[{"oa_version":"Published Version","file_date_updated":"2023-12-06T13:14:15Z","ddc":["570"],"month":"11","day":"30","citation":{"ista":"Hennessey-Wesen M. 2023. Adaptive mutation in E. coli modulated by luxS. Institute of Science and Technology Austria.","ama":"Hennessey-Wesen M. Adaptive mutation in E. coli modulated by luxS. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:14641\">10.15479/at:ista:14641</a>","short":"M. Hennessey-Wesen, Adaptive Mutation in E. Coli Modulated by LuxS, Institute of Science and Technology Austria, 2023.","ieee":"M. Hennessey-Wesen, “Adaptive mutation in E. coli modulated by luxS,” Institute of Science and Technology Austria, 2023.","apa":"Hennessey-Wesen, M. (2023). <i>Adaptive mutation in E. coli modulated by luxS</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:14641\">https://doi.org/10.15479/at:ista:14641</a>","mla":"Hennessey-Wesen, Mike. <i>Adaptive Mutation in E. Coli Modulated by LuxS</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:14641\">10.15479/at:ista:14641</a>.","chicago":"Hennessey-Wesen, Mike. “Adaptive Mutation in E. Coli Modulated by LuxS.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:14641\">https://doi.org/10.15479/at:ista:14641</a>."},"article_processing_charge":"No","has_accepted_license":"1","file":[{"file_id":"14648","date_created":"2023-12-06T13:13:26Z","access_level":"closed","checksum":"4127c285b34f4bf7fb31ef24f9d14c25","content_type":"application/vnd.oasis.opendocument.text","date_updated":"2023-12-06T13:13:26Z","file_name":"mike_thesis_v06-12-2023.odt","file_size":46405919,"relation":"source_file","creator":"mhenness"},{"file_name":"mike_thesis_v06-12-2023.pdf","relation":"main_file","creator":"mhenness","file_size":21282155,"embargo":"2024-11-30","access_level":"closed","content_type":"application/pdf","checksum":"f5203a61eddaf35235bbc51904d73982","date_updated":"2023-12-06T13:14:15Z","embargo_to":"open_access","file_id":"14649","date_created":"2023-12-06T13:14:15Z"}],"degree_awarded":"PhD","doi":"10.15479/at:ista:14641","_id":"14641","author":[{"full_name":"Hennessey-Wesen, Mike","last_name":"Hennessey-Wesen","id":"3F338C72-F248-11E8-B48F-1D18A9856A87","first_name":"Mike"}],"supervisor":[{"orcid":"0000-0003-2057-2754","full_name":"Hof, Björn","last_name":"Hof","id":"3A374330-F248-11E8-B48F-1D18A9856A87","first_name":"Björn"}],"title":"Adaptive mutation in E. coli modulated by luxS","ec_funded":1,"status":"public","publication_status":"published","project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program","call_identifier":"H2020"}],"publication_identifier":{"issn":["2663 - 337X"]},"acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"Bio"},{"_id":"CampIT"}],"date_created":"2023-12-04T13:17:37Z","date_published":"2023-11-30T00:00:00Z","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","department":[{"_id":"GradSch"},{"_id":"BjHo"}],"type":"dissertation","language":[{"iso":"eng"}],"publisher":"Institute of Science and Technology Austria","keyword":["microfluidics","miceobiology","mutations","quorum sensing"],"year":"2023","alternative_title":["ISTA Thesis"],"page":"104","date_updated":"2023-12-07T14:12:25Z"},{"abstract":[{"text":"The process of detecting and evaluating sensory information to guide behaviour is termed perceptual decision-making (PDM), and is critical for the ability of an organism to interact with its external world. Individuals with autism, a neurodevelopmental condition primarily characterised by social and communication difficulties, frequently exhibit altered sensory processing and PDM difficulties are widely reported. Recent technological advancements have pushed forward our understanding of the genetic changes accompanying this condition, however our understanding of how these mutations affect the function of specific neuronal circuits and bring about the corresponding behavioural changes remains limited. Here, we use an innate PDM task, the looming avoidance response (LAR) paradigm, to identify a convergent behavioural abnormality across three molecularly distinct genetic mouse models of autism (Cul3, Setd5 and Ptchd1). Although mutant mice can rapidly detect threatening visual stimuli, their responses are consistently delayed, requiring longer to initiate an appropriate response than their wild-type siblings. Mutant animals show abnormal adaptation in both their stimulus- evoked escape responses and exploratory dynamics following repeated stimulus presentations. Similarly delayed behavioural responses are observed in wild-type animals when faced with more ambiguous threats, suggesting the mutant phenotype could arise from a dysfunction in the flexible control of this PDM process.