Detecting and Correcting False Transients in Calcium Imaging Article Swipe
Jeffrey L. Gauthier
,
Sue Ann Koay
,
Edward H. Nieh
,
David W. Tank
,
Jonathan W. Pillow
,
Adam S. Charles
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/473470
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/473470
Population recordings of calcium activity are a major source of insight into neural function. Large dataset sizes often require automated methods, but automation can introduce errors that are difficult to detect. Here we show that automatic time course estimation can sometimes lead to significant misattribution errors, in which fluorescence is ascribed to the wrong cell. Misattribution arises when the shapes of overlapping cells are imperfectly defined, or when entire cells or processes are not identified, and misattribution can even be produced by methods specifically designed to handle overlap. To diagnose this problem, we develop a transient-by-transient metric and a visualization tool that allow users to quickly assess the degree of misattribution in large populations. To filter out misattribution, we also design a robust estimator that explicitly accounts for contaminating signals in a generative model. Our methods can be combined with essentially any cell finding technique, empowering users to diagnose and correct at large scale a problem that has the potential to significantly alter scientific conclusions.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/473470
- https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdf
- OA Status
- green
- Cited By
- 13
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2900913494
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2900913494Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/473470Digital Object Identifier
- Title
-
Detecting and Correcting False Transients in Calcium ImagingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-11-19Full publication date if available
- Authors
-
Jeffrey L. Gauthier, Sue Ann Koay, Edward H. Nieh, David W. Tank, Jonathan W. Pillow, Adam S. CharlesList of authors in order
- Landing page
-
https://doi.org/10.1101/473470Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdfDirect OA link when available
- Concepts
-
Misattribution of memory, Computer science, Metric (unit), Jaccard index, Population, Artificial intelligence, Machine learning, Algorithm, Pattern recognition (psychology), Neuroscience, Psychology, Engineering, Demography, Operations management, Sociology, CognitionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
13Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2022: 3, 2021: 3, 2020: 2, 2019: 3Per-year citation counts (last 5 years)
- References (count)
-
35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2900913494 |
|---|---|
| doi | https://doi.org/10.1101/473470 |
| ids.doi | https://doi.org/10.1101/473470 |
| ids.mag | 2900913494 |
| ids.openalex | https://openalex.org/W2900913494 |
| fwci | 1.30304259 |
| type | preprint |
| title | Detecting and Correcting False Transients in Calcium Imaging |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10581 |
| topics[0].field.id | https://openalex.org/fields/28 |
| topics[0].field.display_name | Neuroscience |
| topics[0].score | 0.9997000098228455 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2805 |
| topics[0].subfield.display_name | Cognitive Neuroscience |
| topics[0].display_name | Neural dynamics and brain function |
| topics[1].id | https://openalex.org/T10540 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9951000213623047 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1304 |
| topics[1].subfield.display_name | Biophysics |
| topics[1].display_name | Advanced Fluorescence Microscopy Techniques |
| topics[2].id | https://openalex.org/T12859 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.989300012588501 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1304 |
| topics[2].subfield.display_name | Biophysics |
| topics[2].display_name | Cell Image Analysis Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C120039088 |
| concepts[0].level | 3 |
| concepts[0].score | 0.9455361366271973 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q6875176 |
| concepts[0].display_name | Misattribution of memory |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6527303457260132 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C176217482 |
| concepts[2].level | 2 |
| concepts[2].score | 0.49671560525894165 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q860554 |
| concepts[2].display_name | Metric (unit) |
| concepts[3].id | https://openalex.org/C203519979 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4767923355102539 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q865360 |
| concepts[3].display_name | Jaccard index |
| concepts[4].id | https://openalex.org/C2908647359 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4539756774902344 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2625603 |
