DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics

Autor: Owen M. O’Connor, Razan N. Alnahhas, Jean-Baptiste Lugagne, Mary J. Dunlop

Publikováno v: PLoS Computational Biology, Vol 18, Iss 1, p e1009797 (2022)
PLoS Computational Biology

Improvements in microscopy software and hardware have dramatically increased the pace of image acquisition, making analysis a major bottleneck in generating quantitative, single-cell data. Although tools for segmenting and tracking bacteria within ti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb337f97aad161a391120ab420ba6570
https://doaj.org/article/cec53aeb977a44d086aac6257abee85d

Patterning with clocks and genetic cascades: Segmentation and regionalization of vertebrate versus insect body plans

Autor: Ezzat El-Sherif, Olivier Pourquié, Margarete Diaz-Cuadros

Publikováno v: PLoS Genetics, Vol 17, Iss 10, p e1009812 (2021)
PLoS Genetics

Oscillatory and sequential processes have been implicated in the spatial patterning of many embryonic tissues. For example, molecular clocks delimit segmental boundaries in vertebrates and insects and mediate lateral root formation in plants, whereas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3864de5a4ea2b23bf81be7e9aaa8513
https://doaj.org/article/25c6d5c1e8f94c68adc64418e5bb9350

Controversies surrounding segments and parasegments in Onychophora

Autor: Franke, Franziska Anni, Mayer, Georg

Publikováno v: PLoS ONE 9(12): e114383. doi:10.1371/ journal.pone.0114383

Arthropods typically show two types of segmentation: the embryonic parasegments and the adult segments that lie out of register with each other. Such a dual nature of body segmentation has not been described from Onychophora, one of the closest arthr

Externí odkaz: http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-157833
http://www.qucosa.de/fileadmin/data/qucosa/documents/15783/OAP-104-Franke-journal.pone.0114383-2.pdf

Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection

Autor: Fletcher Thompson, Ludvig Ahm Krag, Patrizio Mariani, Maria Sokolova

Publikováno v: PLoS ONE, Vol 16, Iss 6, p e0252824 (2021)
PLoS One
PLoS ONE
Sokolova, M, Thompson, F, Mariani, P & Krag, L A 2021, ' Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection ', PLOS ONE, vol. 16, no. 6, e0252824 . https://doi.org/10.1371/journal.pone.0252824

Underwater video monitoring systems are being widely used in fisheries to investigate fish behavior in relation to fishing gear and fishing gear performance during fishing. Such systems can be useful to evaluate the catch composition as well. In deme

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63f407337819478dcaf8f92f7fdb1c4f
https://doaj.org/article/5ada4e32d6cc41dface0860224d446d0

NuSeT: A deep learning tool for reliably separating and analyzing crowded cells

Autor: Linfeng Yang, Rajarshi P Ghosh, J Matthew Franklin, Simon Chen, Chenyu You, Raja R Narayan, Marc L Melcher, Jan T Liphardt

Publikováno v: PLoS Computational Biology, Vol 16, Iss 9, p e1008193 (2020)
PLoS Computational Biology

Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learni

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a41d9e8731da997ee2998fbab630320f
https://doaj.org/article/b1465e3dfd0347d695e217e01e9ead8e