\r\nOur knowledge of the core neuronal circuitry mediating the LAR facilitated a detailed dissection of the neuronal mechanisms underlying the behavioural impairment. In vivo extracellular recording revealed that visual responses were unaffected within a key brain region for the rapid processing of visual threats, the superior colliculus (SC), indicating that the behavioural delay was unlikely to originate from sensory impairments. Delayed behavioural responses were recapitulated in the Setd5 model following optogenetic stimulation of the excitatory output neurons of the SC, which are known to mediate escape initiation through the activation of cells in the underlying dorsal periaqueductal grey (dPAG). In vitro patch-clamp recordings of dPAG cells uncovered a stark hypoexcitability phenotype in two out of the three genetic models investigated (Setd5 and Ptchd1), that in Setd5, is mediated by the misregulation of voltage-gated potassium channels. Overall, our results show that the ability to use visual information to drive efficient escape responses is impaired in three diverse genetic mouse models of autism and that, in one of the models studied, this behavioural delay likely originates from differences in the intrinsic excitability of a key subcortical node, the dPAG. Furthermore, this work showcases the use of an innate behavioural paradigm to mechanistically dissect PDM processes in autism.","lang":"eng"}],"doi":"10.15479/at:ista:12716","author":[{"id":"3B717F68-F248-11E8-B48F-1D18A9856A87","first_name":"Laura","full_name":"Burnett, Laura","last_name":"Burnett","orcid":"0000-0002-8937-410X"}],"title":"To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism","supervisor":[{"last_name":"Jösch","full_name":"Jösch, Maximilian A","first_name":"Maximilian A","id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3937-1330"}],"_id":"12716","status":"public","publication_status":"published","ec_funded":1,"publication_identifier":{"issn":["2663-337X"]},"project":[{"call_identifier":"H2020","name":"Circuits of Visual Attention","_id":"2634E9D2-B435-11E9-9278-68D0E5697425","grant_number":"756502"}],"oa_version":"Published Version","day":"10","citation":{"chicago":"Burnett, Laura. “To Flee, or Not to Flee? Using Innate Defensive Behaviours to Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in Mouse Models of Autism.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:12716\">https://doi.org/10.15479/at:ista:12716</a>.","mla":"Burnett, Laura. <i>To Flee, or Not to Flee? Using Innate Defensive Behaviours to Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in Mouse Models of Autism</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:12716\">10.15479/at:ista:12716</a>.","ieee":"L. Burnett, “To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism,” Institute of Science and Technology Austria, 2023.","apa":"Burnett, L. (2023). <i>To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12716\">https://doi.org/10.15479/at:ista:12716</a>","ama":"Burnett L. To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:12716\">10.15479/at:ista:12716</a>","ista":"Burnett L. 2023. To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism. Institute of Science and Technology Austria.","short":"L. Burnett, To Flee, or Not to Flee? Using Innate Defensive Behaviours to Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in Mouse Models of Autism, Institute of Science and Technology Austria, 2023."},"file_date_updated":"2023-03-08T15:08:46Z","month":"03","ddc":["599","573"],"has_accepted_license":"1","article_processing_charge":"No","degree_awarded":"PhD","file":[{"date_created":"2023-03-08T15:08:46Z","file_id":"12717","relation":"source_file","file_size":23029260,"creator":"lburnett","file_name":"Burnett_Thesis_2023.docx","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","checksum":"6c6d9cc2c4cdacb74e6b1047a34d7332","access_level":"closed","date_updated":"2023-03-08T15:08:46Z"},{"date_created":"2023-03-08T15:08:46Z","file_id":"12718","file_size":11959869,"creator":"lburnett","relation":"main_file","file_name":"Burnett_Thesis_2023_pdfA.pdf","checksum":"cebc77705288bf4382db9b3541483cd0","content_type":"application/pdf","access_level":"open_access","date_updated":"2023-03-08T15:08:46Z","success":1}],"year":"2023","alternative_title":["ISTA