Virtual tissue microstructure reconstruction across species using generative deep learning Article Swipe
Nicolás Bettancourt
,
Cristian Pérez-Gallardo
,
Valeria Candia
,
Pamela Guevara
,
Yannis Kalaidzidis
,
Marino Zerial
,
Fabián Segovia‐Miranda
,
Hernán Morales‐Navarrete
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0306073
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0306073
Analyzing tissue microstructure is essential for understanding complex biological systems in different species. Tissue functions largely depend on their intrinsic tissue architecture. Therefore, studying the three-dimensional (3D) microstructure of tissues, such as the liver, is particularly fascinating due to its conserved essential roles in metabolic processes and detoxification. Here, we present TiMiGNet, a novel deep learning approach for virtual 3D tissue microstructure reconstruction using Generative Adversarial Networks and fluorescence microscopy. TiMiGNet overcomes challenges such as poor antibody penetration and time-intensive procedures by generating accurate, high-resolution predictions of tissue components across large volumes without the need of paired images as input. We applied TiMiGNet to analyze tissue microstructure in mouse and human liver tissue. TiMiGNet shows high performance in predicting structures like bile canaliculi, sinusoids, and Kupffer cell shapes from actin meshwork images. Remarkably, using TiMiGNet we were able to computationally reconstruct tissue structures that cannot be directly imaged due experimental limitations in deep dense tissues, a significant advancement in deep tissue imaging. Our open-source virtual prediction tool facilitates accessible and efficient multi-species tissue microstructure analysis, accommodating researchers with varying expertise levels. Overall, our method represents a powerful approach for studying tissue microstructure, with far-reaching applications in diverse biological contexts and species.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0306073
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printable
- OA Status
- gold
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400579955
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4400579955Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1371/journal.pone.0306073Digital Object Identifier
- Title
-
Virtual tissue microstructure reconstruction across species using generative deep learningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-07-12Full publication date if available
- Authors
-
Nicolás Bettancourt, Cristian Pérez-Gallardo, Valeria Candia, Pamela Guevara, Yannis Kalaidzidis, Marino Zerial, Fabián Segovia‐Miranda, Hernán Morales‐NavarreteList of authors in order
- Landing page
-
https://doi.org/10.1371/journal.pone.0306073Publisher landing page
- PDF URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printableDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printableDirect OA link when available
- Concepts
-
Computer science, Microstructure, Deep learning, Liver tissue, Artificial intelligence, Biology, Biological system, Computational biology, Materials science, Endocrinology, MetallurgyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
40Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4400579955 |
|---|---|
| doi | https://doi.org/10.1371/journal.pone.0306073 |
| ids.doi | https://doi.org/10.1371/journal.pone.0306073 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/38995963 |
| ids.openalex | https://openalex.org/W4400579955 |
| fwci | 0.0 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000077321 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Deep Learning |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D006801 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Humans |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D000818 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Animals |
| mesh[3].qualifier_ui | |
| mesh[3].descriptor_ui | D051379 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | |
| mesh[3].descriptor_name | Mice |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D008099 |
| mesh[4].is_major_topic | True |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Liver |
| mesh[5].qualifier_ui | Q000379 |
| mesh[5].descriptor_ui | D021621 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | methods |
| mesh[5].descriptor_name | Imaging, Three-Dimensional |
| mesh[6].qualifier_ui | Q000379 |
| mesh[6].descriptor_ui | D008856 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | methods |
| mesh[6].descriptor_name | Microscopy, Fluorescence |
| mesh[7].qualifier_ui | Q000379 |
| mesh[7].descriptor_ui | D007091 |
| mesh[7].is_major_topic | False |
| mesh[7].qualifier_name | methods |
| mesh[7].descriptor_name | Image Processing, Computer-Assisted |
| mesh[8].qualifier_ui | |
