HiCat: A Semi-Supervised Approach for Cell Type Annotation | Paper Citation Record

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HiCat: A Semi-Supervised Approach for Cell Type Annotation ezproxy.library.uvic.ca/articles/s41467-021-25725-x

Reference 1

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Unresolved cited work

Reference 2

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Unresolved cited work

Reference 3

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This paper cites Genome Biology20(1), 264 (Dec 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Genome Biology20(1), 264 (Dec 2019)

Reference 4

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This paper cites Nature Immunology 20(2), 163–172 (Feb 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Immunology 20(2), 163–172 (Feb 2019)

Reference 5

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This paper cites https://doi.org/10.21203/rs.3.rs-3219242/v1, https://www.

HiCat: A Semi-Supervised Approach for Cell Type Annotation https://doi.org/10.21203/rs.3.rs-3219242/v1, https://www

Reference 6

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This paper cites Cell Systems3(4), 346–360.e4 (Oct 2016).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Systems3(4), 346–360.e4 (Oct 2016)

Reference 7

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This paper cites iScience 23(3), 100914 (Feb 2020).

HiCat: A Semi-Supervised Approach for Cell Type Annotation iScience 23(3), 100914 (Feb 2020)

Reference 8

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Observation a95dd26a-953f-413b-8eef-ef532d6a890e · outbound

This paper cites Machine Learning 45(1), 5–32 (Oct 2001).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Machine Learning 45(1), 5–32 (Oct 2001)

Reference 9

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This paper cites Frontiers in Immunology13, 885267 (Apr 2022).https://doi.org/10.3389/ fimmu.2022.885267, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9096838/.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Frontiers in Immunology13, 885267 (Apr 2022).https://doi.org/10.3389/ fimmu.2022.885267, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9096838/

Reference 10

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This paper cites Nature Neuroscience20(3), 484–496 (Mar 2017).https://doi.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Neuroscience20(3), 484–496 (Mar 2017).https://doi

Reference 11

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This paper cites In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

HiCat: A Semi-Supervised Approach for Cell Type Annotation In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Reference 12

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This paper cites Nature Machine Intelligence4(2), 116–126 (Feb 2022).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Machine Intelligence4(2), 116–126 (Feb 2022)

Reference 13

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This paper cites IEEE Transactions on Information Theory13(1), 21–27 (Jan 1967).

HiCat: A Semi-Supervised Approach for Cell Type Annotation IEEE Transactions on Information Theory13(1), 21–27 (Jan 1967)

Reference 14

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This paper cites Blood121(24), 4930–4937 (Jun 2013).https://doi.org/10.1182/blood-2013-02-486217, https://doi.org/10.1182/blood-2013-02-486217.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Blood121(24), 4930–4937 (Jun 2013).https://doi.org/10.1182/blood-2013-02-486217, https://doi.org/10.1182/blood-2013-02-486217

Reference 15

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This paper cites Nucleic Acids Research47(16), e95 (Sep 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nucleic Acids Research47(16), e95 (Sep 2019)

Reference 16

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This paper cites Nature Biotechnology38(6), 737–746 (Jun 2020).https: //doi.org/10.1038/s41587-020-0465-8, https://www.nature.com/articles/s41587-020-0465-8, publisher: Nature Publishing Group.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Biotechnology38(6), 737–746 (Jun 2020).https: //doi.org/10.1038/s41587-020-0465-8, https://www.nature.com/articles/s41587-020-0465-8, publisher: Nature Publishing Group

Reference 17

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This paper cites CatBoost: gradient boosting with categorical features support.

HiCat: A Semi-Supervised Approach for Cell Type Annotation CatBoost: gradient boosting with categorical features support

Reference 18

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This paper cites BMC Bioinformatics21(1), 191 (May 2020).

HiCat: A Semi-Supervised Approach for Cell Type Annotation BMC Bioinformatics21(1), 191 (May 2020)

Reference 19

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This paper cites In: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining.

HiCat: A Semi-Supervised Approach for Cell Type Annotation In: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining

Reference 20

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HiCat: A Semi-Supervised Approach for Cell Type Annotation F1000Research 9, 223 (Jul 2020)

Reference 21

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This paper cites Domain-Adversarial Training of Neural Networks.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Domain-Adversarial Training of Neural Networks

Reference 22

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HiCat: A Semi-Supervised Approach for Cell Type Annotation In: Advances in Neural Information Processing Sys- tems

Reference 23

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This paper cites https://doi.