Thesis"],"oa":1,"page":"178","date_updated":"2023-04-05T10:59:04Z","date_published":"2023-03-10T00:00:00Z","acknowledged_ssus":[{"_id":"PreCl"},{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"CampIT"}],"date_created":"2023-03-08T15:19:45Z","department":[{"_id":"GradSch"},{"_id":"MaJö"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","type":"dissertation","language":[{"iso":"eng"}],"publisher":"Institute of Science and Technology Austria"},{"degree_awarded":"PhD","file":[{"date_created":"2021-05-24T11:22:29Z","file_id":"9419","content_type":"application/pdf","checksum":"4f0abe64114cfed264f9d36e8d1197e3","access_level":"open_access","date_updated":"2021-05-24T11:22:29Z","success":1,"creator":"bphuong","file_size":2673905,"relation":"main_file","file_name":"mph-thesis-v519-pdfimages.pdf"},{"date_created":"2021-05-24T11:56:02Z","file_id":"9420","relation":"source_file","creator":"bphuong","file_size":92995100,"file_name":"thesis.zip","checksum":"f5699e876bc770a9b0df8345a77720a2","content_type":"application/zip","access_level":"closed","date_updated":"2021-05-24T11:56:02Z"}],"has_accepted_license":"1","article_processing_charge":"No","day":"30","citation":{"mla":"Phuong, Mary. <i>Underspecification in Deep Learning</i>. Institute of Science and Technology Austria, 2021, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:9418\">10.15479/AT:ISTA:9418</a>.","chicago":"Phuong, Mary. “Underspecification in Deep Learning.” Institute of Science and Technology Austria, 2021. <a href=\"https://doi.org/10.15479/AT:ISTA:9418\">https://doi.org/10.15479/AT:ISTA:9418</a>.","short":"M. Phuong, Underspecification in Deep Learning, Institute of Science and Technology Austria, 2021.","ama":"Phuong M. Underspecification in deep learning. 2021. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:9418\">10.15479/AT:ISTA:9418</a>","ista":"Phuong M. 2021. Underspecification in deep learning. Institute of Science and Technology Austria.","apa":"Phuong, M. (2021). <i>Underspecification in deep learning</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:9418\">https://doi.org/10.15479/AT:ISTA:9418</a>","ieee":"M. Phuong, “Underspecification in deep learning,” Institute of Science and Technology Austria, 2021."},"ddc":["000"],"month":"05","file_date_updated":"2021-05-24T11:56:02Z","oa_version":"Published Version","publication_identifier":{"issn":["2663-337X"]},"status":"public","publication_status":"published","author":[{"id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","first_name":"Phuong","full_name":"Bui Thi Mai, Phuong","last_name":"Bui Thi Mai"}],"title":"Underspecification in deep learning","supervisor":[{"orcid":"0000-0001-8622-7887","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","full_name":"Lampert, Christoph","last_name":"Lampert"}],"_id":"9418","abstract":[{"lang":"eng","text":"Deep learning is best known for its empirical success across a wide range of applications\r\nspanning computer vision, natural language processing and speech. Of equal significance,\r\nthough perhaps less known, are its ramifications for learning theory: deep networks have\r\nbeen observed to perform surprisingly well in the high-capacity regime, aka the overfitting\r\nor underspecified regime. Classically, this regime on the far right of the bias-variance curve\r\nis associated with poor generalisation; however, recent experiments with deep networks\r\nchallenge this view.\r\n\r\nThis thesis is devoted to investigating various aspects of underspecification in deep learning.\r\nFirst, we argue that deep learning models are underspecified on two levels: a) any given\r\ntraining dataset can be fit by many different functions, and b) any given function can be\r\nexpressed by many different parameter configurations. We refer to the second kind of\r\nunderspecification as parameterisation redundancy and we precisely characterise its extent.\r\nSecond, we characterise the implicit criteria (the inductive bias) that guide learning in the\r\nunderspecified regime. Specifically, we consider a nonlinear but tractable classification\r\nsetting, and show that given the choice, neural networks learn classifiers with a large margin.