| mesh[8].descriptor_ui | D000077321 |
| mesh[8].is_major_topic | True |
| mesh[8].qualifier_name | |
| mesh[8].descriptor_name | Deep Learning |
| mesh[9].qualifier_ui | |
| mesh[9].descriptor_ui | D006801 |
| mesh[9].is_major_topic | False |
| mesh[9].qualifier_name | |
| mesh[9].descriptor_name | Humans |
| mesh[10].qualifier_ui | |
| mesh[10].descriptor_ui | D000818 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | |
| mesh[10].descriptor_name | Animals |
| mesh[11].qualifier_ui | |
| mesh[11].descriptor_ui | D051379 |
| mesh[11].is_major_topic | False |
| mesh[11].qualifier_name | |
| mesh[11].descriptor_name | Mice |
| mesh[12].qualifier_ui | |
| mesh[12].descriptor_ui | D008099 |
| mesh[12].is_major_topic | True |
| mesh[12].qualifier_name | |
| mesh[12].descriptor_name | Liver |
| mesh[13].qualifier_ui | Q000379 |
| mesh[13].descriptor_ui | D021621 |
| mesh[13].is_major_topic | False |
| mesh[13].qualifier_name | methods |
| mesh[13].descriptor_name | Imaging, Three-Dimensional |
| mesh[14].qualifier_ui | Q000379 |
| mesh[14].descriptor_ui | D008856 |
| mesh[14].is_major_topic | False |
| mesh[14].qualifier_name | methods |
| mesh[14].descriptor_name | Microscopy, Fluorescence |
| mesh[15].qualifier_ui | Q000379 |
| mesh[15].descriptor_ui | D007091 |
| mesh[15].is_major_topic | False |
| mesh[15].qualifier_name | methods |
| mesh[15].descriptor_name | Image Processing, Computer-Assisted |
| mesh[16].qualifier_ui | |
| mesh[16].descriptor_ui | D000077321 |
| mesh[16].is_major_topic | True |
| mesh[16].qualifier_name | |
| mesh[16].descriptor_name | Deep Learning |
| mesh[17].qualifier_ui | |
| mesh[17].descriptor_ui | D006801 |
| mesh[17].is_major_topic | False |
| mesh[17].qualifier_name | |
| mesh[17].descriptor_name | Humans |
| mesh[18].qualifier_ui | |
| mesh[18].descriptor_ui | D000818 |
| mesh[18].is_major_topic | False |
| mesh[18].qualifier_name | |
| mesh[18].descriptor_name | Animals |
| mesh[19].qualifier_ui | |
| mesh[19].descriptor_ui | D051379 |
| mesh[19].is_major_topic | False |
| mesh[19].qualifier_name | |
| mesh[19].descriptor_name | Mice |
| mesh[20].qualifier_ui | |
| mesh[20].descriptor_ui | D008099 |
| mesh[20].is_major_topic | True |
| mesh[20].qualifier_name | |
| mesh[20].descriptor_name | Liver |
| mesh[21].qualifier_ui | Q000379 |
| mesh[21].descriptor_ui | D021621 |
| mesh[21].is_major_topic | False |
| mesh[21].qualifier_name | methods |
| mesh[21].descriptor_name | Imaging, Three-Dimensional |
| mesh[22].qualifier_ui | Q000379 |
| mesh[22].descriptor_ui | D008856 |
| mesh[22].is_major_topic | False |
| mesh[22].qualifier_name | methods |
| mesh[22].descriptor_name | Microscopy, Fluorescence |
| mesh[23].qualifier_ui | Q000379 |
| mesh[23].descriptor_ui | D007091 |
| mesh[23].is_major_topic | False |
| mesh[23].qualifier_name | methods |
| mesh[23].descriptor_name | Image Processing, Computer-Assisted |
| type | article |
| title | Virtual tissue microstructure reconstruction across species using generative deep learning |
| awards[0].id | https://openalex.org/G4379057255 |
| awards[0].funder_id | https://openalex.org/F4320338073 |
| awards[0].display_name | |
| awards[0].funder_award_id | ANID Fondecyt regular 1200965 and VRID-UdeC 2024001079INV |
| awards[0].funder_display_name | Fondo Nacional de Desarrollo Científico y Tecnológico |
| biblio.issue | 7 |
| biblio.volume | 19 |
| biblio.last_page | e0306073 |
| biblio.first_page | e0306073 |
| topics[0].id | https://openalex.org/T12859 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9994999766349792 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1304 |
| topics[0].subfield.display_name | Biophysics |
| topics[0].display_name | Cell Image Analysis Techniques |
| topics[1].id | https://openalex.org/T10862 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9965999722480774 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | AI in cancer detection |
| topics[2].id | https://openalex.org/T10775 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9879000186920166 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Generative Adversarial Networks and Image Synthesis |
| funders[0].id | https://openalex.org/F4320338073 |
| funders[0].ror | https://ror.org/02ap3w078 |
| funders[0].display_name | Fondo Nacional de Desarrollo Científico y Tecnológico |
| is_xpac | False |
| apc_list.value | 1805 |
| apc_list.currency | USD |
| apc_list.value_usd | 1805 |
| apc_paid.value | 1805 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1805 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.5197950601577759 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C87976508 |
| concepts[1].level | 2 |
| concepts[1].score | 0.4625481963157654 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1498213 |
| concepts[1].display_name | Microstructure |
| concepts[2].id | https://openalex.org/C108583219 |
