21 results on '"Kastelic, Damjana"'
Search Results
2. Optimised ‘on demand’ protein arraying from DNA by cell free expression with the ‘DNA to Protein Array’ (DAPA) technology
- Author
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Schmidt, Ronny, Cook, Elizabeth A., Kastelic, Damjana, Taussig, Michael J., and Stoevesandt, Oda
- Published
- 2013
- Full Text
- View/download PDF
3. The Global Sequence Signature algorithm unveils a structural network surrounding heavy chain CDR3 loop in Camelidae variable domains
- Author
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Kastelic, Damjana, Soler, Nicolas, Komel, Radovan, and Pompon, Denis
- Published
- 2013
- Full Text
- View/download PDF
4. Cell free expression put on the spot: advances in repeatable protein arraying from DNA (DAPA)
- Author
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Stoevesandt, Oda, Vetter, Maike, Kastelic, Damjana, Palmer, Elizabeth A., He, Mingyue, and Taussig, Michael J.
- Published
- 2011
- Full Text
- View/download PDF
5. A single-step procedure of recombinant library construction for the selection of efficiently produced llama VH binders directed against cancer markers
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Kastelic, Damjana, Frković-Grazio, Snježana, Baty, Daniel, Truan, Gilles, Komel, Radovan, and Pompon, Denis
- Published
- 2009
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6. Methods for analyzing and quantifying protein–protein interaction
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Syafrizayanti, Betzen, Christian, Hoheisel, Jörg D, and Kastelic, Damjana
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- 2014
- Full Text
- View/download PDF
7. Ribosome Display and Screening for Protein Therapeutics
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Kastelic, Damjana, primary and He, Mingyue, additional
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- 2012
- Full Text
- View/download PDF
8. Eukaryotic Ribosome Display with In Situ DNA Recovery
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He, Mingyue, primary, Edwards, Bryan M., additional, Kastelic, Damjana, additional, and Taussig, Michael J., additional
- Published
- 2011
- Full Text
- View/download PDF
9. Initiatives to Build a Whole-Cell Modeling Community: 2019 Update
- Author
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Karr, Jonathan R, Lluch-Senar, Maria, Kastelic, Damjana, Serrano, Luis, and Sauro, Herbert M
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computational biology ,summer school ,dynamical modeling ,4. Education ,cell biology ,systems biology ,bioinformatics ,whole-cell modeling ,3. Good health - Abstract
Whole-cell (WC) models that predict phenotype from genotype have the potential to transform biology, bioengineering, and medicine. Achieving WC models will likely require collaboration among modelers, experimentalists, mathematicians, computer scientists, and engineers. In 2012, we and others began to build a WC community by organizing a central website, a primer, schools, hackathons, and challenges. This year, we have continued to build a WC community by developing a new website, expanding the primer, organizing a third school, and launching an online seminar. Here, we summarize these initiatives, their impact to date, and our plans to continue to build a WC community.
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- 2019
- Full Text
- View/download PDF
10. A Case Report: Building communities with training and resources for Open Science trainers
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Brinken, Helene, primary, Kuchma, Iryna, additional, Kalaitzi, Vasso, additional, Davidson, Joy, additional, Pontika, Nancy, additional, Cancellieri, Matteo, additional, Correia, Antónia, additional, Carvalho, José, additional, Melero, Remedios, additional, Kastelic, Damjana, additional, Borba, Filomena, additional, Lenaki, Katerina, additional, Toelch, Ulf, additional, Zourou, Katerina, additional, Knoth, Petr, additional, Schmidt, Birgit, additional, and Rodrigues, Eloy, additional
- Published
- 2019
- Full Text
- View/download PDF
11. The 2017 Whole-Cell Modeling Summer School
- Author
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Karr, Jonathan R, Lluch-Senar, Maria, Serrano, Luis, and Kastelic, Damjana
- Subjects
computational biology ,dynamical modeling ,4. Education ,cell biology ,systems biology ,3. Good health - Abstract
Whole-cell models that predict phenotype from genotype are needed to advance biology, bioengineering, and medicine. Achieving whole-cell models will require extensive collaboration among modelers, experimentalists, mathematicians, computer scientists, and software engineers. In September2017, we organized the second Whole-Cell Modeling Summer School to continue to build a whole-cell community by training new researchers. The school created new whole-cell training materials;trained 18 students, postdoctoral scholars, and faculty; and generated ideas about how to better teach whole-cell modeling. To build a whole-cell modeling community, we plan to continue to organize schools, continue to improve these schools based on the lessons that we learned this year, andinitiate an annual workshop and/or online seminar series to facilitate sustained discussion aboutwhole-cell modeling.
