-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Beijing, November 15, 2021/PRNewswire/ - Today, Genetron Health (Nasdaq: GTH) announced the publication of the "Briefings in Bioinformatics" (Briefings in Bioinformatics) published a new variant recognition algorithm UVC (Unity-of-opposites small Variant Caller, unity of opposition variant recognition), and the results of using this algorithm to significantly improve the performance of variant recognition
Accurate detection of somatic variants is essential for cancer diagnosis, prognosis and treatment monitoring
The paper published by Genetron Health describes the performance superiority of UVC compared with other mutation recognition algorithms with similar functions, and uses the following data set for performance evaluation: GIAB germ cell mutation real data set, 192 computer mixed simulation simulations Tumor samples (simulating the depth/purity of different tumors/controls), GIAB somatic mutation real data set, and SEQC2 system mutation reference data set constructed with HCC1395 breast cancer cell line
The main findings of this paper [1] include:
Researchers used extreme analysis methods to build statistical models and discovered new principles to improve the mutation identification process
Genetron Biosciences co-founder and CEO Wang Sizhen said: "I am very pleased that our bioinformatics team has made innovative breakthroughs in the field of mutation identification algorithms, which enable Genetron Biosciences detection products to have higher sensitivity and accuracy
About Panshengzi
Generic Health (Nasdaq: GTH) is a global cutting-edge cancer precision medicine company, focusing on cancer genomics research and application, and is committed to changing the way of cancer diagnosis and treatment relying on advanced molecular biology and big data analysis capabilities
Reference materials:
[1] Xiaofei Zhao, Allison C Hu, Sizhen Wang, Xiaoyue Wang, Calling small variants using universality with Bayes-factor-adjusted odds ratios, Briefings in Bioinformatics, 2021
Safe Harbor Statement
This press release contains Genetron Health's future expectations, plans and forward-looking statements, which are subject to corresponding risks and uncertainties, which may cause actual results to differ from the expectations described in the forward-looking statements
Source: Genetron Health