| concepts[2].level | 2 |
| concepts[2].score | 0.46203210949897766 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q197536 |
| concepts[2].display_name | Deep learning |
| concepts[3].id | https://openalex.org/C2992176824 |
| concepts[3].level | 2 |
| concepts[3].score | 0.4570493996143341 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q9368 |
| concepts[3].display_name | Liver tissue |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.4231884479522705 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C86803240 |
| concepts[5].level | 0 |
| concepts[5].score | 0.40176117420196533 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[5].display_name | Biology |
| concepts[6].id | https://openalex.org/C186060115 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3593220114707947 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q30336093 |
| concepts[6].display_name | Biological system |
| concepts[7].id | https://openalex.org/C70721500 |
| concepts[7].level | 1 |
| concepts[7].score | 0.32267874479293823 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[7].display_name | Computational biology |
| concepts[8].id | https://openalex.org/C192562407 |
| concepts[8].level | 0 |
| concepts[8].score | 0.18006625771522522 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[8].display_name | Materials science |
| concepts[9].id | https://openalex.org/C134018914 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q162606 |
| concepts[9].display_name | Endocrinology |
| concepts[10].id | https://openalex.org/C191897082 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11467 |
| concepts[10].display_name | Metallurgy |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.5197950601577759 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/microstructure |
| keywords[1].score | 0.4625481963157654 |
| keywords[1].display_name | Microstructure |
| keywords[2].id | https://openalex.org/keywords/deep-learning |
| keywords[2].score | 0.46203210949897766 |
| keywords[2].display_name | Deep learning |
| keywords[3].id | https://openalex.org/keywords/liver-tissue |
| keywords[3].score | 0.4570493996143341 |
| keywords[3].display_name | Liver tissue |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.4231884479522705 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/biology |
| keywords[5].score | 0.40176117420196533 |
| keywords[5].display_name | Biology |
| keywords[6].id | https://openalex.org/keywords/biological-system |
| keywords[6].score | 0.3593220114707947 |
| keywords[6].display_name | Biological system |
| keywords[7].id | https://openalex.org/keywords/computational-biology |
| keywords[7].score | 0.32267874479293823 |
| keywords[7].display_name | Computational biology |
| keywords[8].id | https://openalex.org/keywords/materials-science |
| keywords[8].score | 0.18006625771522522 |
| keywords[8].display_name | Materials science |
| language | en |
| locations[0].id | doi:10.1371/journal.pone.0306073 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S202381698 |
| locations[0].source.issn | 1932-6203 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1932-6203 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | PLoS ONE |
| locations[0].source.host_organization | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_name | Public Library of Science |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_lineage_names | Public Library of Science |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printable |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | PLOS ONE |
| locations[0].landing_page_url | https://doi.org/10.1371/journal.pone.0306073 |
| locations[1].id | pmid:38995963 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | PloS one |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/38995963 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:11244806 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | other-oa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/other-oa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | PLoS One |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/11244806 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5098532820 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Nicolás Bettancourt |
| authorships[0].countries | CL |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I172787465 |
| authorships[0].affiliations[0].raw_affiliation_string | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I172787465 |
| authorships[0].affiliations[1].raw_affiliation_string | Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[0].affiliations[2].institution_ids | https://openalex.org/I172787465 |
| authorships[0].affiliations[2].raw_affiliation_string | Faculty of Engineering, Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile |
| authorships[0].institutions[0].id | https://openalex.org/I172787465 |