- Published
- 2017
- Full Text
- View/download PDF
12. Exploiting sequence and stability information for directing nanobody stability engineering
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European Commission, Kunz, Patrick, Flock, Tilman, Soler, Nicolas, Zaiss, Moritz, Vincke, Cécile, Sterckx, Yann, Kastelic, Damjana, Muyldermans, Serge, Hoheisel, Jörg D., European Commission, Kunz, Patrick, Flock, Tilman, Soler, Nicolas, Zaiss, Moritz, Vincke, Cécile, Sterckx, Yann, Kastelic, Damjana, Muyldermans, Serge, and Hoheisel, Jörg D.
- Abstract
[Background] Variable domains of camelid heavy-chain antibodies, commonly named nanobodies, have highbiotechnological potential. In view of their broad range of applications in research, diagnostics and therapy,engineering their stability is of particular interest. One important aspect is the improvement of thermostability,because it can have immediate effects on conformational stability, protease resistance and aggregation pro-pensity of the protein, [Methods] We analyzed the sequences and thermostabilities of 78 purified nanobody binders. From this data,potentially stabilizing amino acid variations were identified and studied experimentally.Results:Some mutations improved the stability of nanobodies by up to 6.1 °C, with an average of 2.3 °C acrosseight modified nanobodies. The stabilizing mechanism involves an improvement of both conformational stabilityand aggregation behavior, explaining the variable degree of stabilization in individual molecules. In some in-stances, variations predicted to be stabilizing actually led to thermal destabilization of the proteins. The reasonsfor this contradiction between prediction and experiment were investigated., [Conclusions] The results reveal a mutational strategy to improve the biophysical behavior of nanobody bindersand indicate a species-specificity of nanobody architecture, [General significance] This study illustrates the potential and limitations of engineering nanobody thermostabilityby merging sequence information with stability data, an aspect that is becoming increasingly important with therecent development of high-throughput biophysical methods
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- 2017
13. Možnosti razmnoževanja sobne kale (Zantedeschia aetiopica Spreng.)
- Author
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Kastelic, Damjana and Osterc, Gregor
- Subjects
kala ,udc:635.914:631.533(043.2) ,rez korenik ,sobne rastline ,setev ,čas skladiščenja ,sobna kala ,Zantedeschia aetiopica Spreng ,okrasne rastline ,razmnoževanje - Published
- 2014
14. Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays
- Author
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Sill, Martin, primary, Schröder, Christoph, additional, Shen, Ying, additional, Marzoq, Aseel, additional, Komel, Radovan, additional, Hoheisel, Jörg, additional, Nienhüser, Henrik, additional, Schmidt, Thomas, additional, and Kastelic, Damjana, additional
- Published
- 2016
- Full Text
- View/download PDF
15. Eukaryotic Ribosome Display with In Situ DNA Recovery.
- Author
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He, Mingyue, Edwards, Bryan M., Kastelic, Damjana, and Taussig, Michael J.
