Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio
Nuclear Magnetic Resonance (NMR) spectroscopy has become a powerful method to study cell metabolism in vivo. Low sensitivity of nuclear magnetic resonance (NMR) measurements of living cell composition by conventional methods requires samples with high cell density compared to that in growing culture...
Gespeichert in:
| Veröffentlicht in: | Biotechnology techniques 1989, Vol.3 (1), p.13-18 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 18 |
|---|---|
| container_issue | 1 |
| container_start_page | 13 |
| container_title | Biotechnology techniques |
| container_volume | 3 |
| creator | GALAZZO, J. L BAILEY, J. E |
| description | Nuclear Magnetic Resonance (NMR) spectroscopy has become a powerful method to study cell metabolism in vivo. Low sensitivity of nuclear magnetic resonance (NMR) measurements of living cell composition by conventional methods requires samples with high cell density compared to that in growing cultures. Reasonably accurate intracellular concentration estimates from lower cell density samples can be obtained by treating the time-domain NMR data by linear prediction singular value decomposition (LPSVD) prior to Fourier transformation. Alternatively, application of LPSVD enables intracellular concentrations estimates in less NMR acquisition time, improving time resolution in NMR measurements of intracellular transients. |
| doi_str_mv | 10.1007/BF01876214 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pasca</sourceid><recordid>TN_cdi_proquest_miscellaneous_15327856</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>15327856</sourcerecordid><originalsourceid>FETCH-LOGICAL-p130t-226608db27a5ddcdb85541421079f654df578642453b120ff8d9ead5e1535ba43</originalsourceid><addsrcrecordid>eNotkE1LAzEYhIMoWKsXf0EO4m01yeZrj1WsClVBFLwt2XzUSJqsm90WwR_vtvb0wrwPM8MAcI7RFUZIXN_MEZaCE0wPwAQzURZcSHoIJqhiuCBIfhyDk5y_EEIlQnQCfmdtG7xWvU8RJgeDj1Z1sO2s8XonZh-XQxi1tQqDhcbqtGpT9runS1s2aZu3GPQRrv06weenV2hUr-DG958wpM3osowqFH0qYvLZwm6beAqOnArZnu3vFLzP795uH4rFy_3j7WxRtLhEfUEI50iahgjFjNGmkYxRTAlGonKcUeOYkJwSysoGE-ScNJVVhlnMStYoWk7B5b_vWPV7sLmvVz5rG4KKNg25HjkiJOMjeLEHVdYquE5F7XPddn6lup-as0rScdQ_U8tuhA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>15327856</pqid></control><display><type>article</type><title>Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio</title><source>SpringerLink Journals - AutoHoldings</source><creator>GALAZZO, J. L ; BAILEY, J. E</creator><creatorcontrib>GALAZZO, J. L ; BAILEY, J. E</creatorcontrib><description>Nuclear Magnetic Resonance (NMR) spectroscopy has become a powerful method to study cell metabolism in vivo. Low sensitivity of nuclear magnetic resonance (NMR) measurements of living cell composition by conventional methods requires samples with high cell density compared to that in growing cultures. Reasonably accurate intracellular concentration estimates from lower cell density samples can be obtained by treating the time-domain NMR data by linear prediction singular value decomposition (LPSVD) prior to Fourier transformation. Alternatively, application of LPSVD enables intracellular concentrations estimates in less NMR acquisition time, improving time resolution in NMR measurements of intracellular transients.</description><identifier>ISSN: 0951-208X</identifier><identifier>EISSN: 1573-6784</identifier><identifier>DOI: 10.1007/BF01876214</identifier><identifier>CODEN: BTECE6</identifier><language>eng</language><publisher>London: Chapman and Hall</publisher><subject>Biological and medical sciences ; Biotechnology ; cell density ; Fourier analysis ; Fundamental and applied biological sciences. Psychology ; Methods. Procedures. Technologies ; Others ; Various methods and equipments</subject><ispartof>Biotechnology techniques, 1989, Vol.3 (1), p.13-18</ispartof><rights>1990 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,4010,27900,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=6598457$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>GALAZZO, J. L</creatorcontrib><creatorcontrib>BAILEY, J. E</creatorcontrib><title>Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio</title><title>Biotechnology techniques</title><description>Nuclear Magnetic Resonance (NMR) spectroscopy has become a powerful method to study cell metabolism in vivo. Low sensitivity of nuclear magnetic resonance (NMR) measurements of living cell composition by conventional methods requires samples with high cell density compared to that in growing cultures. Reasonably accurate intracellular concentration estimates from lower cell density samples can be obtained by treating the time-domain NMR data by linear prediction singular value decomposition (LPSVD) prior to Fourier transformation. Alternatively, application of LPSVD enables intracellular concentrations estimates in less NMR acquisition time, improving time resolution in NMR measurements of intracellular transients.</description><subject>Biological and medical sciences</subject><subject>Biotechnology</subject><subject>cell density</subject><subject>Fourier analysis</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Methods. Procedures. Technologies</subject><subject>Others</subject><subject>Various methods and equipments</subject><issn>0951-208X</issn><issn>1573-6784</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1989</creationdate><recordtype>article</recordtype><recordid>eNotkE1LAzEYhIMoWKsXf0EO4m01yeZrj1WsClVBFLwt2XzUSJqsm90WwR_vtvb0wrwPM8MAcI7RFUZIXN_MEZaCE0wPwAQzURZcSHoIJqhiuCBIfhyDk5y_EEIlQnQCfmdtG7xWvU8RJgeDj1Z1sO2s8XonZh-XQxi1tQqDhcbqtGpT9runS1s2aZu3GPQRrv06weenV2hUr-DG958wpM3osowqFH0qYvLZwm6beAqOnArZnu3vFLzP795uH4rFy_3j7WxRtLhEfUEI50iahgjFjNGmkYxRTAlGonKcUeOYkJwSysoGE-ScNJVVhlnMStYoWk7B5b_vWPV7sLmvVz5rG4KKNg25HjkiJOMjeLEHVdYquE5F7XPddn6lup-as0rScdQ_U8tuhA</recordid><startdate>1989</startdate><enddate>1989</enddate><creator>GALAZZO, J. L</creator><creator>BAILEY, J. E</creator><general>Chapman and Hall</general><scope>IQODW</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>1989</creationdate><title>Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio</title><author>GALAZZO, J. L ; BAILEY, J. E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p130t-226608db27a5ddcdb85541421079f654df578642453b120ff8d9ead5e1535ba43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Biological and medical sciences</topic><topic>Biotechnology</topic><topic>cell density</topic><topic>Fourier analysis</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Methods. Procedures. Technologies</topic><topic>Others</topic><topic>Various methods and equipments</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>GALAZZO, J. L</creatorcontrib><creatorcontrib>BAILEY, J. E</creatorcontrib><collection>Pascal-Francis</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Biotechnology techniques</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>GALAZZO, J. L</au><au>BAILEY, J. E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio</atitle><jtitle>Biotechnology techniques</jtitle><date>1989</date><risdate>1989</risdate><volume>3</volume><issue>1</issue><spage>13</spage><epage>18</epage><pages>13-18</pages><issn>0951-208X</issn><eissn>1573-6784</eissn><coden>BTECE6</coden><abstract>Nuclear Magnetic Resonance (NMR) spectroscopy has become a powerful method to study cell metabolism in vivo. Low sensitivity of nuclear magnetic resonance (NMR) measurements of living cell composition by conventional methods requires samples with high cell density compared to that in growing cultures. Reasonably accurate intracellular concentration estimates from lower cell density samples can be obtained by treating the time-domain NMR data by linear prediction singular value decomposition (LPSVD) prior to Fourier transformation. Alternatively, application of LPSVD enables intracellular concentrations estimates in less NMR acquisition time, improving time resolution in NMR measurements of intracellular transients.</abstract><cop>London</cop><pub>Chapman and Hall</pub><doi>10.1007/BF01876214</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0951-208X |
| ispartof | Biotechnology techniques, 1989, Vol.3 (1), p.13-18 |
| issn | 0951-208X 1573-6784 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_15327856 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Biological and medical sciences Biotechnology cell density Fourier analysis Fundamental and applied biological sciences. Psychology Methods. Procedures. Technologies Others Various methods and equipments |
| title | Application of linear prediction singular value decomposition for processing in vivo NMR data with low signal-to-noise ratio |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T09%3A52%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pasca&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Application%20of%20linear%20prediction%20singular%20value%20decomposition%20for%20processing%20in%20vivo%20NMR%20data%20with%20low%20signal-to-noise%20ratio&rft.jtitle=Biotechnology%20techniques&rft.au=GALAZZO,%20J.%20L&rft.date=1989&rft.volume=3&rft.issue=1&rft.spage=13&rft.epage=18&rft.pages=13-18&rft.issn=0951-208X&rft.eissn=1573-6784&rft.coden=BTECE6&rft_id=info:doi/10.1007/BF01876214&rft_dat=%3Cproquest_pasca%3E15327856%3C/proquest_pasca%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=15327856&rft_id=info:pmid/&rfr_iscdi=true |