.9% and 83.8%, respectively. The MoA results and top ranking substructures with accompanying MoA predictions are available as a platform to assess screening collections.

Published
2016
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