Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail all...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Höllt, T [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Rechteinformationen: |
Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Computer graphics forum - Oxford : Blackwell, 1982, 35(2016), 3, Seite 171-180 |
|---|---|
| Übergeordnetes Werk: |
volume:35 ; year:2016 ; number:3 ; pages:171-180 |
| Links: |
|---|
| DOI / URN: |
10.1111/cgf.12893 |
|---|
| Katalog-ID: |
OLC1977962203 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1977962203 | ||
| 003 | DE-627 | ||
| 005 | 20230515122952.0 | ||
| 007 | tu | ||
| 008 | 160719s2016 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1111/cgf.12893 |2 doi | |
| 028 | 5 | 2 | |a PQ20160719 |
| 035 | |a (DE-627)OLC1977962203 | ||
| 035 | |a (DE-599)GBVOLC1977962203 | ||
| 035 | |a (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 | ||
| 035 | |a (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 004 |q DNB |
| 084 | |a 54.00 |2 bkl | ||
| 100 | 1 | |a Höllt, T |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. | ||
| 540 | |a Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. | ||
| 650 | 4 | |a Categories and Subject Descriptors (according to ACM CCS) | |
| 650 | 4 | |a I.3.8 [Computer Graphics]: Applications | |
| 700 | 1 | |a Pezzotti, N |4 oth | |
| 700 | 1 | |a van Unen, V |4 oth | |
| 700 | 1 | |a Koning, F |4 oth | |
| 700 | 1 | |a Eisemann, E |4 oth | |
| 700 | 1 | |a Lelieveldt, B |4 oth | |
| 700 | 1 | |a Vilanova, A |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Computer graphics forum |d Oxford : Blackwell, 1982 |g 35(2016), 3, Seite 171-180 |w (DE-627)129621536 |w (DE-600)246488-3 |w (DE-576)015130568 |x 0167-7055 |7 nnns |
| 773 | 1 | 8 | |g volume:35 |g year:2016 |g number:3 |g pages:171-180 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1111/cgf.12893 |3 Volltext |
| 856 | 4 | 2 | |u http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract |
| 856 | 4 | 2 | |u http://search.proquest.com/docview/1801479089 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-TEC | ||
| 912 | |a SSG-OLC-CHE | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a SSG-OLC-GWK | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a SSG-OLC-DE-84 | ||
| 936 | b | k | |a 54.00 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 35 |j 2016 |e 3 |h 171-180 | ||
| author_variant |
t h th |
|---|---|
| matchkey_str |
article:01677055:2016----::yopoeneatvimnclpeoyigolre |
| hierarchy_sort_str |
2016 |
| bklnumber |
54.00 |
| publishDate |
2016 |
| allfields |
10.1111/cgf.12893 doi PQ20160719 (DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Höllt, T verfasserin aut Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications Pezzotti, N oth van Unen, V oth Koning, F oth Eisemann, E oth Lelieveldt, B oth Vilanova, A oth Enthalten in Computer graphics forum Oxford : Blackwell, 1982 35(2016), 3, Seite 171-180 (DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 0167-7055 nnns volume:35 year:2016 number:3 pages:171-180 http://dx.doi.org/10.1111/cgf.12893 Volltext http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 54.00 AVZ AR 35 2016 3 171-180 |
| spelling |
10.1111/cgf.12893 doi PQ20160719 (DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Höllt, T verfasserin aut Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications Pezzotti, N oth van Unen, V oth Koning, F oth Eisemann, E oth Lelieveldt, B oth Vilanova, A oth Enthalten in Computer graphics forum Oxford : Blackwell, 1982 35(2016), 3, Seite 171-180 (DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 0167-7055 nnns volume:35 year:2016 number:3 pages:171-180 http://dx.doi.org/10.1111/cgf.12893 Volltext http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 54.00 AVZ AR 35 2016 3 171-180 |
| allfields_unstemmed |
10.1111/cgf.12893 doi PQ20160719 (DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Höllt, T verfasserin aut Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications Pezzotti, N oth van Unen, V oth Koning, F oth Eisemann, E oth Lelieveldt, B oth Vilanova, A oth Enthalten in Computer graphics forum Oxford : Blackwell, 1982 35(2016), 3, Seite 171-180 (DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 0167-7055 nnns volume:35 year:2016 number:3 pages:171-180 http://dx.doi.org/10.1111/cgf.12893 Volltext http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 54.00 AVZ AR 35 2016 3 171-180 |
| allfieldsGer |
10.1111/cgf.12893 doi PQ20160719 (DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Höllt, T verfasserin aut Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications Pezzotti, N oth van Unen, V oth Koning, F oth Eisemann, E oth Lelieveldt, B oth Vilanova, A oth Enthalten in Computer graphics forum Oxford : Blackwell, 1982 35(2016), 3, Seite 171-180 (DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 0167-7055 nnns volume:35 year:2016 number:3 pages:171-180 http://dx.doi.org/10.1111/cgf.12893 Volltext http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 54.00 AVZ AR 35 2016 3 171-180 |
| allfieldsSound |
10.1111/cgf.12893 doi PQ20160719 (DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Höllt, T verfasserin aut Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications Pezzotti, N oth van Unen, V oth Koning, F oth Eisemann, E oth Lelieveldt, B oth Vilanova, A oth Enthalten in Computer graphics forum Oxford : Blackwell, 1982 35(2016), 3, Seite 171-180 (DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 0167-7055 nnns volume:35 year:2016 number:3 pages:171-180 http://dx.doi.org/10.1111/cgf.12893 Volltext http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 54.00 AVZ AR 35 2016 3 171-180 |
| language |
English |
| source |
Enthalten in Computer graphics forum 35(2016), 3, Seite 171-180 volume:35 year:2016 number:3 pages:171-180 |
| sourceStr |
Enthalten in Computer graphics forum 35(2016), 3, Seite 171-180 volume:35 year:2016 number:3 pages:171-180 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications |
| dewey-raw |
004 |
| isfreeaccess_bool |
false |
| container_title |
Computer graphics forum |
| authorswithroles_txt_mv |
Höllt, T @@aut@@ Pezzotti, N @@oth@@ van Unen, V @@oth@@ Koning, F @@oth@@ Eisemann, E @@oth@@ Lelieveldt, B @@oth@@ Vilanova, A @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
129621536 |
| dewey-sort |
14 |
| id |
