Resultados totales (Incluyendo duplicados): 94
Encontrada(s) 10 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
Dataset. 2022

BRAINGUT_WINEUP DAILY LIFELIKE IMAGES [DATASET]

  • Bartolomé, Begoña
  • Moreno-Arribas, M. Victoria
  • Lloret Iglesias, Lara
  • Aguilar, Fernando
  • Cobo Cano, Miriam
  • García Díaz, Daniel
  • Heredia, Ignacio
  • Yuste, Silvia
  • Pérez-Matute, Patricia
  • Motilva, María-José
The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters. Each file name is unique and contains information of the parameters under which the photograph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Rea_Rio_C_Bor_175_nd_nd_fr10_nd_nd_ar2 corresponds to an almost real image (Rea), taken in La Rioja (Rio), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at none defined time (nd) and undefined lighting (nd), with a real back-ground (fr10) and without reference (nd) nor distance (nd) considerations, and upper angle (ar2)., Peer reviewed

DOI: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
HANDLE: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
PMID: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
Ver en: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
Dataset. 2022

BRAINGUT_WINEUP REAL IMAGES [DATASET]

  • Relaño de la Guía, Edgard
  • Lloret Iglesias, Lara
  • Aguilar, Fernando
  • Cobo Cano, Miriam
  • García Díaz, Daniel
  • Heredia, Ignacio
  • Yuste, Silvia
  • Pérez-Matute, Patricia
  • Motilva, María-José
  • Bartolomé, Begoña
  • Moreno-Arribas, M. Victoria
The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Each file name is unique and contains information of the parameters under which the photo-graph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Vol_Mad_C_Bor_175_Cena_nd_nd_nd_nd_nd corresponds to a real image taken by a consumer(#Vol), taken in Madrid (Mad), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at dinner (Cena) with undefined lighting (nd) and a random real background (nd), and without reference (nd) nor distance (nd), nor angle (nd) considerations., Peer reviewed

DOI: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
HANDLE: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
PMID: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
Ver en: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/308427
Dataset. 2022

FLOWCHART OUTLINING THE PIPELINE FOR SMALL RNASEQ ANALYSIS

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
1 figure, Including the identification of known and putative novel miRNAs, miRNA abundance profiling and differential abundance analysis. rRNA: ribosomal RNA; tRNA: transfer RNA; snoRNA: small nucleolar RNA; snRNA: small nuclear RNA; RE: repeat elements; qPCR: quantitative real-time PCR., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/308427
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/308427
HANDLE: http://hdl.handle.net/10261/308427
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/308427
PMID: http://hdl.handle.net/10261/308427
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/308427
Ver en: http://hdl.handle.net/10261/308427
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/308427

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310598
Dataset. 2022

STACKED BAR PLOT REPORTING THE FRACTION OF SMALL RNASEQ READS ASSIGNED TO THE ANNOTATED FELIS CATUS MIRNAS (FCA-MIRNAS) FROM ENSEMBL V.99 (BLUE), FELINE GENOME (ORANGE) OR THAT WERE NOT MAPPED (RED)

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
1 figure, CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310598
HANDLE: http://hdl.handle.net/10261/310598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310598
PMID: http://hdl.handle.net/10261/310598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310598
Ver en: http://hdl.handle.net/10261/310598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310598

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310603
Dataset. 2022

PRINCIPAL COMPONENT ANALYSIS (PCA) OF SAMPLES PROFILED BY SMALL RNASEQ TECHNIQUE

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
A. PCA of urine samples on the basis of normalized read counts of the known and putative novel miRNAs for the 38 samples initially processed. The red arrows indicate the outlier Control samples (C5, C6 and C7). B. PCA excluding the high outlier samples. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310603
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310603
HANDLE: http://hdl.handle.net/10261/310603
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310603
PMID: http://hdl.handle.net/10261/310603
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310603
Ver en: http://hdl.handle.net/10261/310603
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310603

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310606
Dataset. 2022

DETAILED CHARACTERISTICS OF THE KNOWN AND PUTATIVE NOVEL MIRNAS IN CAT URINE FOR THE 35 SAMPLES BASED ON RNASEQ DATA

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
A. Proportion of samples for which each of the known miRNAs across the different groups were detected. B. Cumulative abundance of the known feline miRNAs. The dots indicate the log10 of the miRNA abundance for each miRNA. miRNAs are sorted in each group in a decreasing order by their miRNA abundance on the x-axis, independently for each group. C. Proportion of samples for which each of the putative novel miRNA candidates across the different groups were detected. D. Cumulative abundance of the putative novel miRNAs. The dots indicate the log10 of the miRNA abundance for each miRNA. miRNAs are sorted in each group in a decreasing order by their miRNA abundance on the x-axis, independently for each group. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310606
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310606
HANDLE: http://hdl.handle.net/10261/310606
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310606
PMID: http://hdl.handle.net/10261/310606
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310606
Ver en: http://hdl.handle.net/10261/310606
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310606

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310610
Dataset. 2022

PRINCIPAL COMPONENT ANALYSIS (PCA) OF URINE SAMPLES (N = 38) ON THE BASIS OF LOG2 NORMALIZED RELATIVE QUANTITIES (RQ) OF PROFILED MIRNAS USING QPCR

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
1 figure., All samples together (all groups), as well as each one of the contrasts considered (Controls vs. PN; Control vs. SB/C; Control vs. UO; Control vs. CKD; PN vs. SB/C; PN vs. UO; PN vs. CKD and PN vs. other Pathologies) are shown. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310610
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310610
HANDLE: http://hdl.handle.net/10261/310610
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310610
PMID: http://hdl.handle.net/10261/310610
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310610
Ver en: http://hdl.handle.net/10261/310610
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310610

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310617
Dataset. 2022

PEARSON CORRELATION ANALYSIS BETWEEN ABUNDANCE PROFILES OF SMALL RNASEQ AND QPCR DATA FROM SELECTED MIRNAS THAT WERE DA (|LOG2FC| ≥ 1.5 FOR QPCR AND ≥ 2 FOR SMALL RNASEQ; Q-VALUE < 0.05) USING BOTH METHODOLOGIES

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
1 figure., CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million, Rq: Relative quantities., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310617
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310617
HANDLE: http://hdl.handle.net/10261/310617
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310617
PMID: http://hdl.handle.net/10261/310617
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310617
Ver en: http://hdl.handle.net/10261/310617
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310617

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310621
Dataset. 2022

BLAND-ALTMAN PLOTS OF ABUNDANCE PROFILES OF SMALL RNASEQ AND QPCR

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
The data presented is from selected miRNAs that were DA (|log2FC| ≥ 1.5 for qPCR and |log2FC| ≥ 2 for small RNAseq; q-value < 0.05) using both methodologies. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million, Rq: Relative quantities., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310621
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310621
HANDLE: http://hdl.handle.net/10261/310621
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310621
PMID: http://hdl.handle.net/10261/310621
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310621
Ver en: http://hdl.handle.net/10261/310621
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310621

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310630
Dataset. 2022

MIRNAS SELECTED FOR QPCR VERIFICATION

  • Gòdia, Marta
  • Brogaard, Louise
  • Mármol-Sánchez, Emilio
  • Langhorn, Rebecca
  • Nordang Kieler, Ida
  • Reezigt, Bert Jan
  • Nielsen, Lise Nikolic
  • Jessen, Lisbeth Rem
  • Cirera, Susanna
1 table., The table includes for each miRNA the arguments for its selection for further validation, the forward and reverse sequence, the miRBase sequence used as template for primer design, if successful miRNA amplification was obtained with qPCR and qPCR amplification efficiency., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310630
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310630
HANDLE: http://hdl.handle.net/10261/310630
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310630
PMID: http://hdl.handle.net/10261/310630
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310630
Ver en: http://hdl.handle.net/10261/310630
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310630

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