SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Kwon Y) srt2:(2020-2021)"

Sökning: WFRF:(Kwon Y) > (2020-2021)

  • Resultat 1-10 av 26
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Niemi, MEK, et al. (författare)
  • 2021
  • swepub:Mat__t
  •  
2.
  •  
3.
  • 2021
  • swepub:Mat__t
  •  
4.
  • 2021
  • swepub:Mat__t
  •  
5.
  •  
6.
  • Glasbey, JC, et al. (författare)
  • 2021
  • swepub:Mat__t
  •  
7.
  •  
8.
  •  
9.
  • Ramilowski, JA, et al. (författare)
  • Functional annotation of human long noncoding RNAs via molecular phenotyping
  • 2020
  • Ingår i: Genome research. - : Cold Spring Harbor Laboratory. - 1549-5469 .- 1088-9051. ; 30:7, s. 1060-1072
  • Tidskriftsartikel (refereegranskat)abstract
    • Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
  •  
10.
  • Kang, JS, et al. (författare)
  • Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning
  • 2020
  • Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1, s. 20140-
  • Tidskriftsartikel (refereegranskat)abstract
    • Most models for predicting malignant pancreatic intraductal papillary mucinous neoplasms were developed based on logistic regression (LR) analysis. Our study aimed to develop risk prediction models using machine learning (ML) and LR techniques and compare their performances. This was a multinational, multi-institutional, retrospective study. Clinical variables including age, sex, main duct diameter, cyst size, mural nodule, and tumour location were factors considered for model development (MD). After the division into a MD set and a test set (2:1), the best ML and LR models were developed by training with the MD set using a tenfold cross validation. The test area under the receiver operating curves (AUCs) of the two models were calculated using an independent test set. A total of 3,708 patients were included. The stacked ensemble algorithm in the ML model and variable combinations containing all variables in the LR model were the most chosen during 200 repetitions. After 200 repetitions, the mean AUCs of the ML and LR models were comparable (0.725 vs. 0.725). The performances of the ML and LR models were comparable. The LR model was more practical than ML counterpart, because of its convenience in clinical use and simple interpretability.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-10 av 26

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy