Statistical Analysis in Proteomics:
This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adap...
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2016
|
| Ausgabe: | 1st ed. 2016 |
| Schriftenreihe: | Methods in Molecular Biology
1362 |
| Schlagworte: | |
| Online-Zugang: | UBR01 TUM01 URL des Erstveröffentlichers |
| Zusammenfassung: | This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory. Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data |
| Beschreibung: | 1 Online-Ressource (X, 313 p. 85 illus., 58 illus. in color) |
| ISBN: | 9781493931064 |
| DOI: | 10.1007/978-1-4939-3106-4 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV044951429 | ||
| 003 | DE-604 | ||
| 005 | 20181024 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 180517s2016 |||| o||u| ||||||eng d | ||
| 020 | |a 9781493931064 |9 978-1-4939-3106-4 | ||
| 024 | 7 | |a 10.1007/978-1-4939-3106-4 |2 doi | |
| 035 | |a (ZDB-2-PRO)978-1-4939-3106-4 | ||
| 035 | |a (OCoLC)941407888 | ||
| 035 | |a (DE-599)BVBBV044951429 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-355 |a DE-91 | ||
| 082 | 0 | |a 572.60727 |2 23 | |
| 082 | 0 | |a 572.6 |2 23 | |
| 084 | |a WC 4150 |0 (DE-625)148092: |2 rvk | ||
| 084 | |a WC 7000 |0 (DE-625)148142: |2 rvk | ||
| 245 | 1 | 0 | |a Statistical Analysis in Proteomics |c edited by Klaus Jung |
| 250 | |a 1st ed. 2016 | ||
| 264 | 1 | |a New York, NY |b Springer New York |c 2016 | |
| 300 | |a 1 Online-Ressource (X, 313 p. 85 illus., 58 illus. in color) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Methods in Molecular Biology |v 1362 | |
| 520 | |a This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory. Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data | ||
| 650 | 4 | |a Life Sciences | |
| 650 | 4 | |a Protein Science | |
| 650 | 4 | |a Life sciences | |
| 650 | 4 | |a Proteins | |
| 650 | 0 | 7 | |a Statistik |0 (DE-588)4056995-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Proteomanalyse |0 (DE-588)4596545-6 |2 gnd |9 rswk-swf |
| 655 | 7 | |8 1\p |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Proteomanalyse |0 (DE-588)4596545-6 |D s |
| 689 | 0 | 1 | |a Statistik |0 (DE-588)4056995-0 |D s |
| 689 | 0 | |C b |5 DE-604 | |
| 700 | 1 | |a Jung, Klaus |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781493931057 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4939-3106-4 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-2-PRO | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030344187 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u https://doi.org/10.1007/978-1-4939-3106-4 |l UBR01 |p ZDB-2-PRO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4939-3106-4 |l TUM01 |p ZDB-2-PRO |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804178540023775232 |
|---|---|
| any_adam_object | |
| author2 | Jung, Klaus |
| author2_role | edt |
| author2_variant | k j kj |
| author_facet | Jung, Klaus |
| building | Verbundindex |
| bvnumber | BV044951429 |
| classification_rvk | WC 4150 WC 7000 |
| collection | ZDB-2-PRO |
| ctrlnum | (ZDB-2-PRO)978-1-4939-3106-4 (OCoLC)941407888 (DE-599)BVBBV044951429 |
| dewey-full | 572.60727 572.6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 572 - Biochemistry |
| dewey-raw | 572.60727 572.6 |
| dewey-search | 572.60727 572.6 |
| dewey-sort | 3572.60727 |
| dewey-tens | 570 - Biology |
| discipline | Biologie |
| doi_str_mv | 10.1007/978-1-4939-3106-4 |
| edition | 1st ed. 2016 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03150nmm a2200553zcb4500</leader><controlfield tag="001">BV044951429</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20181024 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">180517s2016 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781493931064</subfield><subfield code="9">978-1-4939-3106-4</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4939-3106-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-PRO)978-1-4939-3106-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)941407888</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV044951429</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-91</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">572.60727</subfield><subfield code="2">23</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">572.6</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">WC 4150</subfield><subfield code="0">(DE-625)148092:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">WC 7000</subfield><subfield code="0">(DE-625)148142:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Statistical Analysis in Proteomics</subfield><subfield code="c">edited by Klaus Jung</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed. 2016</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer New York</subfield><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (X, 313 p. 85 illus., 58 illus. in color)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Methods in Molecular Biology</subfield><subfield code="v">1362</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory. Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Life Sciences</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Protein Science</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Life sciences</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Proteins</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Statistik</subfield><subfield code="0">(DE-588)4056995-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Proteomanalyse</subfield><subfield code="0">(DE-588)4596545-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="8">1\p</subfield><subfield code="0">(DE-588)4143413-4</subfield><subfield code="a">Aufsatzsammlung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Proteomanalyse</subfield><subfield code="0">(DE-588)4596545-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Statistik</subfield><subfield code="0">(DE-588)4056995-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="C">b</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jung, Klaus</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781493931057</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4939-3106-4</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-PRO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030344187</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4939-3106-4</subfield><subfield code="l">UBR01</subfield><subfield code="p">ZDB-2-PRO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4939-3106-4</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-2-PRO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| genre | 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV044951429 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:05:35Z |
| institution | BVB |
| isbn | 9781493931064 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030344187 |
| oclc_num | 941407888 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-91 DE-BY-TUM |
| owner_facet | DE-355 DE-BY-UBR DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (X, 313 p. 85 illus., 58 illus. in color) |
| psigel | ZDB-2-PRO |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Springer New York |
| record_format | marc |
| series2 | Methods in Molecular Biology |
| spelling | Statistical Analysis in Proteomics edited by Klaus Jung 1st ed. 2016 New York, NY Springer New York 2016 1 Online-Ressource (X, 313 p. 85 illus., 58 illus. in color) txt rdacontent c rdamedia cr rdacarrier Methods in Molecular Biology 1362 This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory. Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data Life Sciences Protein Science Life sciences Proteins Statistik (DE-588)4056995-0 gnd rswk-swf Proteomanalyse (DE-588)4596545-6 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Proteomanalyse (DE-588)4596545-6 s Statistik (DE-588)4056995-0 s b DE-604 Jung, Klaus edt Erscheint auch als Druck-Ausgabe 9781493931057 https://doi.org/10.1007/978-1-4939-3106-4 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Statistical Analysis in Proteomics Life Sciences Protein Science Life sciences Proteins Statistik (DE-588)4056995-0 gnd Proteomanalyse (DE-588)4596545-6 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4596545-6 (DE-588)4143413-4 |
| title | Statistical Analysis in Proteomics |
| title_auth | Statistical Analysis in Proteomics |
| title_exact_search | Statistical Analysis in Proteomics |
| title_full | Statistical Analysis in Proteomics edited by Klaus Jung |
| title_fullStr | Statistical Analysis in Proteomics edited by Klaus Jung |
| title_full_unstemmed | Statistical Analysis in Proteomics edited by Klaus Jung |
| title_short | Statistical Analysis in Proteomics |
| title_sort | statistical analysis in proteomics |
| topic | Life Sciences Protein Science Life sciences Proteins Statistik (DE-588)4056995-0 gnd Proteomanalyse (DE-588)4596545-6 gnd |
| topic_facet | Life Sciences Protein Science Life sciences Proteins Statistik Proteomanalyse Aufsatzsammlung |
| url | https://doi.org/10.1007/978-1-4939-3106-4 |
| work_keys_str_mv | AT jungklaus statisticalanalysisinproteomics |