OLC1977962203 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1977962203</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230515122952.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/cgf.12893</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1977962203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1977962203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Höllt, T</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Categories and Subject Descriptors (according to ACM CCS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">I.3.8 [Computer Graphics]: Applications</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pezzotti, N</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Unen, V</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Koning, F</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Eisemann, E</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lelieveldt, B</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vilanova, A</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Computer graphics forum</subfield><subfield code="d">Oxford : Blackwell, 1982</subfield><subfield code="g">35(2016), 3, Seite 171-180</subfield><subfield code="w">(DE-627)129621536</subfield><subfield code="w">(DE-600)246488-3</subfield><subfield code="w">(DE-576)015130568</subfield><subfield code="x">0167-7055</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:35</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:3</subfield><subfield code="g">pages:171-180</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1111/cgf.12893</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1801479089</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-GWK</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.00</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">35</subfield><subfield code="j">2016</subfield><subfield code="e">3</subfield><subfield code="h">171-180</subfield></datafield></record></collection>
|
| author |
Höllt, T |
| spellingShingle |
Höllt, T ddc 004 bkl 54.00 misc Categories and Subject Descriptors (according to ACM CCS) misc I.3.8 [Computer Graphics]: Applications Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| authorStr |
Höllt, T |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)129621536 |
| format |
Article |
| dewey-ones |
004 - Data processing & computer science |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0167-7055 |
| topic_title |
004 DNB 54.00 bkl Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets Categories and Subject Descriptors (according to ACM CCS) I.3.8 [Computer Graphics]: Applications |
| topic |
ddc 004 bkl 54.00 misc Categories and Subject Descriptors (according to ACM CCS) misc I.3.8 [Computer Graphics]: Applications |
| topic_unstemmed |
ddc 004 bkl 54.00 misc Categories and Subject Descriptors (according to ACM CCS) misc I.3.8 [Computer Graphics]: Applications |
| topic_browse |
ddc 004 bkl 54.00 misc Categories and Subject Descriptors (according to ACM CCS) misc I.3.8 [Computer Graphics]: Applications |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
n p np u v v uv uvv f k fk e e ee b l bl a v av |
| hierarchy_parent_title |
Computer graphics forum |
| hierarchy_parent_id |
129621536 |
| dewey-tens |
000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Computer graphics forum |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)129621536 (DE-600)246488-3 (DE-576)015130568 |
| title |
Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| ctrlnum |
(DE-627)OLC1977962203 (DE-599)GBVOLC1977962203 (PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90 (KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge |
| title_full |
Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| author_sort |
Höllt, T |
| journal |
Computer graphics forum |
| journalStr |
Computer graphics forum |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
171 |
| author_browse |
Höllt, T |
| container_volume |
35 |
| class |
004 DNB 54.00 bkl |
| format_se |
Aufsätze |
| author-letter |
Höllt, T |
| doi_str_mv |
10.1111/cgf.12893 |
| dewey-full |
004 |
| title_sort |
cytosplore: interactive immune cell phenotyping for large single‐cell datasets |
| title_auth |
Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| abstract |
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. |
| abstractGer |
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. |
| abstract_unstemmed |
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-GWK SSG-OLC-PHA SSG-OLC-DE-84 |
| container_issue |
3 |
| title_short |
Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets |
| url |
http://dx.doi.org/10.1111/cgf.12893 http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract http://search.proquest.com/docview/1801479089 |
| remote_bool |
false |
| author2 |
Pezzotti, N van Unen, V Koning, F Eisemann, E Lelieveldt, B Vilanova, A |
| author2Str |
Pezzotti, N van Unen, V Koning, F Eisemann, E Lelieveldt, B Vilanova, A |
| ppnlink |
129621536 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth oth oth |
| doi_str |
10.1111/cgf.12893 |
| up_date |
2024-07-03T20:08:00.568Z |
| _version_ |
1803589811512016896 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1977962203</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230515122952.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/cgf.12893</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1977962203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1977962203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1313-61e976528d10d6bcc314eea9f1ba1c0aa9793c67507ddf0c8ac6580145bcdce90</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0120587020160000035000300171cytosploreinteractiveimmunecellphenotypingforlarge</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Höllt, T</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: 2016 The Author(s) Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Categories and Subject Descriptors (according to ACM CCS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">I.3.8 [Computer Graphics]: Applications</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pezzotti, N</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Unen, V</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Koning, F</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Eisemann, E</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lelieveldt, B</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vilanova, A</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Computer graphics forum</subfield><subfield code="d">Oxford : Blackwell, 1982</subfield><subfield code="g">35(2016), 3, Seite 171-180</subfield><subfield code="w">(DE-627)129621536</subfield><subfield code="w">(DE-600)246488-3</subfield><subfield code="w">(DE-576)015130568</subfield><subfield code="x">0167-7055</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:35</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:3</subfield><subfield code="g">pages:171-180</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1111/cgf.12893</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1111/cgf.12893/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1801479089</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-GWK</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.00</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">35</subfield><subfield code="j">2016</subfield><subfield code="e">3</subfield><subfield code="h">171-180</subfield></datafield></record></collection>
|
| score |
7.4010124 |