| concepts[4].display_name | Population |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.41216665506362915 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C119857082 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3612983226776123 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[6].display_name | Machine learning |
| concepts[7].id | https://openalex.org/C11413529 |
| concepts[7].level | 1 |
| concepts[7].score | 0.33777928352355957 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[7].display_name | Algorithm |
| concepts[8].id | https://openalex.org/C153180895 |
| concepts[8].level | 2 |
| concepts[8].score | 0.2769771218299866 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[8].display_name | Pattern recognition (psychology) |
| concepts[9].id | https://openalex.org/C169760540 |
| concepts[9].level | 1 |
| concepts[9].score | 0.1432756781578064 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q207011 |
| concepts[9].display_name | Neuroscience |
| concepts[10].id | https://openalex.org/C15744967 |
| concepts[10].level | 0 |
| concepts[10].score | 0.11741423606872559 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[10].display_name | Psychology |
| concepts[11].id | https://openalex.org/C127413603 |
| concepts[11].level | 0 |
| concepts[11].score | 0.11732816696166992 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[11].display_name | Engineering |
| concepts[12].id | https://openalex.org/C149923435 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q37732 |
| concepts[12].display_name | Demography |
| concepts[13].id | https://openalex.org/C21547014 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1423657 |
| concepts[13].display_name | Operations management |
| concepts[14].id | https://openalex.org/C144024400 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q21201 |
| concepts[14].display_name | Sociology |
| concepts[15].id | https://openalex.org/C169900460 |
| concepts[15].level | 2 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q2200417 |
| concepts[15].display_name | Cognition |
| keywords[0].id | https://openalex.org/keywords/misattribution-of-memory |
| keywords[0].score | 0.9455361366271973 |
| keywords[0].display_name | Misattribution of memory |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6527303457260132 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/metric |
| keywords[2].score | 0.49671560525894165 |
| keywords[2].display_name | Metric (unit) |
| keywords[3].id | https://openalex.org/keywords/jaccard-index |
| keywords[3].score | 0.4767923355102539 |
| keywords[3].display_name | Jaccard index |
| keywords[4].id | https://openalex.org/keywords/population |
| keywords[4].score | 0.4539756774902344 |
| keywords[4].display_name | Population |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.41216665506362915 |
| keywords[5].display_name | Artificial intelligence |
| keywords[6].id | https://openalex.org/keywords/machine-learning |
| keywords[6].score | 0.3612983226776123 |
| keywords[6].display_name | Machine learning |
| keywords[7].id | https://openalex.org/keywords/algorithm |
| keywords[7].score | 0.33777928352355957 |
| keywords[7].display_name | Algorithm |
| keywords[8].id | https://openalex.org/keywords/pattern-recognition |
| keywords[8].score | 0.2769771218299866 |
| keywords[8].display_name | Pattern recognition (psychology) |
| keywords[9].id | https://openalex.org/keywords/neuroscience |
| keywords[9].score | 0.1432756781578064 |
| keywords[9].display_name | Neuroscience |
| keywords[10].id | https://openalex.org/keywords/psychology |
| keywords[10].score | 0.11741423606872559 |
| keywords[10].display_name | Psychology |
| keywords[11].id | https://openalex.org/keywords/engineering |
| keywords[11].score | 0.11732816696166992 |
| keywords[11].display_name | Engineering |
| language | en |
| locations[0].id | doi:10.1101/473470 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/473470 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5023712673 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-0509-8532 |
| authorships[0].author.display_name | Jeffrey L. Gauthier |
| authorships[0].countries | IT, US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[0].affiliations[0].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[0].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[0].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[0].institutions[0].type | facility |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[0].institutions[0].country_code | IT |
| authorships[0].institutions[0].display_name | Neuroscience Institute |
| authorships[0].institutions[1].id | https://openalex.org/I20089843 |
| authorships[0].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[0].institutions[1].country_code | US |