- Published
- 2012
- Full Text
- View/download PDF
16. Initiatives to Build a Whole-Cell Modeling Community: 2019 Update
- Author
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Karr, Jonathan R, Lluch-Senar, Maria, Kastelic, Damjana, Serrano, Luis, and Sauro, Herbert M
- Subjects
computational biology ,summer school ,dynamical modeling ,cell biology ,systems biology ,bioinformatics ,whole-cell modeling ,3. Good health - Abstract
Whole-cell (WC) models that predict phenotype from genotype have the potential to transform biology, bioengineering, and medicine. Achieving WC models will likely require collaboration among modelers, experimentalists, mathematicians, computer scientists, and engineers. In 2012, we and others began to build a WC community by organizing a central website, a primer, schools, hackathons, and challenges. This year, we have continued to build a WC community by developing a new website, expanding the primer, organizing a third school, and launching an online seminar. Here, we summarize these initiatives, their impact to date, and our plans to continue to build a WC community., These efforts were supported by National Science Foundation awards 1548123 and 1649014 to JRK, National Institutes of Health award R35 GM119771 to JRK, and National Institutes of Health award P41 EB023912 to Herbert Sauro. The 2019 school was also supported by an EMBO Practical Course award to JRK, MLS, and DK., {"references":["Tomita, M. Whole-cell simulation: a grand challenge of the 21st century. Trends Biotechnol 19, 205–210 (2001).","Karr, J. R., Takahashi, K. & Funahashi, A. The principles of whole-cell modeling. Curr Opin Microbiol 27, 18–24 (2015).","Carrera, J. & Covert, M. W. Why build whole-cell models? Trends Cell Biol 25, 719–722 (2015).","Karr, J. R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150, 389–401 (2012).","Macklin, D. N., Ruggero, N. A. & Covert, M. W. The future of whole-cell modeling. Curr Opin Biotechnol 28, 111–115 (2014).","Goldberg, A. P. et al. Emerging whole-cell modeling principles and methods. Curr Opin Biotechnol 51, 97–102 (2018).","Szigeti, B. et al. A blueprint for human whole-cell modeling. Curr Opin Syst Biol 7, 8–15 (2018).","Karr, J. R. & Pochiraju, S. Whole-cell modeling https://www.wholecell.org (2019).","Karr, J. R. et al. Summary of the DREAM8 parameter estimation challenge: toward parameter identification for whole-cell models. PLoS Comput Biol 11, e1004096 (2015).","Hucka, M. et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531 (2003).","Waltemath, D. et al. Toward community standards and software for whole-cell modeling. IEEE Trans Biomed Eng 63, 2007–2014 (2016).","Karr, J. R., Lluch-Senar, M, Serrano, L & Carrera, J. The 2016 Whole-Cell Modeling Summer School https://doi.org/10.5281/zenodo.1004027 (2016).","Karr, J. R., Lluch-Senar, M, Serrano, L & Carrera, J. The 2017 Whole-Cell Modeling Summer School https://doi.org/10.5281/zenodo.1004135 (2017).","Karr, J. R. & Goldberg, A. P. An introduction to whole-cell modeling https://intro-to- wc-modeling.readthedocs.io (2017).","Karr, J. R., Lluch-Senar, M, Kastelic, D & Serrano, L. 2019 EMBO whole-cell modeling sum- mer school http://meetings.embo.org/event/19-whole-cell-modelling (2019).","Roth, Y. D., Porubsky, V., Sauro, H. M. & Karr, J. R. Online whole-Cell modeling seminar https://reproduciblebiomodels.org/seminar (2019).","Medley, J. K., Goldberg, A. P. & Karr, J. R. Guidelines for reproducibly building and simu- lating systems biology models. IEEE Trans Biomed Eng 63, 2015–2020 (2016).","Watanabe, L., König, M. & Myers, C. Dynamic flux balance analysis models in SBML. BioRXiv, 245076 (2018).","Burke, P. E., de Campos, C. B. & Quiles, M. G. Whole-cell representation and analysis of My- coplasma genitalium organism using complex networks. ComplexNet. doi: 10.13140/2.1.3736.6084.","Rees, J. et al. Designing minimal genomes using whole-cell models. bioRxiv, 344564 (2019)."]}
17. The 2017 Whole-Cell Modeling Summer School
- Author
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Karr, Jonathan R, Lluch-Senar, Maria, Serrano, Luis, and Kastelic, Damjana
- Subjects
computational biology ,dynamical modeling ,4. Education ,cell biology ,systems biology ,3. Good health - Abstract
