Resultados totales (Incluyendo duplicados): 34338
Encontrada(s) 3434 página(s)
CORA.Repositori de Dades de Recerca
doi:10.34810/data426
Dataset. 2022

IDGP

  • Furney, Simon J.
  • Albà Soler, Mar
  • López Bigas, Núria
Database of human genes prioritized for their probability of involvement in dominant or recessive hereditary diseases.

Proyecto: //
DOI: https://doi.org/10.34810/data426
CORA.Repositori de Dades de Recerca
doi:10.34810/data426
HANDLE: https://doi.org/10.34810/data426
CORA.Repositori de Dades de Recerca
doi:10.34810/data426
PMID: https://doi.org/10.34810/data426
CORA.Repositori de Dades de Recerca
doi:10.34810/data426
Ver en: https://doi.org/10.34810/data426
CORA.Repositori de Dades de Recerca
doi:10.34810/data426

CORA.Repositori de Dades de Recerca
doi:10.34810/data427
Dataset. 2022

PERFORMANCE OF LOW-COST MONITORS TO ASSESS HOUSEHOLD AIR POLLUTION [DATASET]

  • Curto Tirado, Ariadna, 1987-
  • Donaire González, David
  • Barrera Gómez, Jose
  • Marshall, Julian D.
  • Nieuwenhuijsen, Mark J.
  • Wellenius, Gregory A.
  • Tonne, Cathryn
Raw data of PM2.5 and CO from an indoor wood-combustion experiment. We evaluated the performance of two low-cost sensors measuring fine particulate matter (PM2.5) (HAPEX Nano, Climate Solutions Consulting, and TZOA-R Model RD02, MyTZOA) and one measuring carbon monoxide (CO) (EL-USB-CO, Lascar Electronics Ltd.) in a real-world wood-combustion experiment. PM2.5 devices were compared against a DustTrak (Model 8534, TSI Inc.) and a BGI pump (BGI4004, BGI Inc.) and the EL-USB-CO data-logger was compared against a Q-Trak (Model 7575, TSI Inc.). Sampling was conducted in a single-family house in Terrassa (Spain) during five non-consecutive days. All devices were co-located 1 meter away from an indoor fireplace and 0.6 meters above the ground. Fire was set once per day with hardwood logs and kept burning for 12 hours including a minimum of 2 hours with an opened window. The data provided is the raw output from all the devices tested for the 5 sampling days aiming interested researchers to play with the data and reproduce our findings.

Proyecto: //
DOI: https://doi.org/10.34810/data427
CORA.Repositori de Dades de Recerca
doi:10.34810/data427
HANDLE: https://doi.org/10.34810/data427
CORA.Repositori de Dades de Recerca
doi:10.34810/data427
PMID: https://doi.org/10.34810/data427
CORA.Repositori de Dades de Recerca
doi:10.34810/data427
Ver en: https://doi.org/10.34810/data427
CORA.Repositori de Dades de Recerca
doi:10.34810/data427

CORA.Repositori de Dades de Recerca
doi:10.34810/data428
Dataset. 2022

QUANTITATIVE PREDICTIONS OF PROTEIN INTERACTIONS WITH LONG NONCODING RNAS

  • Cirillo, Davide
Long noncoding RNAs (lncRNAs, which comprise 68% of the human transcriptome with average length of 1,000 nt) interact with various RNA-binding proteins (RBPs) to mediate cellular functions. Here we introduce Global Score as a tool to predict protein interactions with lncRNAs (http://service.tartaglialab.com/new_submission/globalscore). We used enhanced CLIP (eCLIP) to test the binding of the lncRNA Xist to the RBPs HnrnpK (Global Score of 0.99), Ptbp1 (0.99), Lbr (0.79), HnrnpU (Saf-A) (0.66), Spen (Sharp) (0.59) and negative control Dkc1 (0.01). Global Score prediction correlates with the eCLIP binding profile (Pearson correlation = 0.93). As for the binding sites, Spen and HnrnpK, Ptbp1, and Lbr interact respectively with Xist A, B, and E repeats and adjacent regions, while HnrnpU binds across the whole transcript, and Dkc1 does not interact with Xist.

Proyecto: //
DOI: https://doi.org/10.34810/data428
CORA.Repositori de Dades de Recerca
doi:10.34810/data428
HANDLE: https://doi.org/10.34810/data428
CORA.Repositori de Dades de Recerca
doi:10.34810/data428
PMID: https://doi.org/10.34810/data428
CORA.Repositori de Dades de Recerca
doi:10.34810/data428
Ver en: https://doi.org/10.34810/data428
CORA.Repositori de Dades de Recerca
doi:10.34810/data428

CORA.Repositori de Dades de Recerca
doi:10.34810/data429
Dataset. 2023

INTOGEN - CANCER DRIVERS DATABASE (2014)

  • Rubio Pérez, Carlota
  • Tamborero Noguera, David
  • Schroeder, Michael Philipp, 1986-
  • Antolín Hernández, Albert, 1984-
  • Déu Pons, Jordi
  • Pérez Llamas, Christian, 1976-
  • Mestres i López, Jordi
  • González-Pérez, Abel
  • López Bigas, Núria
This database contains information on the genes identified as drivers in Rubio-Perez and Tamborero et al. (2015). It contains information on driver identification at mutational, CNA and gene fusion level. Additional ancillary information about the role and major clonality of drivers is also included. A table is also provided with the list of datasets used for mutational driver identification.

Proyecto: //
DOI: https://doi.org/10.34810/data429
CORA.Repositori de Dades de Recerca
doi:10.34810/data429
HANDLE: https://doi.org/10.34810/data429
CORA.Repositori de Dades de Recerca
doi:10.34810/data429
PMID: https://doi.org/10.34810/data429
CORA.Repositori de Dades de Recerca
doi:10.34810/data429
Ver en: https://doi.org/10.34810/data429
CORA.Repositori de Dades de Recerca
doi:10.34810/data429

CORA.Repositori de Dades de Recerca
doi:10.34810/data42
Dataset. 2021

SEQUENCE OF MODELS OBTAINED BY BACKWARDS SELECTION FOR ADG OF CALVES FED A MILK REPLACER SUPPLEMENTED WITH DIFFERENT AA

  • Terré, Marta
  • Ortuzar-Fernández, Iban
  • Graffelman, Jan
  • Bassols, Anna
  • Vidal Amigo, Maria
  • Bach, Alex
The effects on growth performance of supplementation of four different AA combinations in a milk replacer (MR, 25.4% CP and 20.3% fat) based on skimmed milk powder and whey protein concentrate were evaluated in 76 Holstein male calves (3 ± 1.7 d old). The 4 MR were: CTRL with no AA supplementation; PG supplying additional 0.3% Pro and 0.1% Gly; FY supplying additional 0.2% Phe and 0.2% Tyr; KMT providing additional 0.62% Lys, 0.22% Met, and 0.61% Thr. All calves were fed the same milk allowance program and were weaned at 56 d of study. Concentrate intake was limited to minimize interference of potential differences in solid feed intake among treatments. Animals were weighed weekly, intakes recorded daily, and blood samples obtained at 2, 5, and 7 wk of study to determine serum urea and plasma AA concentrations. The file presents data of the backwards selection process to assess the model that fitted better ADG with the study variables (performance, intake, plasma AA balances). Data was collected at Torre Marimon IRTA calf facilities (Caldes de Montbui, Spain) during 2017

Proyecto: //
DOI: https://doi.org/10.34810/data42
CORA.Repositori de Dades de Recerca
doi:10.34810/data42
HANDLE: https://doi.org/10.34810/data42
CORA.Repositori de Dades de Recerca
doi:10.34810/data42
PMID: https://doi.org/10.34810/data42
CORA.Repositori de Dades de Recerca
doi:10.34810/data42
Ver en: https://doi.org/10.34810/data42
CORA.Repositori de Dades de Recerca
doi:10.34810/data42

CORA.Repositori de Dades de Recerca
doi:10.34810/data430
Dataset. 2013

INTOGEN - TCGA PAN-CANCER12 HIGH CONFIDENCE DRIVERS

  • Tamborero Noguera, David
  • González-Pérez, Abel
  • Pérez Llamas, Christian, 1976-
  • Déu Pons, Jordi
  • Kandoth, Cyriac
  • Reimand, Jüri
  • Lawrence, Michael S.
  • Getz, Gad
  • Bader, Gary D.
  • Ding, Li
  • López Bigas, Núria
This file lists the High Confidence Drivers identified as part of the pan-cancer12 initiative, published in the paper Comprehensive identification of mutational cancer driver genes across 12 tumor types" Scientific Reports 3:2650, 2013, doi:10.1038/srep02650

Proyecto: //
DOI: https://doi.org/10.34810/data430
CORA.Repositori de Dades de Recerca
doi:10.34810/data430
HANDLE: https://doi.org/10.34810/data430
CORA.Repositori de Dades de Recerca
doi:10.34810/data430
PMID: https://doi.org/10.34810/data430
CORA.Repositori de Dades de Recerca
doi:10.34810/data430
Ver en: https://doi.org/10.34810/data430
CORA.Repositori de Dades de Recerca
doi:10.34810/data430

CORA.Repositori de Dades de Recerca
doi:10.34810/data431
Dataset. 2023

INTOGEN - ARRAYS

  • Gundem, Gunes
  • Pérez Llamas, Christian
  • Jené i Sanz, Alba
  • Kedzierska, Anna
  • Islam, Abul
  • Déu Pons, Jordi
  • Furney, Simon J.
  • López Bigas, Núria
Genes and pathways affected by expression and copy number changes in tumors across projects and cancer types.

Proyecto: //
DOI: https://doi.org/10.34810/data431
CORA.Repositori de Dades de Recerca
doi:10.34810/data431
HANDLE: https://doi.org/10.34810/data431
CORA.Repositori de Dades de Recerca
doi:10.34810/data431
PMID: https://doi.org/10.34810/data431
CORA.Repositori de Dades de Recerca
doi:10.34810/data431
Ver en: https://doi.org/10.34810/data431
CORA.Repositori de Dades de Recerca
doi:10.34810/data431

CORA.Repositori de Dades de Recerca
doi:10.34810/data432
Dataset. 2022

ONCODRIVEMUT

  • Tamborero Noguera, David
  • Rubio Pérez, Carlota
  • Déu Pons, Jordi
  • Schroeder, Michael Philipp, 1986-
  • Vivancos Prellezo, Ana
  • Rovira Guerín, Ana
  • Tusquets, Ignasi
  • Albanell Mestres, Joan
  • Rodon, Jordi
  • Tabernero Cartula, Josep
  • Dienstman, Rodrigo
  • González-Pérez, Abel
  • López Bigas, Núria
Bioinformatics method to identify individual driver mutations.

Proyecto: //
DOI: https://doi.org/10.34810/data432
CORA.Repositori de Dades de Recerca
doi:10.34810/data432
HANDLE: https://doi.org/10.34810/data432
CORA.Repositori de Dades de Recerca
doi:10.34810/data432
PMID: https://doi.org/10.34810/data432
CORA.Repositori de Dades de Recerca
doi:10.34810/data432
Ver en: https://doi.org/10.34810/data432
CORA.Repositori de Dades de Recerca
doi:10.34810/data432

CORA.Repositori de Dades de Recerca
doi:10.34810/data433
Dataset. 2022

INTOGEN - CATALOG OF DRIVER MUTATIONS

  • Tamborero Noguera, David
  • Rubio Pérez, Carlota
  • Déu Pons, Jordi
  • Schroeder, Michael Philipp, 1986-
  • Vivancos Prellezo, Ana
  • Rovira Guerín, Ana
  • Tusquets, Ignasi
  • Albanell Mestres, Joan
  • Tabernero Cartula, Josep
  • Dienstman, Rodrigo
  • González-Pérez, Abel
  • López Bigas, Núria
This database contains the results of the driver analysis performed by the Cancer Genome Interpreter across 6,792 exomes of a pan-cancer cohort of 28 tumor types. Validated oncogenic mutations are identified according to the state-of-the-art clinical and experimental data, whereas the effect of the mutations of unknown significance is predicted by the OncodriveMUT method.

Proyecto: //
DOI: https://doi.org/10.34810/data433
CORA.Repositori de Dades de Recerca
doi:10.34810/data433
HANDLE: https://doi.org/10.34810/data433
CORA.Repositori de Dades de Recerca
doi:10.34810/data433
PMID: https://doi.org/10.34810/data433
CORA.Repositori de Dades de Recerca
doi:10.34810/data433
Ver en: https://doi.org/10.34810/data433
CORA.Repositori de Dades de Recerca
doi:10.34810/data433

CORA.Repositori de Dades de Recerca
doi:10.34810/data435
Dataset. 2013

INTOGEN - CANCER DRIVER DATABASE (2013)

  • González-Pérez, Abel
  • Pérez Llamas, Christian, 1976-
  • Déu Pons, Jordi
  • Tamborero Noguera, David
  • Schroeder, Michael Philipp, 1986-
  • Jené i Sanz, Alba, 1984-
  • Santos, Alberto
  • López Bigas, Núria
Mutations, genes and pathways involved in tumorigenesis across 4,623 cancer genomes/exomes from 13 cancer sites. IntOGen-mutations identifies cancer drivers across tumor types. Nature Methods 10, 2013, doi:10.1038/nmeth.2642

Proyecto: //
DOI: https://doi.org/10.34810/data435
CORA.Repositori de Dades de Recerca
doi:10.34810/data435
HANDLE: https://doi.org/10.34810/data435
CORA.Repositori de Dades de Recerca
doi:10.34810/data435
PMID: https://doi.org/10.34810/data435
CORA.Repositori de Dades de Recerca
doi:10.34810/data435
Ver en: https://doi.org/10.34810/data435
CORA.Repositori de Dades de Recerca
doi:10.34810/data435

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