| authorships[0].institutions[1].display_name | Princeton University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Jeff L. Gauthier |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Princeton Neuroscience Institute, Princeton University |
| authorships[1].author.id | https://openalex.org/A5101936262 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-9648-2475 |
| authorships[1].author.display_name | Sue Ann Koay |
| authorships[1].countries | IT, US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[1].affiliations[0].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[1].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[1].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[1].institutions[0].type | facility |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[1].institutions[0].country_code | IT |
| authorships[1].institutions[0].display_name | Neuroscience Institute |
| authorships[1].institutions[1].id | https://openalex.org/I20089843 |
| authorships[1].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[1].institutions[1].type | education |
| authorships[1].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[1].institutions[1].country_code | US |
| authorships[1].institutions[1].display_name | Princeton University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Sue Ann Koay |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Princeton Neuroscience Institute, Princeton University |
| authorships[2].author.id | https://openalex.org/A5031770042 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Edward H. Nieh |
| authorships[2].countries | IT, US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[2].affiliations[0].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[2].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[2].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[2].institutions[0].country_code | IT |
| authorships[2].institutions[0].display_name | Neuroscience Institute |
| authorships[2].institutions[1].id | https://openalex.org/I20089843 |
| authorships[2].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[2].institutions[1].type | education |
| authorships[2].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[2].institutions[1].country_code | US |
| authorships[2].institutions[1].display_name | Princeton University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Edward H. Nieh |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Princeton Neuroscience Institute, Princeton University |
| authorships[3].author.id | https://openalex.org/A5042778805 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-9423-4267 |
| authorships[3].author.display_name | David W. Tank |
| authorships[3].countries | IT, US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[3].affiliations[0].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I20089843 |
| authorships[3].affiliations[1].raw_affiliation_string | Department of Molecular Biology, Princeton University |
| authorships[3].affiliations[2].institution_ids | https://openalex.org/I20089843 |
| authorships[3].affiliations[2].raw_affiliation_string | Bezos Center for Neural Circuit Dynamics, Princeton University |
| authorships[3].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[3].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[3].institutions[0].country_code | IT |
| authorships[3].institutions[0].display_name | Neuroscience Institute |
| authorships[3].institutions[1].id | https://openalex.org/I20089843 |
| authorships[3].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[3].institutions[1].type | education |
| authorships[3].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[3].institutions[1].country_code | US |
| authorships[3].institutions[1].display_name | Princeton University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | David W. Tank |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Bezos Center for Neural Circuit Dynamics, Princeton University, Department of Molecular Biology, Princeton University, Princeton Neuroscience Institute, Princeton University |
| authorships[4].author.id | https://openalex.org/A5047908820 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-3638-8831 |
| authorships[4].author.display_name | Jonathan W. Pillow |
| authorships[4].countries | IT, US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I20089843 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Psychology, Princeton University |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[4].affiliations[1].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[4].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[4].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[4].institutions[0].country_code | IT |
| authorships[4].institutions[0].display_name | Neuroscience Institute |
| authorships[4].institutions[1].id | https://openalex.org/I20089843 |
| authorships[4].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[4].institutions[1].country_code | US |