Whole-cell models that predict phenotype from genotype are needed to advance biology, bioengineering, and medicine. Achieving whole-cell models will require extensive collaboration among modelers, experimentalists, mathematicians, computer scientists, and software engineers. In September 2017, we organized the second Whole-Cell Modeling Summer School to continue to build a whole-cell community by training new researchers. The school created new whole-cell training materials; trained 18 students, postdoctoral scholars, and faculty; and generated ideas about how to better teach whole-cell modeling. To build a whole-cell modeling community, we plan to continue to organize schools, continue to improve these schools based on the lessons that we learned this year, and initiate an annual workshop and/or online seminar series to facilitate sustained discussion about whole-cell modeling., The school was partly supported by ERASynBio award to JRK, LS, and MLS; Horizon 2020 award 634942 to LS; and National Science Foundation award 1649014 to JRK., {"references":["Tomita, M. Whole-cell simulation: a grand challenge of the 21st century. Trends Biotechnol 19, 205–210 (2001).","Karr, J. R., Takahashi, K. & Funahashi, A. The principles of whole-cell modeling. Curr Opin Microbiol 27, 18–24 (2015).","Carrera, J. & Covert, M. W. Why build whole-cell models? Trends Cell Biol 25, 719–722 (2015).","Karr, J. R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150, 389–401 (2012).","Macklin, D. N., Ruggero, N. A. & Covert, M. W. The future of whole-cell modeling. Curr Opin Biotechnol 28, 111–115 (2014).","Goldberg, A. P. et al. Emerging whole-cell modeling principles and methods. Curr Opin Biotechnol (In submission).","Szigeti, B et al. A blueprint for human whole-cell modeling. Curr Opin Syst Biol (In submis- sion).","Karr, J. R., Lluch-Senar, M, Serrano, L & Carrera, J. The 2016 Whole-Cell Modeling Summer School http://www.karrlab.org/static/doc/papers/Karr2016.pdf (2016).","Waltemath, D. et al. Toward community standards and software for whole-cell modeling. IEEE Trans Biomed Eng 63, 2007–2014 (2016).","Karr, J. R., Lluch-Senar, M, Serrano, L & Kastelic, D. 2017 Whole-Cell Modeling Summer School http://www.wholecell.org/school-2017 (2017).","Karr, J. R. & Goldberg, A. P. An introduction to whole-cell modeling http://intro-to-wc- modeling.readthedocs.io (2017).","European Molecular Biology Organization. Practical course funding http://www.embo.org/ funding-awards/courses-workshops/practical-courses (2017)."]}
18. A Case Report: Building communities with training and resources for Open Science trainers
- Author
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Brinken, Helene, Kuchma, Iryna, Kalaitzi, Vaso, Davidson, Joy, Pontika, Nancy, Cancellieri, Matteo, Correia, Antonia, Carvalho, Jose, Melero, Reme, Kastelic, Damjana, Borba, Filomena, Lenaki, Katerina, Toelch, Ulf, Zourou, Katerina, Knoth, Petr, Schmidt, Birgit, Rodrigues, Eloy, Brinken, Helene, Kuchma, Iryna, Kalaitzi, Vaso, Davidson, Joy, Pontika, Nancy, Cancellieri, Matteo, Correia, Antonia, Carvalho, Jose, Melero, Reme, Kastelic, Damjana, Borba, Filomena, Lenaki, Katerina, Toelch, Ulf, Zourou, Katerina, Knoth, Petr, Schmidt, Birgit, and Rodrigues, Eloy
- Abstract
To foster responsible research and innovation, research communities, institutions, and funders are shifting their practices and requirements towards Open Science. Open Science skills are becoming increasingly essential for researchers. Indeed general awareness of Open Science has grown among EU researchers, but the practical adoption can be further improved. Recognizing a gap between the needed and the provided training offer, the FOSTER project offers practical guidance and training to help researchers learn how to open up their research within a particular domain or research environment. Aiming for a sustainable approach, FOSTER focused on strengthening the Open Science training capacity by establishing and supporting a community of trainers. The creation of an Open Science training handbook was a first step towards bringing together trainers to share their experiences and to create an open and living knowledge resource. A subsequent series of train-the-trainer bootcamps helped trainers to find inspiration, improve their skills and to intensify exchange within a peer group. Four trainers, who attended one of the bootcamps, contributed a case study on their experiences and how they rolled out Open Science training within their own institutions. On its platform the project provides a range of online courses and resources to learn about key Open Science topics. FOSTER awards users gamification badges when completing courses in order to provide incentives and rewards, and to spur them on to even greater achievements in learning. The paper at hand describes FOSTER Plus’ training strategies, shares the lessons learnt and provides guidance on how to reuse the project’s materials and training approaches.