\r\nThird, we consider learning scenarios where the inductive bias is not by itself sufficient to\r\ndeal with underspecification. We then study different ways of ‘tightening the specification’: i)\r\nIn the setting of representation learning with variational autoencoders, we propose a hand-\r\ncrafted regulariser based on mutual information. ii) In the setting of binary classification, we\r\nconsider soft-label (real-valued) supervision. We derive a generalisation bound for linear\r\nnetworks supervised in this way and verify that soft labels facilitate fast learning. Finally, we\r\nexplore an application of soft-label supervision to the training of multi-exit models."}],"doi":"10.15479/AT:ISTA:9418","publisher":"Institute of Science and Technology Austria","type":"dissertation","language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"ChLa"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","date_published":"2021-05-30T00:00:00Z","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"CampIT"},{"_id":"E-Lib"}],"date_created":"2021-05-24T13:06:23Z","date_updated":"2023-09-08T11:11:12Z","related_material":{"record":[{"id":"7435","status":"deleted","relation":"part_of_dissertation"},{"id":"7481","status":"public","relation":"part_of_dissertation"},{"status":"public","relation":"part_of_dissertation","id":"9416"},{"status":"public","relation":"part_of_dissertation","id":"7479"}]},"page":"125","oa":1,"alternative_title":["ISTA Thesis"],"year":"2021"},{"language":[{"iso":"eng"}],"type":"dissertation","publisher":"Institute of Science and Technology Austria","date_published":"2020-06-26T00:00:00Z","acknowledged_ssus":[{"_id":"E-Lib"},{"_id":"CampIT"}],"date_created":"2020-06-26T10:00:36Z","department":[{"_id":"UlWa"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","related_material":{"record":[{"id":"6556","status":"public","relation":"dissertation_contains"},{"id":"7093","relation":"dissertation_contains","status":"public"}]},"page":"xviii+120","date_updated":"2023-09-07T13:18:27Z","alternative_title":["ISTA Thesis"],"year":"2020","oa":1,"has_accepted_license":"1","article_processing_charge":"No","degree_awarded":"PhD","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"file_name":"Kristof_Huszar-Thesis.pdf","relation":"main_file","file_size":2637562,"creator":"khuszar","date_updated":"2020-07-14T12:48:08Z","access_level":"open_access","content_type":"application/pdf","checksum":"bd8be6e4f1addc863dfcc0fad29ee9c3","file_id":"8034","date_created":"2020-06-26T10:03:58Z"},{"file_id":"8035","date_created":"2020-06-26T10:10:06Z","file_name":"Kristof_Huszar-Thesis-source.zip","relation":"source_file","creator":"khuszar","file_size":7163491,"access_level":"closed","checksum":"d5f8456202b32f4a77552ef47a2837d1","content_type":"application/x-zip-compressed","date_updated":"2020-07-14T12:48:08Z"}],"oa_version":"Published Version","day":"26","citation":{"ieee":"K. Huszár, “Combinatorial width parameters for 3-dimensional manifolds,” Institute of Science and Technology Austria, 2020.","apa":"Huszár, K. (2020). <i>Combinatorial width parameters for 3-dimensional manifolds</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8032\">https://doi.org/10.15479/AT:ISTA:8032</a>","ista":"Huszár K. 2020. Combinatorial width parameters for 3-dimensional manifolds. Institute of Science and Technology Austria.","ama":"Huszár K. Combinatorial width parameters for 3-dimensional manifolds. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8032\">10.15479/AT:ISTA:8032</a>","short":"K. Huszár, Combinatorial Width Parameters for 3-Dimensional Manifolds, Institute of Science and Technology Austria, 2020.","mla":"Huszár, Kristóf. <i>Combinatorial Width Parameters for 3-Dimensional Manifolds</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8032\">10.15479/AT:ISTA:8032</a>.","chicago":"Huszár, Kristóf. “Combinatorial Width Parameters for 3-Dimensional Manifolds.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8032\">https://doi.org/10.15479/AT:ISTA:8032</a>."},"file_date_updated":"2020-07-14T12:48:08Z","ddc":["514"],"month":"06","status":"public","publication_status":"published","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-006-0"]},"abstract":[{"lang":"eng","text":"Algorithms in computational 3-manifold topology typically take a triangulation as an input and return topological information about the underlying 3-manifold. However, extracting the desired information from a triangulation (e.g., evaluating an invariant) is often computationally very expensive. In recent years this complexity barrier has been successfully tackled in some cases by importing ideas from the theory of parameterized algorithms into the realm of 3-manifolds. Various computationally hard problems were shown to be efficiently solvable for input triangulations that are sufficiently “tree-like.”\r\nIn this thesis we focus on the key combinatorial parameter in the above context: we consider the treewidth of a compact, orientable 3-manifold, i.e., the smallest treewidth of the dual graph of any triangulation thereof. By building on the work of Scharlemann–Thompson and Scharlemann–Schultens–Saito on generalized Heegaard splittings, and on the work of Jaco–Rubinstein on layered triangulations, we establish quantitative relations between the treewidth and classical topological invariants of a 3-manifold. In particular, among other results, we show that the treewidth of a closed, orientable, irreducible, non-Haken 3-manifold is always within a constant factor of its Heegaard genus."}],"doi":"10.15479/AT:ISTA:8032","author":[{"orcid":"0000-0002-5445-5057","first_name":"Kristóf","id":"33C26278-F248-11E8-B48F-1D18A9856A87","last_name":"Huszár","full_name":"Huszár, Kristóf"}],"supervisor":[{"id":"36690CA2-F248-11E8-B48F-1D18A9856A87","first_name":"Uli","full_name":"Wagner, Uli","last_name":"Wagner","orcid":"0000-0002-1494-0568"},{"first_name":"Jonathan","full_name":"Spreer, Jonathan","last_name":"Spreer"}],"title":"Combinatorial width parameters for 3-dimensional manifolds","_id":"8032"},{"page":"197","related_material":{"record":[{"relation":"part_of_dissertation","status":"public","id":"7936"},{"relation":"part_of_dissertation","status":"public","id":"7937"},{"id":"8193","status":"public","relation":"part_of_dissertation"},{"id":"8092","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","status":"public","id":"911"}]},"date_updated":"2023-10-16T10:04:02Z","year":"2020","alternative_title":["ISTA Thesis"],"oa":1,"language":[{"iso":"eng"}],"type":"dissertation","publisher":"Institute of Science and Technology Austria","date_created":"2020-09-14T13:42:09Z","acknowledged_ssus":[{"_id":"CampIT"},{"_id":"ScienComp"}],"date_published":"2020-09-14T00:00:00Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"ChLa"}],"publication_status":"published","status":"public","acknowledgement":"Last but not least, I would like to acknowledge the support of the IST IT and scientific computing team for helping provide a great work environment.","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-007-7"]},"doi":"10.15479/AT:ISTA:8390","abstract":[{"lang":"eng","text":"Deep neural networks have established a new standard for data-dependent feature extraction pipelines in the Computer Vision literature. Despite their remarkable performance in the standard supervised learning scenario, i.e. when models are trained with labeled data and tested on samples that follow a similar distribution, neural networks have been shown to struggle with more advanced generalization abilities, such as transferring knowledge across visually different domains, or generalizing to new unseen combinations of known concepts. In this thesis we argue that, in contrast to the usual black-box behavior of neural networks, leveraging more structured internal representations is a promising direction\r\nfor tackling such problems. In particular, we focus on two forms of structure. First, we tackle modularity: We show that (i) compositional architectures are a natural tool for modeling reasoning tasks, in that they efficiently capture their combinatorial nature, which is key for generalizing beyond the compositions seen during training. We investigate how to to learn such models, both formally and experimentally, for the task of abstract visual reasoning. Then, we show that (ii) in some settings, modularity allows us to efficiently break down complex tasks into smaller, easier, modules, thereby improving computational efficiency; We study this behavior in the context of generative models for colorization, as well as for small objects detection. Secondly, we investigate the inherently layered structure of representations learned by neural networks, and analyze its role in the context of transfer learning and domain adaptation across visually\r\ndissimilar domains. "}],"_id":"8390","supervisor":[{"orcid":"0000-0001-8622-7887","first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert","full_name":"Lampert, Christoph"}],"title":"Leveraging structure in Computer Vision tasks for flexible Deep Learning models","author":[{"orcid":"0000-0002-8407-0705","first_name":"Amélie","id":"3811D890-F248-11E8-B48F-1D18A9856A87","last_name":"Royer","full_name":"Royer, Amélie"}],"article_processing_charge":"No","has_accepted_license":"1","file":[{"date_created":"2020-09-14T13:39:14Z","file_id":"8391","content_type":"application/pdf","checksum":"c914d2f88846032f3d8507734861b6ee","access_level":"open_access","date_updated":"2020-09-14T13:39:14Z","success":1,"relation":"main_file","creator":"dernst","file_size":30224591,"file_name":"2020_Thesis_Royer.pdf"},{"checksum":"ae98fb35d912cff84a89035ae5794d3c","content_type":"application/x-zip-compressed","access_level":"closed","date_updated":"2020-09-14T13:39:17Z","relation":"main_file","creator":"dernst","file_size":74227627,"file_name":"thesis_sources.zip","date_created":"2020-09-14T13:39:17Z","file_id":"8392"}],"tmp":{"image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)"},"degree_awarded":"PhD","oa_version":"Published Version","license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","ddc":["000"],"file_date_updated":"2020-09-14T13:39:17Z","month":"09","citation":{"chicago":"Royer, Amélie. “Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8390\">https://doi.org/10.15479/AT:ISTA:8390</a>.","mla":"Royer, Amélie. <i>Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8390\">10.15479/AT:ISTA:8390</a>.","apa":"Royer, A. (2020). <i>Leveraging structure in Computer Vision tasks for flexible Deep Learning models</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8390\">https://doi.org/10.15479/AT:ISTA:8390</a>","ieee":"A. Royer, “Leveraging structure in Computer Vision tasks for flexible Deep Learning models,” Institute of Science and Technology Austria, 2020.","short":"A. Royer, Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models, Institute of Science and Technology Austria, 2020.","ista":"Royer A. 2020. Leveraging structure in Computer Vision tasks for flexible Deep Learning models. Institute of Science and Technology Austria.","ama":"Royer A. Leveraging structure in Computer Vision tasks for flexible Deep Learning models. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8390\">10.15479/AT:ISTA:8390</a>"},"day":"14"},{"article_processing_charge":"No","has_accepted_license":"1","file":[{"file_id":"8984","date_created":"2020-12-30T15:34:01Z","date_updated":"2021-12-31T23:30:04Z","access_level":"open_access","checksum":"ec2797ab7a6f253b35df0572b36d1b43","content_type":"application/pdf","embargo":"2021-12-30","file_name":"Thesis_Shamsi_Emtenani_pdfA.pdf","creator":"semtenan","relation":"main_file","file_size":10848175},{"embargo_to":"open_access","file_id":"8985","date_created":"2020-12-30T15:37:36Z","file_name":"Thesis_Shamsi_Emtenani_source file.pdf","file_size":10073648,"creator":"semtenan","relation":"source_file","access_level":"closed","checksum":"cc30e6608a9815414024cf548dff3b3a","content_type":"application/pdf","date_updated":"2021-12-31T23:30:04Z"}],"degree_awarded":"PhD","oa_version":"Published Version","ddc":["570"],"file_date_updated":"2021-12-31T23:30:04Z","month":"12","citation":{"ieee":"S. Emtenani, “Metabolic regulation of Drosophila macrophage tissue invasion,” Institute of Science and Technology Austria, 2020.","apa":"Emtenani, S. (2020). <i>Metabolic regulation of Drosophila macrophage tissue invasion</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8983\">https://doi.org/10.15479/AT:ISTA:8983</a>","ista":"Emtenani S. 2020. Metabolic regulation of Drosophila macrophage tissue invasion. Institute of Science and Technology Austria.","short":"S. Emtenani, Metabolic Regulation of Drosophila Macrophage Tissue Invasion, Institute of Science and Technology Austria, 2020.","ama":"Emtenani S. Metabolic regulation of Drosophila macrophage tissue invasion. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8983\">10.15479/AT:ISTA:8983</a>","chicago":"Emtenani, Shamsi. “Metabolic Regulation of Drosophila Macrophage Tissue Invasion.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8983\">https://doi.org/10.15479/AT:ISTA:8983</a>.","mla":"Emtenani, Shamsi. <i>Metabolic Regulation of Drosophila Macrophage Tissue Invasion</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8983\">10.15479/AT:ISTA:8983</a>."