scholarly journals mQC: A Heuristic Quality-Control Metric for High-Throughput Drug Combination Screening

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Lu Chen ◽  
Kelli Wilson ◽  
Ian Goldlust ◽  
Bryan T. Mott ◽  
Richard Eastman ◽  
...  
Keyword(s):  
Quality Control ◽  
High Throughput ◽  
Drug Combination ◽  
Control Metric

scholarly journals Fast and Efficient 5′P Degradome Library Preparation for Analysis of Co-Translational Decay in Arabidopsis

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 466
Author(s):  
Marie-Christine Carpentier ◽  
Cécile Bousquet-Antonelli ◽  
Rémy Merret
Keyword(s):  
Gene Expression ◽  
Quality Control ◽  
Transcriptional Regulation ◽  
High Throughput ◽  
Library Preparation ◽  
Working Day ◽  
Set Up ◽  
Post Transcriptional Regulation ◽  
Commercial Kit

The recent development of high-throughput technologies based on RNA sequencing has allowed a better description of the role of post-transcriptional regulation in gene expression. In particular, the development of degradome approaches based on the capture of 5′monophosphate decay intermediates allows the discovery of a new decay pathway called co-translational mRNA decay. Thanks to these approaches, ribosome dynamics could now be revealed by analysis of 5′P reads accumulation. However, library preparation could be difficult to set-up for non-specialists. Here, we present a fast and efficient 5′P degradome library preparation for Arabidopsis samples. Our protocol was designed without commercial kit and gel purification and can be easily done in one working day. We demonstrated the robustness and the reproducibility of our protocol. Finally, we present the bioinformatic reads-outs necessary to assess library quality control.

MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS

2015 ◽  
Vol 14 (12) ◽  
pp. 5088-5098 ◽  
Author(s):  
Bas C. Jansen ◽  
Karli R. Reiding ◽  
Albert Bondt ◽  
Agnes L. Hipgrave Ederveen ◽  
Magnus Palmblad ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Processing ◽  
High Throughput ◽  
Maldi Ms ◽  
Relative Quantitation ◽  
Data Processing Tool

scholarly journals DNA-Based Herbal Teas’ Authentication: An ITS2 and psbA-trnH Multi-Marker DNA Metabarcoding Approach

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2120
Author(s):  
Jessica Frigerio ◽  
Giulia Agostinetto ◽  
Valerio Mezzasalma ◽  
Fabrizio De De Mattia ◽  
Massimo Labra ◽  
...  
Keyword(s):  
Quality Control ◽  
Quantitative Analysis ◽  
Medicinal Plants ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
The Other ◽  
Plant Component ◽  
Identification Rate ◽  
Dna Metabarcoding ◽  
Therapeutic Properties

Medicinal plants have been widely used in traditional medicine due to their therapeutic properties. Although they are mostly used as herbal infusion and tincture, employment as ingredients of food supplements is increasing. However, fraud and adulteration are widespread issues. In our study, we aimed at evaluating DNA metabarcoding as a tool to identify product composition. In order to accomplish this, we analyzed fifteen commercial products with DNA metabarcoding, using two barcode regions: psbA-trnH and ITS2. Results showed that on average, 70% (44–100) of the declared ingredients have been identified. The ITS2 marker appears to identify more species (n = 60) than psbA-trnH (n = 35), with an ingredients’ identification rate of 52% versus 45%, respectively. Some species are identified only by one marker rather than the other. Additionally, in order to evaluate the quantitative ability of high-throughput sequencing (HTS) to compare the plant component to the corresponding assigned sequences, in the laboratory, we created six mock mixtures of plants starting both from biomass and gDNA. Our analysis also supports the application of DNA metabarcoding for a relative quantitative analysis. These results move towards the application of HTS analysis for studying the composition of herbal teas for medicinal plants’ traceability and quality control.

GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists

2020 ◽  
pp. 580-592
Author(s):  
Libi Hertzberg ◽  
Assif Yitzhaky ◽  
Metsada Pasmanik-Chor
Keyword(s):  
Gene Expression ◽  
Quality Control ◽  
User Interface ◽  
High Throughput ◽  
Graphical User Interface ◽  
Differential Expression Analysis ◽  
Biological Data ◽  
Expression Data ◽  
Batch Correction ◽  
User Friendly

This article describes how the last decade has been characterized by the production of huge amounts of different types of biological data. Following that, a flood of bioinformatics tools have been published. However, many of these tools are commercial, or require computational skills. In addition, not all tools provide intuitive and highly accessible visualization of the results. The authors have developed GEView (Gene Expression View), which is a free, user-friendly tool harboring several existing algorithms and statistical methods for the analysis of high-throughput gene, microRNA or protein expression data. It can be used to perform basic analysis such as quality control, outlier detection, batch correction and differential expression analysis, through a single intuitive graphical user interface. GEView is unique in its simplicity and highly accessible visualization it provides. Together with its basic and intuitive functionality it allows Bio-Medical scientists with no computational skills to independently analyze and visualize high-throughput data produced in their own labs.

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