HiCat: A Semi-Supervised Approach for Cell Type Annotation https://doi

Reference 24

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This paper cites Nature Biotechnology 42(2), 293–304 (Feb 2024).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Biotechnology 42(2), 293–304 (Feb 2024)

Reference 25

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This paper cites Bioinformatics35(22), 4688–4695 (Nov 2019).https://doi.org/10.1093/bioinformatics/ btz292, https://doi.org/10.1093/bioinformatics/btz292.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Bioinformatics35(22), 4688–4695 (Nov 2019).https://doi.org/10.1093/bioinformatics/ btz292, https://doi.org/10.1093/bioinformatics/btz292

Reference 26

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Bioinformatics Advances3(1), vbad030 (Jan 2023).https://doi.org/10

Reference 27

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This paper cites Clinical and Translational Medicine12(3), e694 (Mar 2022).https://doi.org/10.1002/ctm2.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Clinical and Translational Medicine12(3), e694 (Mar 2022).https://doi.org/10.1002/ctm2

Reference 28

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This paper cites https://doi.org/10.1101/2020.06.04.132324, https://www.biorxiv.org/content/10.1101/2020.06.

HiCat: A Semi-Supervised Approach for Cell Type Annotation https://doi.org/10.1101/2020.06.04.132324, https://www.biorxiv.org/content/10.1101/2020.06

Reference 29

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Meth- ods 15(5), 359–362 (May 2018).https://doi.org/10.1038/nmeth.4644, https://www.nature.com/articles/ nmeth.4644, number: 5 Publisher: Nature Publishing Group

Reference 30

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Reference 31

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Unresolved cited work

Reference 32

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Genome Research27(2), 208–222 (Feb 2017).https://doi.org/10.1101/gr.212720

Reference 33

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This paper cites PLOS ONE 13(10),e0205499(Oct2018).

HiCat: A Semi-Supervised Approach for Cell Type Annotation PLOS ONE 13(10),e0205499(Oct2018)

Reference 34

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correction dated 2018-11-27. Source: crossref record 10.1371/journal.pone.0208349->10.1371/journal.pone.0205499:correction, observed 2026-07-11T03:08:10.371147+00:00. This notice travels one citation hop only.

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This paper cites Molecular Systems Biology16(6), e9389 (Jun 2020).https://doi.org/10.15252/msb.20199389, https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC7306901/.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Molecular Systems Biology16(6), e9389 (Jun 2020).https://doi.org/10.15252/msb.20199389, https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC7306901/

Reference 35

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This paper cites 2023 IEEE International Conference on Bioinformat- ics and Biomedicine (BIBM) pp.

HiCat: A Semi-Supervised Approach for Cell Type Annotation 2023 IEEE International Conference on Bioinformat- ics and Biomedicine (BIBM) pp

Reference 36

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This paper cites Bioinfor- matics 36(2), 533–538 (Jan 2020).https://doi.org/10.1093/bioinformatics/btz592, https://doi.org/10.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Bioinfor- matics 36(2), 533–538 (Jan 2020).https://doi.org/10.1093/bioinformatics/btz592, https://doi.org/10

Reference 37

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HiCat: A Semi-Supervised Approach for Cell Type Annotation UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 38

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This paper cites Cell Systems 3(4), 385–394.e3 (Oct 2016).https://doi.org/10.1016/j.cels.2016.09.002, https://linkinghub.elsevier.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Systems 3(4), 385–394.e3 (Oct 2016).https://doi.org/10.1016/j.cels.2016.09.002, https://linkinghub.elsevier

Reference 39

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Observation 9ddab2d6-6e6e-461c-88ab-36eebb6cb370 · outbound

This paper cites Computational and Structural Biotechnology Journal19, 961–969 (Jan 2021).https://doi.org/10.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Computational and Structural Biotechnology Journal19, 961–969 (Jan 2021).https://doi.org/10

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:38:18.682169Z

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This paper cites Nature Methods 16(10), 983–986 (Oct 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Methods 16(10), 983–986 (Oct 2019)

Reference 41

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Observation fecb22cd-b03a-403a-bd5a-a5d3454073c2 · outbound

This paper cites Cancer Research 84(5_Supplement_2), A087 (Mar 2024).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cancer Research 84(5_Supplement_2), A087 (Mar 2024)

Reference 42

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.903914Z

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Observation f378bc75-c248-41b9-8c3c-7b809abb51df · outbound

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HiCat: A Semi-Supervised Approach for Cell Type Annotation Unresolved cited work

Reference 43

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This paper cites Cell Metabolism24(4), 593–607 (Oct 2016).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Metabolism24(4), 593–607 (Oct 2016)

Reference 44

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This paper cites Nucleic Acids Research 49(21), e122 (Dec 2021).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nucleic Acids Research 49(21), e122 (Dec 2021)

Reference 45

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.885356Z

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Observation b734525d-014e-42d1-80af-273390b49872 · outbound

This paper cites Cell 177(7), 1888–1902.e21 (Jun 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell 177(7), 1888–1902.e21 (Jun 2019)

Reference 46

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Observation f7bd6f5e-874a-448b-9599-bbb35cdef297 · outbound

This paper cites Nature 562(7727), 367–372 (Oct 2018).https://doi.org/10.1038/s41586-018-0590-4.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature 562(7727), 367–372 (Oct 2018).https://doi.org/10.1038/s41586-018-0590-4