| authorships[0].institutions[0].ror | https://ror.org/0460jpj73 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I172787465 |
| authorships[0].institutions[0].country_code | CL |
| authorships[0].institutions[0].display_name | University of Concepción |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Nicolás Bettancourt |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile, Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile, Faculty of Engineering, Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile |
| authorships[1].author.id | https://openalex.org/A5053075530 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Cristian Pérez-Gallardo |
| authorships[1].countries | CL |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I172787465 |
| authorships[1].affiliations[0].raw_affiliation_string | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I172787465 |
| authorships[1].affiliations[1].raw_affiliation_string | Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[1].institutions[0].id | https://openalex.org/I172787465 |
| authorships[1].institutions[0].ror | https://ror.org/0460jpj73 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I172787465 |
| authorships[1].institutions[0].country_code | CL |
| authorships[1].institutions[0].display_name | University of Concepción |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Cristian Pérez-Gallardo |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile, Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[2].author.id | https://openalex.org/A5072075645 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Valeria Candia |
| authorships[2].countries | CL |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I172787465 |
| authorships[2].affiliations[0].raw_affiliation_string | Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[2].affiliations[1].institution_ids | https://openalex.org/I172787465 |
| authorships[2].affiliations[1].raw_affiliation_string | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile |
| authorships[2].institutions[0].id | https://openalex.org/I172787465 |
| authorships[2].institutions[0].ror | https://ror.org/0460jpj73 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I172787465 |
| authorships[2].institutions[0].country_code | CL |
| authorships[2].institutions[0].display_name | University of Concepción |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Valeria Candia |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile, Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[3].author.id | https://openalex.org/A5027223476 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-9988-400X |
| authorships[3].author.display_name | Pamela Guevara |
| authorships[3].countries | CL |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I172787465 |
| authorships[3].affiliations[0].raw_affiliation_string | Faculty of Engineering, Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile |
| authorships[3].institutions[0].id | https://openalex.org/I172787465 |
| authorships[3].institutions[0].ror | https://ror.org/0460jpj73 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I172787465 |
| authorships[3].institutions[0].country_code | CL |
| authorships[3].institutions[0].display_name | University of Concepción |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Pamela Guevara |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Faculty of Engineering, Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile |
| authorships[4].author.id | https://openalex.org/A5078646809 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-6137-1193 |
| authorships[4].author.display_name | Yannis Kalaidzidis |
| authorships[4].countries | DE |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210159854 |
| authorships[4].affiliations[0].raw_affiliation_string | Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany |
| authorships[4].institutions[0].id | https://openalex.org/I4210159854 |
| authorships[4].institutions[0].ror | https://ror.org/05b8d3w18 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I149899117, https://openalex.org/I4210159854 |
| authorships[4].institutions[0].country_code | DE |
| authorships[4].institutions[0].display_name | Max Planck Institute of Molecular Cell Biology and Genetics |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Yannis Kalaidzidis |
| authorships[4].is_corresponding | True |
| authorships[4].raw_affiliation_strings | Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany |
| authorships[5].author.id | https://openalex.org/A5012441246 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-7490-4235 |
| authorships[5].author.display_name | Marino Zerial |
| authorships[5].countries | DE |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210159854 |
| authorships[5].affiliations[0].raw_affiliation_string | Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany |
| authorships[5].institutions[0].id | https://openalex.org/I4210159854 |
| authorships[5].institutions[0].ror | https://ror.org/05b8d3w18 |
| authorships[5].institutions[0].type | facility |
| authorships[5].institutions[0].lineage | https://openalex.org/I149899117, https://openalex.org/I4210159854 |
| authorships[5].institutions[0].country_code | DE |
| authorships[5].institutions[0].display_name | Max Planck Institute of Molecular Cell Biology and Genetics |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Marino Zerial |
| authorships[5].is_corresponding | True |
| authorships[5].raw_affiliation_strings | Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany |
| authorships[6].author.id | https://openalex.org/A5035073302 |
| authorships[6].author.orcid | https://orcid.org/0000-0003-1546-0475 |
| authorships[6].author.display_name | Fabián Segovia‐Miranda |
| authorships[6].countries | CL |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I172787465 |
| authorships[6].affiliations[0].raw_affiliation_string | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile |
| authorships[6].affiliations[1].institution_ids | https://openalex.org/I172787465 |
| authorships[6].affiliations[1].raw_affiliation_string | Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[6].institutions[0].id | https://openalex.org/I172787465 |
| authorships[6].institutions[0].ror | https://ror.org/0460jpj73 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I172787465 |
| authorships[6].institutions[0].country_code | CL |
| authorships[6].institutions[0].display_name | University of Concepción |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Fabián Segovia-Miranda |
| authorships[6].is_corresponding | True |
| authorships[6].raw_affiliation_strings | Faculty of Biological Sciences, Department of Cell Biology, Universidad de Concepción, Concepción, Chile, Faculty of Biological Sciences, Grupo de Procesos en Biología del Desarrollo (GDeP), Universidad de Concepción, Concepción, Chile |
| authorships[7].author.id | https://openalex.org/A5043253041 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-9578-2556 |
| authorships[7].author.display_name | Hernán Morales‐Navarrete |
| authorships[7].countries | DE, EC |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I189712700 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Systems Biology of Development, University of Konstanz, Konstanz, Germany |
| authorships[7].affiliations[1].institution_ids | https://openalex.org/I4210140740 |
| authorships[7].affiliations[1].raw_affiliation_string | Facultad de Ciencias Técnicas, Universidad Internacional Del Ecuador UIDE, Quito, Ecuador |
| authorships[7].institutions[0].id | https://openalex.org/I189712700 |
| authorships[7].institutions[0].ror | https://ror.org/0546hnb39 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I189712700 |
| authorships[7].institutions[0].country_code | DE |
| authorships[7].institutions[0].display_name | University of Konstanz |
| authorships[7].institutions[1].id | https://openalex.org/I4210140740 |
| authorships[7].institutions[1].ror | https://ror.org/04xf2rc74 |
| authorships[7].institutions[1].type | education |
| authorships[7].institutions[1].lineage | https://openalex.org/I4210140740 |
| authorships[7].institutions[1].country_code | EC |
| authorships[7].institutions[1].display_name | Universidad Internacional del Ecuador |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Hernán Morales-Navarrete |
| authorships[7].is_corresponding | True |
| authorships[7].raw_affiliation_strings | Department of Systems Biology of Development, University of Konstanz, Konstanz, Germany, Facultad de Ciencias Técnicas, Universidad Internacional Del Ecuador UIDE, Quito, Ecuador |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printable |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Virtual tissue microstructure reconstruction across species using generative deep learning |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T12859 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9994999766349792 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1304 |
| primary_topic.subfield.display_name | Biophysics |
| primary_topic.display_name | Cell Image Analysis Techniques |
| related_works | https://openalex.org/W2058940780, https://openalex.org/W2090404944, https://openalex.org/W2046332915, https://openalex.org/W2354424856, https://openalex.org/W2375093060, https://openalex.org/W2605776044, https://openalex.org/W2392473810, https://openalex.org/W2803456621, https://openalex.org/W2357211366, https://openalex.org/W3045762471 |
| cited_by_count | 0 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1371/journal.pone.0306073 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S202381698 |