| authorships[4].institutions[1].display_name | Princeton University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Jonathan W. Pillow |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Psychology, Princeton University, Princeton Neuroscience Institute, Princeton University |
| authorships[5].author.id | https://openalex.org/A5062177768 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-9045-3489 |
| authorships[5].author.display_name | Adam S. Charles |
| authorships[5].countries | IT, US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I20089843, https://openalex.org/I4210113153 |
| authorships[5].affiliations[0].raw_affiliation_string | Princeton Neuroscience Institute, Princeton University |
| authorships[5].institutions[0].id | https://openalex.org/I4210113153 |
| authorships[5].institutions[0].ror | https://ror.org/0240rwx68 |
| authorships[5].institutions[0].type | facility |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210113153, https://openalex.org/I4210155236 |
| authorships[5].institutions[0].country_code | IT |
| authorships[5].institutions[0].display_name | Neuroscience Institute |
| authorships[5].institutions[1].id | https://openalex.org/I20089843 |
| authorships[5].institutions[1].ror | https://ror.org/00hx57361 |
| authorships[5].institutions[1].type | education |
| authorships[5].institutions[1].lineage | https://openalex.org/I20089843 |
| authorships[5].institutions[1].country_code | US |
| authorships[5].institutions[1].display_name | Princeton University |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Adam S. Charles |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Princeton Neuroscience Institute, Princeton University |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Detecting and Correcting False Transients in Calcium Imaging |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10581 |
| primary_topic.field.id | https://openalex.org/fields/28 |
| primary_topic.field.display_name | Neuroscience |
| primary_topic.score | 0.9997000098228455 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2805 |
| primary_topic.subfield.display_name | Cognitive Neuroscience |
| primary_topic.display_name | Neural dynamics and brain function |
| related_works | https://openalex.org/W4254879869, https://openalex.org/W3022576529, https://openalex.org/W2891695624, https://openalex.org/W2628526247, https://openalex.org/W4233655303, https://openalex.org/W2596401011, https://openalex.org/W2157685728, https://openalex.org/W2913569734, https://openalex.org/W2162199785, https://openalex.org/W3135750408 |
| cited_by_count | 13 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2022 |
| counts_by_year[1].cited_by_count | 3 |
| counts_by_year[2].year | 2021 |
| counts_by_year[2].cited_by_count | 3 |
| counts_by_year[3].year | 2020 |
| counts_by_year[3].cited_by_count | 2 |
| counts_by_year[4].year | 2019 |
| counts_by_year[4].cited_by_count | 3 |
| counts_by_year[5].year | 2018 |
| counts_by_year[5].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/473470 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/473470 |
| primary_location.id | doi:10.1101/473470 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/19/473470.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/473470 |
| publication_date | 2018-11-19 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W2134363815, https://openalex.org/W2171332611, https://openalex.org/W2079960018, https://openalex.org/W1964314167, https://openalex.org/W2061464631, https://openalex.org/W1982918139, https://openalex.org/W2031582756, https://openalex.org/W2074967846, https://openalex.org/W2145264576, https://openalex.org/W2805271873, https://openalex.org/W2512047842, https://openalex.org/W2019633617, https://openalex.org/W2038573700, https://openalex.org/W2751966825, https://openalex.org/W2794648976, https://openalex.org/W2086871516, https://openalex.org/W1889678891, https://openalex.org/W2068809501, https://openalex.org/W1975032719, https://openalex.org/W2126116691, https://openalex.org/W2136213019, https://openalex.org/W2051237969, https://openalex.org/W2798853277, https://openalex.org/W1995360097, https://openalex.org/W1571164133, https://openalex.org/W2087298647, https://openalex.org/W2469581795, https://openalex.org/W2011973215, https://openalex.org/W2231009150, https://openalex.org/W2795314247, https://openalex.org/W2026425363, https://openalex.org/W2135046866, https://openalex.org/W2157472016, https://openalex.org/W1972815737, https://openalex.org/W2811470308 |
| referenced_works_count | 35 |
| abstract_inverted_index.a | 7, 95, 99, 122, 132, 155 |
| abstract_inverted_index.To | 89, 115 |
| abstract_inverted_index.at | 152 |
| abstract_inverted_index.be | 80, 138 |
| abstract_inverted_index.by | 82 |
| abstract_inverted_index.in | 47, 112, 131 |
| abstract_inverted_index.is | 50 |
| abstract_inverted_index.of | 3, 10, 61, 110 |
| abstract_inverted_index.or | 67, 71 |