19. A Case Report: Building communities with training and resources for Open Science trainers
- Author
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Brinken, Helene, Kuchma, Iryna, Kalaitzi, Vaso, Davidson, Joy, Pontika, Nancy, Cancellieri, Matteo, Correia, Antonia, Carvalho, Jose, Melero, Reme, Kastelic, Damjana, Borba, Filomena, Lenaki, Katerina, Toelch, Ulf, Zourou, Katerina, Knoth, Petr, Schmidt, Birgit, Rodrigues, Eloy, Brinken, Helene, Kuchma, Iryna, Kalaitzi, Vaso, Davidson, Joy, Pontika, Nancy, Cancellieri, Matteo, Correia, Antonia, Carvalho, Jose, Melero, Reme, Kastelic, Damjana, Borba, Filomena, Lenaki, Katerina, Toelch, Ulf, Zourou, Katerina, Knoth, Petr, Schmidt, Birgit, and Rodrigues, Eloy
- Abstract
To foster responsible research and innovation, research communities, institutions, and funders are shifting their practices and requirements towards Open Science. Open Science skills are becoming increasingly essential for researchers. Indeed general awareness of Open Science has grown among EU researchers, but the practical adoption can be further improved. Recognizing a gap between the needed and the provided training offer, the FOSTER project offers practical guidance and training to help researchers learn how to open up their research within a particular domain or research environment. Aiming for a sustainable approach, FOSTER focused on strengthening the Open Science training capacity by establishing and supporting a community of trainers. The creation of an Open Science training handbook was a first step towards bringing together trainers to share their experiences and to create an open and living knowledge resource. A subsequent series of train-the-trainer bootcamps helped trainers to find inspiration, improve their skills and to intensify exchange within a peer group. Four trainers, who attended one of the bootcamps, contributed a case study on their experiences and how they rolled out Open Science training within their own institutions. On its platform the project provides a range of online courses and resources to learn about key Open Science topics. FOSTER awards users gamification badges when completing courses in order to provide incentives and rewards, and to spur them on to even greater achievements in learning. The paper at hand describes FOSTER Plus’ training strategies, shares the lessons learnt and provides guidance on how to reuse the project’s materials and training approaches.
20. Ribosome display and screening for protein therapeutics.
- Author
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Kastelic D and He M
- Subjects
- Animals, Cell-Free System, DNA, Complementary isolation & purification, Escherichia coli, Gene Library, Macromolecular Substances chemistry, Macromolecular Substances isolation & purification, Polymerase Chain Reaction, Rabbits, Reticulocytes, Single-Chain Antibodies genetics, Proteins chemistry, Proteins genetics, RNA, Messenger chemistry, RNA, Messenger genetics, RNA, Messenger isolation & purification, Ribosomes chemistry, Ribosomes genetics, Single-Chain Antibodies isolation & purification
- Abstract
Ribosome display is a cell-free display technology which enables in vitro selection of antibodies from large recombinant DNA libraries. It also allows continuous introduction of mutations into the selected DNA pool by PCR-based mutagenesis in each cycle, enabling selection of antibody variants with improved affinity, specificity, and stability, thus providing a powerful "protein evolution" tool for optimizing antibody therapeutics. Ribosome display selects required molecules by linking individual proteins (phenotype) with their corresponding mRNAs (genotype) through the formation of stable Protein-Ribosome-mRNA (PRM) complexes. By affinity interaction with an immobilized ligand, the captured PRM complexes are recovered as cDNA using RT-PCR from the ribosome-attached mRNA. The DNA is then subjected to subsequent ribosome display cycles for further enrichment of rare species or cloning, expression, and sequencing to identify wanted candidates. Both prokaryotic and eukaryotic cell-free systems have been developed for ribosome display of different proteins. In this chapter, we describe ribosome display of antibodies using the eukaryotic rabbit reticulocyte system with an in situ single-primer DNA recovery method. A high-throughput Escherichia coli expression format is also described for screening of individual antibody binders from the ribosome-selected population.
- Published
- 2012
- Full Text
- View/download PDF
21. Eukaryotic ribosome display with in situ DNA recovery.
- Author
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He M, Edwards BM, Kastelic D, and Taussig MJ
- Subjects
- Animals, DNA genetics, Directed Molecular Evolution, Polymerase Chain Reaction, RNA, Messenger genetics, Rabbits, DNA isolation & purification, Eukaryotic Cells metabolism, Ribosomes genetics, Ribosomes metabolism
- Abstract
Ribosome display is a cell-free display technology for in vitro selection and optimisation of proteins from large diversified libraries. It operates through the formation of stable protein-ribosome-mRNA (PRM) complexes and selection of ligand-binding proteins, followed by DNA recovery from the selected genetic information. Both prokaryotic and eukaryotic ribosome display systems have been developed. In this chapter, we describe the eukaryotic rabbit reticulocyte method in which a distinct in situ single-primer RT-PCR procedure is used to recover DNA from the selected PRM complexes without the need for prior disruption of the ribosome.
- Published
- 2012
- Full Text
- View/download PDF
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