| best_oa_location.source.issn | 1932-6203 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1932-6203 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | PLoS ONE |
| best_oa_location.source.host_organization | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_name | Public Library of Science |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_lineage_names | Public Library of Science |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printable |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | PLOS ONE |
| best_oa_location.landing_page_url | https://doi.org/10.1371/journal.pone.0306073 |
| primary_location.id | doi:10.1371/journal.pone.0306073 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S202381698 |
| primary_location.source.issn | 1932-6203 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1932-6203 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | PLoS ONE |
| primary_location.source.host_organization | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_name | Public Library of Science |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_lineage_names | Public Library of Science |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0306073&type=printable |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | PLOS ONE |
| primary_location.landing_page_url | https://doi.org/10.1371/journal.pone.0306073 |
| publication_date | 2024-07-12 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W2760605310, https://openalex.org/W2055291049, https://openalex.org/W3185341883, https://openalex.org/W3195893403, https://openalex.org/W2043875880, https://openalex.org/W2990404188, https://openalex.org/W2952802990, https://openalex.org/W3037432527, https://openalex.org/W4391512139, https://openalex.org/W1988762667, https://openalex.org/W2395973326, https://openalex.org/W3119060929, https://openalex.org/W3170236431, https://openalex.org/W2995395945, https://openalex.org/W4307134788, https://openalex.org/W2919115771, https://openalex.org/W3198842780, https://openalex.org/W4296772911, https://openalex.org/W2946901414, https://openalex.org/W2811106513, https://openalex.org/W3210642206, https://openalex.org/W6746806848, https://openalex.org/W2949493305, https://openalex.org/W2797749376, https://openalex.org/W4375858815, https://openalex.org/W3096831136, https://openalex.org/W2166572577, https://openalex.org/W2145876651, https://openalex.org/W2622865236, https://openalex.org/W1901129140, https://openalex.org/W2605287558, https://openalex.org/W2963981733, https://openalex.org/W2552465644, https://openalex.org/W2970365501, https://openalex.org/W4210482911, https://openalex.org/W4301206121, https://openalex.org/W2963073614, https://openalex.org/W2768673271, https://openalex.org/W2962793481, https://openalex.org/W2786055572 |
| referenced_works_count | 40 |
| abstract_inverted_index.a | 52, 155, 185 |
| abstract_inverted_index.3D | 59 |
| abstract_inverted_index.We | 100 |
| abstract_inverted_index.as | 31, 74, 98 |
| abstract_inverted_index.be | 145 |
| abstract_inverted_index.by | 81 |
| abstract_inverted_index.in | 10, 43, 107, 117, 151, 158, 195 |
| abstract_inverted_index.is | 3, 34 |
| abstract_inverted_index.of | 28, 86, 95 |
| abstract_inverted_index.on | 17 |
| abstract_inverted_index.to | 38, 103, 138 |
| abstract_inverted_index.we | 49, 135 |
| abstract_inverted_index.Our | 162 |
| abstract_inverted_index.and | 46, 67, 78, 109, 124, 169, 199 |
| abstract_inverted_index.due | 37, 148 |
| abstract_inverted_index.for | 5, 57, 188 |
| abstract_inverted_index.its | 39 |
| abstract_inverted_index.our | 182 |
| abstract_inverted_index.the | 24, 32, 93 |
| abstract_inverted_index.(3D) | 26 |
| abstract_inverted_index.able | 137 |
| abstract_inverted_index.bile | 121 |
| abstract_inverted_index.cell | 126 |
| abstract_inverted_index.deep | 54, 152, 159 |
| abstract_inverted_index.from | 128 |
| abstract_inverted_index.high | 115 |
| abstract_inverted_index.like | 120 |
| abstract_inverted_index.need | 94 |
| abstract_inverted_index.poor | 75 |
| abstract_inverted_index.such | 30, 73 |
| abstract_inverted_index.that | 143 |
| abstract_inverted_index.tool | 166 |
| abstract_inverted_index.were | 136 |
| abstract_inverted_index.with | 177, 192 |
| abstract_inverted_index.Here, | 48 |
| abstract_inverted_index.actin | 129 |
| abstract_inverted_index.dense | 153 |
| abstract_inverted_index.human | 110 |
| abstract_inverted_index.large | 90 |
| abstract_inverted_index.liver | 111 |
| abstract_inverted_index.mouse | 108 |
| abstract_inverted_index.novel | 53 |
| abstract_inverted_index.roles | 42 |
| abstract_inverted_index.shows | 114 |
| abstract_inverted_index.their | 18 |
| abstract_inverted_index.using | 63, 133 |
| abstract_inverted_index.Tissue | 13 |
| abstract_inverted_index.across | 89 |
| abstract_inverted_index.cannot | 144 |
| abstract_inverted_index.depend | 16 |
| abstract_inverted_index.imaged | 147 |