},"day":"30","status":"public","publication_status":"published","acknowledgement":"Also, I would like to express my appreciation and thanks to the Bioimaging facility, LSF, GSO, library, and IT people at IST Austria.","publication_identifier":{"issn":["2663-337X"]},"doi":"10.15479/AT:ISTA:8983","abstract":[{"lang":"eng","text":"Metabolic adaptation is a critical feature of migrating cells. It tunes the metabolic programs of migrating cells to allow them to efficiently exert their crucial roles in development, inflammatory responses and tumor metastasis. Cell migration through physically challenging contexts requires energy. However, how the metabolic reprogramming that underlies in vivo cell invasion is controlled is still unanswered. In my PhD project, I identify a novel conserved metabolic shift in Drosophila melanogaster immune cells that by modulating their bioenergetic potential controls developmentally programmed tissue invasion. We show that this regulation requires a novel conserved nuclear protein, named Atossa. Atossa enhances the transcription of a set of proteins, including an RNA helicase Porthos and two metabolic enzymes, each of which increases the tissue invasion of leading Drosophila macrophages and can rescue the atossa mutant phenotype. Porthos selectively regulates the translational efficiency of a subset of mRNAs containing a 5’-UTR cis-regulatory TOP-like sequence. These 5’TOPL mRNA targets encode mitochondrial-related proteins, including subunits of mitochondrial oxidative phosphorylation (OXPHOS) components III and V and other metabolic-related proteins. Porthos powers up mitochondrial OXPHOS to engender a sufficient ATP supply, which is required for tissue invasion of leading macrophages. Atossa’s two vertebrate orthologs rescue the invasion defect. In my PhD project, I elucidate that Atossa displays a conserved developmental metabolic control to modulate metabolic capacities and the cellular energy state, through altered transcription and translation, to aid the tissue infiltration of leading cells into energy demanding barriers."}],"_id":"8983","supervisor":[{"first_name":"Daria E","id":"3D224B9E-F248-11E8-B48F-1D18A9856A87","last_name":"Siekhaus","full_name":"Siekhaus, Daria E","orcid":"0000-0001-8323-8353"}],"title":"Metabolic regulation of Drosophila macrophage tissue invasion","author":[{"orcid":"0000-0001-6981-6938","first_name":"Shamsi","id":"49D32318-F248-11E8-B48F-1D18A9856A87","last_name":"Emtenani","full_name":"Emtenani, Shamsi"}],"language":[{"iso":"eng"}],"type":"dissertation","publisher":"Institute of Science and Technology Austria","date_created":"2020-12-30T15:41:26Z","acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"E-Lib"},{"_id":"CampIT"}],"date_published":"2020-12-30T00:00:00Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"DaSi"}],"page":"141","related_material":{"record":[{"relation":"part_of_dissertation","status":"public","id":"8557"},{"status":"public","relation":"part_of_dissertation","id":"6187"}]},"date_updated":"2023-09-07T13:24:17Z","alternative_title":["ISTA Thesis"],"year":"2020","oa":1},{"intvolume":"        11","publisher":"Oxford Academic Press","quality_controlled":"1","language":[{"iso":"eng"}],"type":"journal_article","isi":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","department":[{"_id":"BeVi"}],"acknowledged_ssus":[{"_id":"CampIT"}],"scopus_import":"1","date_created":"2019-08-04T21:59:18Z","external_id":{"isi":["000484039500018"],"pmid":["31273378"]},"date_published":"2019-07-01T00:00:00Z","date_updated":"2023-08-29T06:53:58Z","publication":"Genome biology and evolution","article_type":"original","page":"1909-1922","oa":1,"year":"2019","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"content_type":"application/pdf","checksum":"f9e8f6863a406dcc5a36b2be001c138c","access_level":"open_access","date_updated":"2020-07-14T12:47:39Z","relation":"main_file","file_size":580205,"creator":"dernst","file_name":"2019_GenomeBiology_Picard.pdf","date_created":"2019-08-05T07:55:02Z","file_id":"6765"}],"article_processing_charge":"No","volume":11,"has_accepted_license":"1","file_date_updated":"2020-07-14T12:47:39Z","ddc":["570"],"month":"07","pmid":1,"day":"01","citation":{"ista":"Picard MAL, Vicoso B, Roquis D, Bulla I, Augusto RC, Arancibia N, Grunau C, Boissier J, Cosseau C. 2019. Dosage compensation throughout the Schistosoma mansoni lifecycle: Specific chromatin landscape of the Z chromosome. Genome biology and evolution. 