cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17639/nott.6927
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 51507

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 51507 (III) Source: Bloomington Name: tld Full name: tolloid Also known as: Annotation symbol: CG6868 FlyBase ID: FBgn0003719 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.6084/m9.figshare.27931488
title: The Use of Generative AI to Advance Cybersecurity Education Taxonomy

description: After searching on Google Scholar, the papers that did not match the criteria and papers with titles irrelevant to the study were discarded, and the remaining papers moved to the next stage. In this stage, the abstracts and conclusions were reviewed to assess each paper’s relevance to the study. Papers that did not align with the research goals were excluded. The remaining papers were then read in full to confirm their final relevancy to the research goals and the topic of this thesis. The selection process was first performed by the master student and then evaluated by the supervisor to ensure reliability of the findings.<br>Using the search string mentioned above on Google Scholar results in a total of 386 search results at the time of conducting the paper selection. After eliminating irrelevant papers, a total of 14 papers were found relevant to the research questions. Although the number of papers may appear limited, the research topic is relatively new, and there is a lack of studies available on this subject. As many as seven papers were published in 2024 and six were published in 2023. This recent surge in publications underscores both the growing academic attention of the use of AI to advance cybersecurity education and the need for further research to deepen understanding in this area. The selected papers and their related data, such as title, author(s), publication source, publisher, publication year, findings, and identified themes were extracted in an Excel file which can be accessed on Figshare public repository.
DOI: 10.17639/nott.6921
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 11701

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 11701 (III) Source: VDRC Name: Tim17a2 Full name: Tim17a2 Also known as: Annotation symbol: CG14666 FlyBase ID: FBgn0037307 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6922
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 9455

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 9455 (III) Source: VDRC Name: Tim17B1 Full name: Tim17b1 Also known as: Annotation symbol: CG1158 FlyBase ID: FBgn0037310 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.7014
title: Difficulties encountered using English as a second language in online interaction

description: This is an Nvivo dataset comprised of four csv data files each containing between 1500 and 2800 short text comments. The comments are derived from questionnaire items asking respondents what they found difficult about using English online.
DOI: 10.17639/nott.6966
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 4380R-3

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 4380R-3 (III) Source: NIG Name: usp (1) Full name: ultraspiracle Also known as: DmUSP, CF1, dUSP, EG:22E5 .1, NR2B4 Annotation symbol: CG4380 FlyBase ID: FBgn0003964 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6965
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 5993R-2

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 5993R-2 (III) Source: NIG Name: upd-IR3282 (os) Full name: unpaired 1 Also known as: upd1, upd, os, sisC, sis-c, sy Annotation symbol: CG5993 FlyBase ID: FBgn0004956 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6941
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 18214R1

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 18214R1 (III) Source: NIG Name: trio (1) Full name: trio Also known as: DTrio, l(3)S095914, l(3)S036810, M89 Annotation symbol: CG18214 FlyBase ID: FBgn0024277 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6942
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 40137

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 40137 (III) Source: VDRC Name: trio (2) Full name: Sex combs extra Also known as: DTrio, l(3)S095914, l(3)S036810, M89 Annotation symbol: CG18214 FlyBase ID: FBgn0024277 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6936
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 49383

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 49383 (III) Source: VDRC Name: Trax Full name: Translin associated factor X Also known as: Annotation symbol: CG5063 FlyBase ID: FBgn0038327 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6972
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 50727

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 50727 (III) Source: Bloomington Name: Vhl Full name: von Hippel-Lindau Also known as: dVHL, d-VHL Annotation symbol: CG13221 FlyBase ID: FBgn0041174 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.331
title: An on-surface reaction confined within a porous molecular template

description: On-surface reactions based on metal-catalysed Ullmann coupling have been successfully employed to synthesise a wide variety of covalently coupled structures. Substrate chemistry and topology are both known to effect the progression of an on-surface reaction; offering routes to control efficiency and selectivity. Here, we detail ultra-high vacuum scanning probe microscopy experiments showing that templating a catalytically active surface, via a supramolecular template, influences the reaction pathway of an on-surface Ullmann-type coupling reaction by inhibiting one potential intermediate structure and stabilising another.
DOI: 10.17639/nott.51
title: Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks

description: This deposit contains the raw ToF-SIMS data of freeze-dried cells used in Van Nuffel, Sebastiaan, et al. "Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks." Analyst 141.1 (2016): 90-95.
DOI: 10.17639/nott.372
title: Raw data for new compounds described in the paper: "Synthesis of multisubstituted pyrroles by nickel-catalyzed arylative cyclizations of N-tosyl alkynamides"

description: Raw data for new compounds described in the paper: "Synthesis of multisubstituted pyrroles by nickel-catalyzed arylative cyclizations of N-tosyl alkynamides".
DOI: 10.17639/nott.374
title: NMR data for new compounds described in the paper: "Nickel-catalyzed, ligand-free, diastereoselective synthesis of 3-methyleneindan-1-ols"

description: Raw NMR data for new compounds described in the paper: "Nickel-catalyzed, ligand-free, diastereoselective synthesis of 3-methyleneindan-1-ols".
DOI: 10.17639/nott.70
title: Muzicodes (Musical Code Recognition System) user workshops, 2016, public dataset

description: Data from a series of development workshops using the muzicodes musical code recognition system, held with musicians with varying levels of experience and background. Includes participant information, summary information of the codes/experiences developed and fragment of transcript.
DOI: 10.17639/nott.66
title: Making silicone rubber highly resistant to bacterial attachment using thiol-ene grafting

description: RAW data required by EPSRC relating to the paper described in the title. Contains data regarding: XPS, ToF-SIMS, FT-IR, Confocal Microscopy Quantification and Polymer Characterisation
DOI: 10.17639/nott.61
title: Conversational agent use in a café

description: Anonymised transcripts of conversational agent use in a café that were used for the following publication: Martin Porcheron, Joel E. Fischer, and Sarah Sharples. 2017. “Do Animals Have Accents?”: Talking with Agents in Multi-party Conversation. In Proceedings of the 20th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’17). ACM, New York, NY, USA. https://doi.org/10.1145/2998181.2998298
DOI: 10.17639/nott.6254
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 2902

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 2902 (III) Source: VDRC Name: Akt1 (1) Full name: Akt1 Also known as: Akt, dAkt, PKB, Dakt1, dPKB Annotation symbol: CG4006 FlyBase ID: FBgn0010379 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6681
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 1771R-1

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 1771R-1 (III) Source: NIG Name: mew (aPS1) Integrin Full name: multiple edematous wings Also known as: mew, αPS1, αPS1, PS1, PS1α, α1Int Annotation symbol: CG1771 FlyBase ID: FBgn0004456 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)