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1.
Wellcome Open Res ; 8: 389, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38434743

RESUMO

We present a genome assembly from an individual female Sympetrum striolatum (the Common Darter; Arthropoda; Insecta; Odonata; Libellulidae). The genome sequence is 1349.6 megabases in span. Most of the assembly is scaffolded into 12 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled and is 16.16 kilobases in length.

2.
Wellcome Open Res ; 8: 320, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38764968

RESUMO

We present a genome assembly from an individual male Platycnemis pennipes (the White-legged damselfly; Arthropoda; Insecta; Odonata; Platycnemididae). The genome sequence is 1793.3 megabases in span. Most of the assembly is scaffolded into 13 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled and is 15.42 kilobases in length.

3.
Biodivers Data J ; 7: e32342, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30863197

RESUMO

The Natural History Museum, London (NHM) has embarked on an ambitious programme to digitise its collections. One aim of the programme has been to improve the workflows and infrastructure needed to support high-throughput digitisation and create comprehensive digital inventories of large scientific collections. This paper presents the workflow developed to digitise the entire Phthiraptera (parasitic lice) microscope slide collection (70,663 slides). Here we describe a novel process of semi-automated mass digitisation using both temporary and permanent barcode labels applied before and during slide imaging. By using a series of barcodes encoding information associated with each slide (i.e. unique identifier, location in the collection and taxonomic name), we can run a series of automated processes, including file renaming, image processing and bulk import into the NHM's collection management system. We provide data on the comparative efficiency of these processes, illustrating how simple activities, like automated file renaming, reduces image post-processing time, minimises human error and can be applied across multiple collection types.

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