11(7), 1909–1922.","ama":"Picard MAL, Vicoso B, Roquis D, et al. Dosage compensation throughout the Schistosoma mansoni lifecycle: Specific chromatin landscape of the Z chromosome. <i>Genome biology and evolution</i>. 2019;11(7):1909-1922. doi:<a href=\"https://doi.org/10.1093/gbe/evz133\">10.1093/gbe/evz133</a>","short":"M.A.L. Picard, B. Vicoso, D. Roquis, I. Bulla, R.C. Augusto, N. Arancibia, C. Grunau, J. Boissier, C. Cosseau, Genome Biology and Evolution 11 (2019) 1909–1922.","ieee":"M. A. L. Picard <i>et al.</i>, “Dosage compensation throughout the Schistosoma mansoni lifecycle: Specific chromatin landscape of the Z chromosome,” <i>Genome biology and evolution</i>, vol. 11, no. 7. Oxford Academic Press, pp. 1909–1922, 2019.","apa":"Picard, M. A. L., Vicoso, B., Roquis, D., Bulla, I., Augusto, R. C., Arancibia, N., … Cosseau, C. (2019). Dosage compensation throughout the Schistosoma mansoni lifecycle: Specific chromatin landscape of the Z chromosome. <i>Genome Biology and Evolution</i>. Oxford Academic Press. <a href=\"https://doi.org/10.1093/gbe/evz133\">https://doi.org/10.1093/gbe/evz133</a>","chicago":"Picard, Marion A L, Beatriz Vicoso, David Roquis, Ingo Bulla, Ronaldo C. Augusto, Nathalie Arancibia, Christoph Grunau, Jérôme Boissier, and Céline Cosseau. “Dosage Compensation throughout the Schistosoma Mansoni Lifecycle: Specific Chromatin Landscape of the Z Chromosome.” <i>Genome Biology and Evolution</i>. Oxford Academic Press, 2019. <a href=\"https://doi.org/10.1093/gbe/evz133\">https://doi.org/10.1093/gbe/evz133</a>.","mla":"Picard, Marion A. L., et al. “Dosage Compensation throughout the Schistosoma Mansoni Lifecycle: Specific Chromatin Landscape of the Z Chromosome.” <i>Genome Biology and Evolution</i>, vol. 11, no. 7, Oxford Academic Press, 2019, pp. 1909–22, doi:<a href=\"https://doi.org/10.1093/gbe/evz133\">10.1093/gbe/evz133</a>."},"oa_version":"Published Version","publication_identifier":{"eissn":["1759-6653"]},"status":"public","publication_status":"published","_id":"6755","author":[{"last_name":"Picard","full_name":"Picard, Marion A L","first_name":"Marion A L","id":"2C921A7A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8101-2518"},{"orcid":"0000-0002-4579-8306","first_name":"Beatriz","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87","last_name":"Vicoso","full_name":"Vicoso, Beatriz"},{"first_name":"David","last_name":"Roquis","full_name":"Roquis, David"},{"last_name":"Bulla","full_name":"Bulla, Ingo","first_name":"Ingo"},{"last_name":"Augusto","full_name":"Augusto, Ronaldo C.","first_name":"Ronaldo C."},{"full_name":"Arancibia, Nathalie","last_name":"Arancibia","first_name":"Nathalie"},{"first_name":"Christoph","full_name":"Grunau, Christoph","last_name":"Grunau"},{"first_name":"Jérôme","last_name":"Boissier","full_name":"Boissier, Jérôme"},{"first_name":"Céline","last_name":"Cosseau","full_name":"Cosseau, Céline"}],"title":"Dosage compensation throughout the Schistosoma mansoni lifecycle: Specific chromatin landscape of the Z chromosome","doi":"10.1093/gbe/evz133","issue":"7","abstract":[{"text":"Differentiated sex chromosomes are accompanied by a difference in gene dose between X/Z-specific and autosomal genes. At the transcriptomic level, these sex-linked genes can lead to expression imbalance, or gene dosage can be compensated by epigenetic mechanisms and results into expression level equalization. Schistosoma mansoni has been previously described as a ZW species (i.e., female heterogamety, in opposition to XY male heterogametic species) with a partial dosage compensation, but underlying mechanisms are still unexplored. Here, we combine transcriptomic (RNA-Seq) and epigenetic data (ChIP-Seq against H3K4me3, H3K27me3,andH4K20me1histonemarks) in free larval cercariae and intravertebrate parasitic stages. For the first time, we describe differences in dosage compensation status in ZW females, depending on the parasitic status: free cercariae display global dosage compensation, whereas intravertebrate stages show a partial dosage compensation. We also highlight regional differences of gene expression along the Z chromosome in cercariae, but not in the intravertebrate stages. Finally, we feature a consistent permissive chromatin landscape of the Z chromosome in both sexes and stages. We argue that dosage compensation in schistosomes is characterized by chromatin remodeling mechanisms in the Z-specific region.","lang":"eng"}]}]