Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

pre-mRNA Processing02:01

pre-mRNA Processing

57.2K
In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a “cap” to the 5’ end of the growing transcript. In this process, a 5’ phosphate is replaced by modified guanosine that has a methyl group attached to it (7-Methyl...
57.2K
Quality Control01:05

Quality Control

1.2K
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
1.2K
Pre-mRNA Processing: Modification of pre-mRNA Ends01:35

Pre-mRNA Processing: Modification of pre-mRNA Ends

14.0K
In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a cap to the 5' end of the growing transcript. In this process, a 5' phosphate is replaced by modified guanosine that has a methyl group attached (7-methyl guanosine). This 5' cap helps...
14.0K
Chromatin Structure Regulates pre-mRNA Processing02:41

Chromatin Structure Regulates pre-mRNA Processing

8.1K
In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
8.1K
Pre-mRNA Processing: RNA Splicing01:36

Pre-mRNA Processing: RNA Splicing

6.7K
6.7K
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

614
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
614

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

WearAware: A Wearable-Based Early Warning Framework for Out-of-Hospital Cardiac Risk Monitoring.

Studies in health technology and informatics·2026
Same author

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same author

Publisher Correction: Metabolic septic shock sub-phenotypes, stability over time and association with clinical outcome.

Intensive care medicine·2026
Same author

Artificial Intelligence-Based Prediction of Progression from Gestational Diabetes to Type 2 Diabetes.

Studies in health technology and informatics·2026
Same author

Temporal and Behaviour-Aware Multimodal Modelling for Hour-Ahead Hypoglycaemia Prediction During Ramadan Fasting in Type 1 Diabetes.

Sensors (Basel, Switzerland)·2026
Same author

Host, microbial, and environmental drivers of vaginal microbiota composition.

Fertility and sterility·2026

Related Experiment Video

Updated: Jan 21, 2026

Metabolic Profile Analysis of Zebrafish Embryos
05:41

Metabolic Profile Analysis of Zebrafish Embryos

Published on: January 14, 2013

20.5K

The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling

Caroline J Sands1, Arnaud M Wolfer1, Gonçalo D S Correia1

  • 1National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK.

Bioinformatics (Oxford, England)
|July 28, 2019
PubMed
Summary
This summary is machine-generated.

The nPYc-Toolbox offers software for metabolic phenotyping data analysis, including pre-processing and quality control (QC). This tool enhances data consistency for individual studies and enables reliable comparisons across different research projects.

More Related Videos

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

4.2K
Quality-Controlled Sputum Analysis by Flow Cytometry
07:22

Quality-Controlled Sputum Analysis by Flow Cytometry

Published on: August 9, 2021

5.8K

Related Experiment Videos

Last Updated: Jan 21, 2026

Metabolic Profile Analysis of Zebrafish Embryos
05:41

Metabolic Profile Analysis of Zebrafish Embryos

Published on: January 14, 2013

20.5K
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

4.2K
Quality-Controlled Sputum Analysis by Flow Cytometry
07:22

Quality-Controlled Sputum Analysis by Flow Cytometry

Published on: August 9, 2021

5.8K

Area of Science:

  • Metabolomics
  • Bioinformatics
  • Computational Biology

Background:

  • Large-scale metabolic phenotyping studies are growing in prevalence.
  • Systematic pre-processing and quality control (QC) are crucial for analytical data.
  • Inter-study data comparability is essential for robust scientific conclusions.

Purpose of the Study:

  • To introduce the nPYc-Toolbox, a software solution for metabolic phenotyping data.
  • To provide tools for data import, pre-processing, QC, and visualization.
  • To support both interactive and automated data analysis pipelines.

Main Methods:

  • The nPYc-Toolbox is implemented in Python.
  • It offers functionalities for data import, pre-processing, and quality control.
  • Visualization tools are integrated for data exploration.

Main Results:

  • The nPYc-Toolbox facilitates efficient handling of metabolic phenotyping datasets.
  • It enables consistent data pre-processing and QC within and across studies.
  • The software supports interactive analysis and automated pipelines.

Conclusions:

  • The nPYc-Toolbox addresses the need for standardized data handling in metabolic phenotyping.
  • It improves the reliability of statistical analysis and inter-study comparisons.
  • The freely available software promotes reproducible research in metabolomics.