cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17639/nott.6592
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 17610R2

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: 17610R2 (III) Source: NIG Name: grk (1) Full name: gurken Also known as: Annotation symbol: CG17610 FlyBase ID: FBgn0001137 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.6604
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 26998

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: 26998 (III) Source: VDRC Name: hiw (1) Full name: highwire Also known as: Annotation symbol: CG32592 FlyBase ID: FBgn0030600 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.6602
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 13266

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: 13266 (X) Source: VDRC Name: hig (1) Full name: hikaru genki Also known as: CT6282 Annotation symbol: CG2040 FlyBase ID: FBgn0010114 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.6593
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 4331

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: 4331 (III) Source: VDRC Name: grk (2) Full name: gurken Also known as: Annotation symbol: CG17610 FlyBase ID: FBgn0001137 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.6418
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 1819R-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: 1819R-1 (III) Source: NIG Name: CG34120 (2) Full name: Also known as: Annotation symbol: CG34120 FlyBase ID: FBgn0083956 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.6539
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 36233

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: 36233 (III) Source: VDRC Name: Dscam1 (2) Full name: Down syndrome cell adhesion molecule 1 Also known as: Dscam, l(2)43Bc, Dm_2R:13612 , Neu1, Dm_2R:13579 Annotation symbol: CG17800 FlyBase ID: FBgn0033159 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.6536
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 15637R-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: 15637R-2 (III) Source: NIG Name: Dp (2) Full name: DP transcription factor Also known as: dDP, l(2)vr10, DP1 Annotation symbol: CG4654 FlyBase ID: FBgn0011763 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.6535
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 7836

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: 7836 (III) Source: VDRC Name: Dp (1) Full name: DP transcription factor Also known as: dDP, l(2)vr10, DP1 Annotation symbol: CG4654 FlyBase ID: FBgn0011763 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.6622
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 55224

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: 55224 (III) Source: Bloomington Name: Irp-1B (2) Full name: Iron regulatory protein 1B Also known as: IRP, cAcon, IRP-1 Annotation symbol: CG6342 FlyBase ID: FBgn0024957 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.6537
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 4313

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: 4313 (III) Source: VDRC Name: ds Full name: dachsous Also known as: l(2)01855 Annotation symbol: CG17941 FlyBase ID: FBgn0284247 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.6620
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 25813

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: 25813 (III) Source: Bloomington Name: Ir8a Full name: Ionotropic receptor 8a Also known as: Annotation symbol: CG32704 FlyBase ID: FBgn0052704 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.6568
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 1511R-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: 1511R-1 (III) Source: NIG Name: Eph (1) Full name: Eph receptor tyrosine kinase Also known as: dek, lincRNA.923, CT3831, Deph Annotation symbol: CG1511 FlyBase ID: FBgn0025936 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.7324
title: Development of a polymicrobial colony biofilm model
title: Polymicrobial wound model

description: The main aim of this study was to develop and optimise a polymicrobial colony biofilm model to test commercial wound dressings
DOI: 10.17639/nott.7325
title: Pre- and post- listening load pupil baseline and mean diameter of the sample of normal hearing adults

description: The data includes the pre-and post- listening load baseline and mean pupil dilation of the sample of normal hearing adults, per cell (i.e. averaged for each experimental condition)
DOI: 10.17639/nott.7323
title: 2d drawing of 3d shapes by 199 Turkish 12-14 year olds

description: 199 Turkish students participated in regular classroom lessons about 2d drawing of 3d shapes in Geometry classes. Afterwards, they completed worksheets requiring isometric and orthogonal drawings and which corresponded to questions asked on the national exam. Data were coded to explore overall performance and the specific errors that students made in order to understand the extent to which lessons were sucessfull
DOI: 10.17639/nott.7331
title: Knowledge and attitudes about conduct disorder of professionals working with young people
title: Knowledge and attitudes about conduct disorder of professionals working with young people: the influence of occupation and direct and indirect experience

description: The deposited Excel file contains responses from professionals working with young people with conduct disorders.
DOI: 10.17639/nott.7328
title: Data from: On the origins of phenotypic parallelism in benthic and limnetic stickleback

description: Phenotypic and environmental data collected from stickleback and lakes in British Columbia, Canada for the manuscript 'On the origins of phenotypic parallelism in benthic and limnetic stickleback'
DOI: 10.17639/nott.7326
title: Postgraduate Writing Needs and Support

description: Data here is collected from virtual interviews with and survey administered to analyse writing needs among postgraduate students and their evaluation of existing writing support.
DOI: 10.17639/nott.7329
title: Empirical Data on UK Corporate Insolvency Distributions - December 2016 to December 2018

description: This data is being shared here for my PhD viva. It will be referenced to during my defence. I am publishing an empirical article based on this data. It will be published Q1 2024. Please do not make this data set publicly available until you get authorisation from me. Thank you.
description: This is the raw empirical data collected and analysed during my PhD thesis. It is saved here for ease of access and reference. Access to these files may be requested by examiners while they are under embargo. Please contact Mohammed Khan at Mohammed.Khan1@nottingham.ac.uk or Asadkhan9999@gmail.com
DOI: 10.17639/nott.7327
title: Paediatric colon length dataset

description: The deposited Excel file contains the anonymised individual data of the measurements of the length of the colon of 16 children with functional constipation (FC) and 19 healthy children controls, all aged between 7 and 18 years old. The measurements of the length of each colon segment (ascending, transverse, descending, and sigmoid-rectum) were calculated from magnetic resonance images of the colon of the children, using manual segmentation and three-dimensional skeletonization image analysis methods. The file also contains the corresponding anonymised demographic data of the participants.
DOI: 10.17639/nott.7257
title: Raw data for low-dimensional metal-organic magnets as a route towards the S=2 Haldane phase

description: Raw data for publication and analysis scripts (where appropriate); Heat Capacity; Inelastic neutron scattering; Magnetic properties; Powder neutron diffraction; Powder X-ray diffraction; Single-crystal X-ray diffraction; X-ray photoelectron spectroscopy
DOI: 10.17639/nott.7214
title: Researcher attitudes to data sharing 2022
title: Data from "Publishers, Funders and Institutions: Who is supporting UKRI funded researchers to share data?"

description: Researchers in the UK were surveyed to identity attitudes and behaviors around data sharing. Survey was shared through academic libraries and through social media.
DOI: 10.17639/nott.7256
title: A linear, binary classifier to predict bacterial biofilm formation on polyacrylates

description: Research data and Python code to undertake machine learning to predict bacterial attachment to polyacrylates.
DOI: 10.17639/nott.7249
title: Sero-epidemiological associations of human herpesviruses IgG with multiple sclerosis using data generated from Italian and UK patient cohorts and controls

description: Experimental protocol produced before data availability.