| abstract_inverted_index.to | 30, 43, 52, 86, 105, 148, 161 |
| abstract_inverted_index.we | 33, 93, 119 |
| abstract_inverted_index.Our | 135 |
| abstract_inverted_index.and | 76, 98, 150 |
| abstract_inverted_index.any | 142 |
| abstract_inverted_index.are | 6, 28, 64, 73 |
| abstract_inverted_index.but | 22 |
| abstract_inverted_index.can | 24, 40, 78, 137 |
| abstract_inverted_index.for | 128 |
| abstract_inverted_index.has | 158 |
| abstract_inverted_index.not | 74 |
| abstract_inverted_index.out | 117 |
| abstract_inverted_index.the | 53, 59, 108, 159 |
| abstract_inverted_index.Here | 32 |
| abstract_inverted_index.also | 120 |
| abstract_inverted_index.cell | 143 |
| abstract_inverted_index.even | 79 |
| abstract_inverted_index.into | 12 |
| abstract_inverted_index.lead | 42 |
| abstract_inverted_index.show | 34 |
| abstract_inverted_index.that | 27, 35, 102, 125, 157 |
| abstract_inverted_index.this | 91 |
| abstract_inverted_index.time | 37 |
| abstract_inverted_index.tool | 101 |
| abstract_inverted_index.when | 58, 68 |
| abstract_inverted_index.with | 140 |
| abstract_inverted_index.Large | 15 |
| abstract_inverted_index.allow | 103 |
| abstract_inverted_index.alter | 163 |
| abstract_inverted_index.cell. | 55 |
| abstract_inverted_index.cells | 63, 70 |
| abstract_inverted_index.large | 113, 153 |
| abstract_inverted_index.major | 8 |
| abstract_inverted_index.often | 18 |
| abstract_inverted_index.scale | 154 |
| abstract_inverted_index.sizes | 17 |
| abstract_inverted_index.users | 104, 147 |
| abstract_inverted_index.which | 48 |
| abstract_inverted_index.wrong | 54 |
| abstract_inverted_index.arises | 57 |
| abstract_inverted_index.assess | 107 |
| abstract_inverted_index.course | 38 |
| abstract_inverted_index.degree | 109 |
| abstract_inverted_index.design | 121 |
| abstract_inverted_index.entire | 69 |
| abstract_inverted_index.errors | 26 |
| abstract_inverted_index.filter | 116 |
| abstract_inverted_index.handle | 87 |
| abstract_inverted_index.metric | 97 |
| abstract_inverted_index.model. | 134 |
| abstract_inverted_index.neural | 13 |
| abstract_inverted_index.robust | 123 |
| abstract_inverted_index.shapes | 60 |
| abstract_inverted_index.source | 9 |
| abstract_inverted_index.calcium | 4 |
| abstract_inverted_index.correct | 151 |
| abstract_inverted_index.dataset | 16 |
| abstract_inverted_index.detect. | 31 |
| abstract_inverted_index.develop | 94 |
| abstract_inverted_index.errors, | 46 |
| abstract_inverted_index.finding | 144 |
| abstract_inverted_index.insight | 11 |
| abstract_inverted_index.methods | 83, 136 |
| abstract_inverted_index.problem | 156 |
| abstract_inverted_index.quickly | 106 |
| abstract_inverted_index.require | 19 |
| abstract_inverted_index.signals | 130 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.accounts | 127 |
| abstract_inverted_index.activity | 5 |
| abstract_inverted_index.ascribed | 51 |
| abstract_inverted_index.combined | 139 |
| abstract_inverted_index.defined, | 66 |
| abstract_inverted_index.designed | 85 |
| abstract_inverted_index.diagnose | 90, 149 |
| abstract_inverted_index.methods, | 21 |
| abstract_inverted_index.overlap. | 88 |
| abstract_inverted_index.problem, | 92 |
| abstract_inverted_index.produced | 81 |
| abstract_inverted_index.automated | 20 |
| abstract_inverted_index.automatic | 36 |
| abstract_inverted_index.difficult | 29 |
| abstract_inverted_index.estimator | 124 |
| abstract_inverted_index.function. | 14 |
| abstract_inverted_index.introduce | 25 |
| abstract_inverted_index.potential | 160 |
| abstract_inverted_index.processes | 72 |
| abstract_inverted_index.sometimes | 41 |
| abstract_inverted_index.Population | 1 |
| abstract_inverted_index.automation | 23 |
| abstract_inverted_index.empowering | 146 |
| abstract_inverted_index.estimation | 39 |
| abstract_inverted_index.explicitly | 126 |
| abstract_inverted_index.generative | 133 |
| abstract_inverted_index.recordings | 2 |
| abstract_inverted_index.scientific | 164 |
| abstract_inverted_index.technique, | 145 |
| abstract_inverted_index.essentially | 141 |
| abstract_inverted_index.identified, | 75 |
| abstract_inverted_index.imperfectly | 65 |
| abstract_inverted_index.overlapping | 62 |
| abstract_inverted_index.significant | 44 |
| abstract_inverted_index.conclusions. | 165 |
| abstract_inverted_index.fluorescence | 49 |
| abstract_inverted_index.populations. | 114 |
| abstract_inverted_index.specifically | 84 |
| abstract_inverted_index.contaminating | 129 |
| abstract_inverted_index.significantly | 162 |
| abstract_inverted_index.visualization | 100 |
| abstract_inverted_index.Misattribution | 56 |
| abstract_inverted_index.misattribution | 45, 77, 111 |
| abstract_inverted_index.misattribution, | 118 |
| abstract_inverted_index.transient-by-transient | 96 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.77277588 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |