cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17639/nott.6610
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 7716

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: 7716 (III) Source: VDRC Name: Hsp83 Full name: Heat shock protein 83 Also known as: Hsp90, hsp82, l(3)j5C2, E(sev)3A, E(sina)2 Annotation symbol: CG1242 FlyBase ID: FBgn0001233 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.6561
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 31143

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: 31143 (III) Source: Bloomington Name: Ehbp1 Full name: Eps15 homology domain containing protein-binding protein 1 Also known as: dEHBP1 Annotation symbol: CG15609 FlyBase ID: FBgn0034180 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.6550
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 27646

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: 27646 (III) Source: VDRC Name: E(z) (2) Full name: Enhancer of zeste Also known as: EZ, pco, l(3)1902, Su(z)301, E(z)1 Annotation symbol: CG6502 FlyBase ID: FBgn0000629 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.6594
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 33746

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: 33746 (III) Source: Bloomington Name: grn (1) Full name: grain Also known as: GATAc, gra, dGATAc, Gata-c, l(3)84Fa Annotation symbol: CG9656 FlyBase ID: FBgn0001138 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.6595
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 34578

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: 34578 (III) Source: Bloomington Name: grn (2) Full name: grain Also known as: GATAc, gra, dGATAc, Gata-c, l(3)84Fa Annotation symbol: CG9656 FlyBase ID: FBgn0001138 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.6547
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 40026

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: 40026 (III) Source: VDRC Name: Dsor1 (2) Full name: Downstream of raf1 Also known as: MEK, Dsor, MAPKK, D-mek, DRODSOR1 Annotation symbol: CG15793 FlyBase ID: FBgn0010269 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.6573
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 41960

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: 41960 (III) Source: VDRC Name: Exn (1) Full name: Ephexin Also known as: BcDNA:GH03693 Annotation symbol: CG42665 FlyBase ID: FBgn0261547 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: 10.15468/dl.t8ycqh
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Balaenoptera physalus (Linnaeus, 1758)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007083-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17639/nott.6576
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 33173

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: 33173 (III) Source: VDRC Name: Fbp2 Full name: Fat body protein 2 Also known as: P6 Annotation symbol: CG3763 FlyBase ID: FBgn0000640 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.6421
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 39446

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: 39446 (III) Source: VDRC Name: CG34380 (2) Full name: smoke alarm Also known as: smal Annotation symbol: CG34380 FlyBase ID: FBgn0085409 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.6564
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 15302

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: 15302 (III) Source: VDRC Name: Elongin-C Full name: Elongin C Also known as: EloC Annotation symbol: CG9291 FlyBase ID: FBgn0266711 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.6423
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 40440

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: 40440 (III) Source: VDRC Name: CG34422 (2) Full name: hat-trick Also known as: htk Annotation symbol: CG34422 FlyBase ID: FBgn0085451 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.6396
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 34743

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: 34743 (III) Source: VDRC Name: CG30280 (1) Full name: Also known as: Annotation symbol: CG30280 FlyBase ID: FBgn0050280 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.6358
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 43308

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: 43308 (III) Source: Bloomington Name: CG11836 Full name: Also known as: Annotation symbol: CG11836 FlyBase ID: FBgn0039272 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.6176
title: Improved extraction repeatability and spectral reproducibility for liquid extraction surface analysis–mass spectrometry using superhydrophobic–superhydrophilic patterning
title: LESA-MS data of a standard mixture sampled from glass and Droplet Microarray
title: LESA-MS data of urine samples from a tea intervention study sampled from glass and Droplet Microarray

description: Data related to the paper "Improved Extraction Repeatability and Spectral Reproducibility for Liquid Extraction Surface Analysis–Mass Spectrometry Using Superhydrophobic–Superhydrophilic Patterning" A major problem limiting reproducible use of liquid extraction surface analysis (LESA) array sampling of dried surface-deposited liquid samples is the unwanted spread of extraction solvent beyond the dried sample limits, resulting in unreliable data. Here, we explore the use of the Droplet Microarray (DMA), which consists of an array of superhydrophilic spots bordered by a superhydrophobic material giving the potential to confine both the sample spot and the LESA extraction solvent in a defined area. We investigated the DMA method in comparison with a standard glass substrate using LESA analysis of a mixture of biologically relevant compounds with a wide mass range and different physicochemical properties. The optimized DMA method was subsequently applied to urine samples from a human intervention study. Relative standard deviations for the signal intensities were all reduced at least 3-fold when performing LESA-MS on the DMA surface compared with a standard glass surface. Principal component analysis revealed more tight clusters indicating improved spectral reproducibility for a human urine sample extracted from the DMA compared to glass. Lastly, in urine samples from an intervention study, more significant ions (145) were identified when using LESA-MS spectra of control and test urine extracted from the DMA. We demonstrate that DMA provides a surface-assisted LESA-MS method delivering significant improvement of the surface extraction repeatability leading to the acquisition of more robust and higher quality data. The DMA shows potential to be used for LESA-MS for controlled and reproducible surface extraction and for acquisition of high quality, qualitative data in a high-throughput manner.