Reference 47

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Observation cd769b24-4f6e-46cd-b793-93077b8d0281 · outbound

This paper cites Cell Systems9(2), 207–213.e2 (Aug 2019).https://doi.org/10.1016/j.cels.2019.06.004, https://www.cell.com/cell-systems/abstract/S2405-4712(19)30199-1, publisher: Elsevier.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Systems9(2), 207–213.e2 (Aug 2019).https://doi.org/10.1016/j.cels.2019.06.004, https://www.cell.com/cell-systems/abstract/S2405-4712(19)30199-1, publisher: Elsevier

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T13:38:17.634357Z

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Observation bf373dfe-58bf-4ae2-bd37-4d9caca21270 · outbound

This paper cites Nature Neuroscience19(2), 335–346 (Feb 2016).https://doi.org/10.1038/nn.4216.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Nature Neuroscience19(2), 335–346 (Feb 2016).https://doi.org/10.1038/nn.4216

Reference 49

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.852913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 52de75cc-786a-4b04-abcf-ddbcba5db084 · outbound

This paper cites Genome Biology21(1), 12 (Jan 2020).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Genome Biology21(1), 12 (Jan 2020)

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T13:38:17.641903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 806ef0f0-227d-49da-8ca7-6a0abe2adc7d · outbound

This paper cites https://doi.org/10.1101/456129, https://www.biorxiv.org/content/10.1101/456129v1, pages: 456129 Section: New Results.

HiCat: A Semi-Supervised Approach for Cell Type Annotation https://doi.org/10.1101/456129, https://www.biorxiv.org/content/10.1101/456129v1, pages: 456129 Section: New Results

Reference 51

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.832360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation df077ff0-eb74-4eb6-ba95-c6f6ae21f752 · outbound

This paper cites Diabetes 65(10), 3028–3038 (Oct 2016).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Diabetes 65(10), 3028–3038 (Oct 2016)

Reference 52

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.820517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a1053c25-df1e-4cbc-81fa-182159474a3a · outbound

This paper cites Bioinformatics 37(Suppl 1), i51–i58 (Jul 2021).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Bioinformatics 37(Suppl 1), i51–i58 (Jul 2021)

Reference 53

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.809594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5102f4d4-2ce4-41f1-95aa-850b48c28520 · outbound

This paper cites HiCat: A Semi-supervised Cell Annotation Pipeline 15 Nucleic Acids Research47(8), e48 (May 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation HiCat: A Semi-supervised Cell Annotation Pipeline 15 Nucleic Acids Research47(8), e48 (May 2019)

Reference 54

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.798097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7c5d406d-3b90-406a-8a7a-a54a24ddc532 · outbound

This paper cites Cell Metabolism24(4), 608–615 (Oct 2016).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Metabolism24(4), 608–615 (Oct 2016)

Reference 55

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.784745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 71088289-6ea3-4270-98c0-ba0a5e5e4b35 · outbound

This paper cites Molecular Systems Biology 17(1), e9620 (Jan 2021).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Molecular Systems Biology 17(1), e9620 (Jan 2021)

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T13:38:17.664347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea133e63-88f1-4a73-ab9e-b258a439ad95 · outbound

This paper cites Bioinformatics38(22), 5042–5048 (Nov 2022).https://doi.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Bioinformatics38(22), 5042–5048 (Nov 2022).https://doi

Reference 57

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.765177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7d13e63c-5d6f-4a1a-846b-f237391272e6 · outbound

This paper cites an unresolved cited work.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Unresolved cited work

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T13:38:17.672434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db7906e0-c26d-4ccd-b652-a067345a6775 · outbound

This paper cites Briefings in Bioinformatics22(3), bbaa097 (Jun 2020).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Briefings in Bioinformatics22(3), bbaa097 (Jun 2020)

Reference 59

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.745481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6d5929c-673d-421f-9a7e-f4abe2a04d71 · outbound

This paper cites Cell Discovery 5(1), 1–4 (Sep 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Cell Discovery 5(1), 1–4 (Sep 2019)

Reference 60

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.733824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 14ed1c5c-9c02-489e-af32-e14431c47a69 · outbound

This paper cites Frontiers in Immunology14, 1189520 (May 2023).https://doi.org/10.3389/fimmu.2023.1189520, https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC10225553/.

HiCat: A Semi-Supervised Approach for Cell Type Annotation Frontiers in Immunology14, 1189520 (May 2023).https://doi.org/10.3389/fimmu.2023.1189520, https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC10225553/

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T13:38:17.683896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdc82f16-34b8-4374-8fc8-674dec4dcfc1 · outbound

This paper cites Genes 10(7), 531 (Jul 2019).

HiCat: A Semi-Supervised Approach for Cell Type Annotation Genes 10(7), 531 (Jul 2019)

Reference 62

Resolution: verified exact; doi, observed 2026-08-12T13:38:17.721697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers