Quantitative Classification of DNA Damages Induced by Submicromolar Cadmium Using Oligonucleotide Chip Coupled with Lesion-Specific Endonuclease Digestion

2011 ◽  
Vol 45 (10) ◽  
pp. 4460-4467 ◽  
Author(s):  
Sukdeb Pal ◽  
Ji Yeon Kim ◽  
Sun Hee Park ◽  
Heung Bin Lim ◽  
Kyeong-Hee Lee ◽  
...  
Keyword(s):  
Dna Damages ◽  
Quantitative Classification ◽  
Oligonucleotide Chip ◽  
Endonuclease Digestion

scholarly journals Machine learning algorithm improved automated droplet classification of ddPCR for detection of BRAF V600E in paraffin-embedded samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gabriel A. Colozza-Gama ◽  
Fabiano Callegari ◽  
Nikola Bešič ◽  
Ana C. de J. Paviza ◽  
Janete M. Cerutti
Keyword(s):  
Machine Learning ◽  
Sanger Sequencing ◽  
Learning Algorithm ◽  
Absolute Quantification ◽  
Braf V600e Mutation ◽  
Braf V600e ◽  
Driver Genes ◽  
Quantitative Classification ◽  
Cancer Driver

AbstractSomatic mutations in cancer driver genes can help diagnosis, prognosis and treatment decisions. Formalin-fixed paraffin-embedded (FFPE) specimen is the main source of DNA for somatic mutation detection. To overcome constraints of DNA isolated from FFPE, we compared pyrosequencing and ddPCR analysis for absolute quantification of BRAF V600E mutation in the DNA extracted from FFPE specimens and compared the results to the qualitative detection information obtained by Sanger Sequencing. Sanger sequencing was able to detect BRAF V600E mutation only when it was present in more than 15% total alleles. Although the sensitivity of ddPCR is higher than that observed for Sanger, it was less consistent than pyrosequencing, likely due to droplet classification bias of FFPE-derived DNA. To address the droplet allocation bias in ddPCR analysis, we have compared different algorithms for automated droplet classification and next correlated these findings with those obtained from pyrosequencing. By examining the addition of non-classifiable droplets (rain) in ddPCR, it was possible to obtain better qualitative classification of droplets and better quantitative classification compared to no rain droplets, when considering pyrosequencing results. Notable, only the Machine learning k-NN algorithm was able to automatically classify the samples, surpassing manual classification based on no-template controls, which shows promise in clinical practice.

Classification of DNA damages on segmented comet assay images using convolutional neural network

2020 ◽  
Vol 186 ◽  
pp. 105192 ◽  
Author(s):  
Ümit Atila ◽  
Yusuf Yargı Baydilli ◽  
Eftal Sehirli ◽  
Muhammed Kamil Turan
Keyword(s):  
Neural Network ◽  
Comet Assay ◽  
Convolutional Neural Network ◽  
Dna Damages

Quantitative classification of near-fault ground motions selected by energy indicators

Structures ◽  
2022 ◽  
Vol 35 ◽  
pp. 780-791
Author(s):  
Dahai Zhao ◽  
Huiwei Wang ◽  
Ding Wang ◽  
Ruiguang Zhu ◽  
Jinghui Zhang
Keyword(s):  
Ground Motions ◽  
Quantitative Classification ◽  
Near Fault ◽  
Energy Indicators

scholarly journals A STUDY ON THE QUALITY OF VARIOUS TYPES OF CHEESE PRODUCED AND CONSUMED IN GREECE

1974 ◽  
Vol 25 (1) ◽  
pp. 25
Author(s):  
Κ. ΣΚΟΥΝΤΖΟΣ ◽  
Ι. ΑΣΙΚΗΣ
Keyword(s):  
Sodium Chloride ◽  
Protein Content ◽  
Fat Content ◽  
Market Area ◽  
Laboratory Examination ◽  
Quantitative Classification ◽  
Quantitative Characteristics

Laboratory examination of 828 samples of four typss of Greek cheese («telemes» : 415, «kasseri» : 164, «kefalotyrion» : 170, «gruyère» : 79) obtained from the Attikan market area, revealed, that : a. There is great variation relative to the water as well as the fat contents of the various types of cheese, resulting in the lack of standardized organoleptic and quantitative characteristics in the types of cheeses sold. b. The «kefalotyrion» cheese in particular contains significantly high quantities of sodium chloride. The authors suggest that ins criterion of fat content established so far for the quantitative classification of Greek cheese types be replaced by the criterion of protein content.

scholarly journals Köppenova podjela klima i hrvatsko nazivlje

Geoadria ◽  
2017 ◽  
Vol 8 (1) ◽  
pp. 17 ◽  
Author(s):  
Tomislav Šegota ◽  
Anita Filipčić
Keyword(s):  
Systematic Review ◽  
Quantitative Classification ◽  
The World ◽  
Climatic Classification

In this didactic article a systematic review of Köppen's climatic classification is given. The aim is to accept this most rational and quantitative classification of climates widely accepted all over the world. Like in all other languages the present Croatian terminology is confused. This is the reason why we accepted the original Köppen's terms. 

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