| abstract_inverted_index.images | 97 |
| abstract_inverted_index.input. | 99 |
| abstract_inverted_index.liver, | 33 |
| abstract_inverted_index.method | 183 |
| abstract_inverted_index.paired | 96 |
| abstract_inverted_index.shapes | 127 |
| abstract_inverted_index.tissue | 1, 20, 60, 87, 105, 141, 160, 172, 190 |
| abstract_inverted_index.Kupffer | 125 |
| abstract_inverted_index.analyze | 104 |
| abstract_inverted_index.applied | 101 |
| abstract_inverted_index.complex | 7 |
| abstract_inverted_index.diverse | 196 |
| abstract_inverted_index.images. | 131 |
| abstract_inverted_index.largely | 15 |
| abstract_inverted_index.levels. | 180 |
| abstract_inverted_index.present | 50 |
| abstract_inverted_index.systems | 9 |
| abstract_inverted_index.tissue. | 112 |
| abstract_inverted_index.varying | 178 |
| abstract_inverted_index.virtual | 58, 164 |
| abstract_inverted_index.volumes | 91 |
| abstract_inverted_index.without | 92 |
| abstract_inverted_index.Networks | 66 |
| abstract_inverted_index.Overall, | 181 |
| abstract_inverted_index.TiMiGNet | 70, 102, 113, 134 |
| abstract_inverted_index.antibody | 76 |
| abstract_inverted_index.approach | 56, 187 |
| abstract_inverted_index.contexts | 198 |
| abstract_inverted_index.directly | 146 |
| abstract_inverted_index.imaging. | 161 |
| abstract_inverted_index.learning | 55 |
| abstract_inverted_index.meshwork | 130 |
| abstract_inverted_index.powerful | 186 |
| abstract_inverted_index.species. | 12, 200 |
| abstract_inverted_index.studying | 23, 189 |
| abstract_inverted_index.tissues, | 29, 154 |
| abstract_inverted_index.Analyzing | 0 |
| abstract_inverted_index.TiMiGNet, | 51 |
| abstract_inverted_index.accurate, | 83 |
| abstract_inverted_index.analysis, | 174 |
| abstract_inverted_index.conserved | 40 |
| abstract_inverted_index.different | 11 |
| abstract_inverted_index.efficient | 170 |
| abstract_inverted_index.essential | 4, 41 |
| abstract_inverted_index.expertise | 179 |
| abstract_inverted_index.functions | 14 |
| abstract_inverted_index.intrinsic | 19 |
| abstract_inverted_index.metabolic | 44 |
| abstract_inverted_index.overcomes | 71 |
| abstract_inverted_index.processes | 45 |
| abstract_inverted_index.Generative | 64 |
| abstract_inverted_index.Therefore, | 22 |
| abstract_inverted_index.accessible | 168 |
| abstract_inverted_index.biological | 8, 197 |
| abstract_inverted_index.challenges | 72 |
| abstract_inverted_index.components | 88 |
| abstract_inverted_index.generating | 82 |
| abstract_inverted_index.predicting | 118 |
| abstract_inverted_index.prediction | 165 |
| abstract_inverted_index.procedures | 80 |
| abstract_inverted_index.represents | 184 |
| abstract_inverted_index.sinusoids, | 123 |
| abstract_inverted_index.structures | 119, 142 |
| abstract_inverted_index.Adversarial | 65 |
| abstract_inverted_index.Remarkably, | 132 |
| abstract_inverted_index.advancement | 157 |
| abstract_inverted_index.canaliculi, | 122 |
| abstract_inverted_index.facilitates | 167 |
| abstract_inverted_index.fascinating | 36 |
| abstract_inverted_index.limitations | 150 |
| abstract_inverted_index.microscopy. | 69 |
| abstract_inverted_index.open-source | 163 |
| abstract_inverted_index.penetration | 77 |
| abstract_inverted_index.performance | 116 |
| abstract_inverted_index.predictions | 85 |
| abstract_inverted_index.reconstruct | 140 |
| abstract_inverted_index.researchers | 176 |
| abstract_inverted_index.significant | 156 |
| abstract_inverted_index.applications | 194 |
| abstract_inverted_index.experimental | 149 |
| abstract_inverted_index.far-reaching | 193 |
| abstract_inverted_index.fluorescence | 68 |
| abstract_inverted_index.particularly | 35 |
| abstract_inverted_index.accommodating | 175 |
| abstract_inverted_index.architecture. | 21 |
| abstract_inverted_index.multi-species | 171 |
| abstract_inverted_index.understanding | 6 |
| abstract_inverted_index.microstructure | 2, 27, 61, 106, 173 |
| abstract_inverted_index.reconstruction | 62 |
| abstract_inverted_index.time-intensive | 79 |
| abstract_inverted_index.computationally | 139 |
| abstract_inverted_index.detoxification. | 47 |
| abstract_inverted_index.high-resolution | 84 |
| abstract_inverted_index.microstructure, | 191 |
| abstract_inverted_index.three-dimensional | 25 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5098532820, https://openalex.org/A5035073302, https://openalex.org/A5078646809, https://openalex.org/A5027223476, https://openalex.org/A5043253041, https://openalex.org/A5053075530, https://openalex.org/A5072075645, https://openalex.org/A5012441246 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I172787465, https://openalex.org/I189712700, https://openalex.org/I4210140740, https://openalex.org/I4210159854 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.07765531 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |