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

Yeast Signaling01:28

Yeast Signaling

17.3K
Yeasts are single-celled organisms, but unlike bacteria, they are eukaryotes (cells with a nucleus). Cell signaling in yeast is similar to signaling in other eukaryotic cells. A ligand, such as a protein or a small molecule released from a yeast cell, attaches to a receptor on the cell surface. The binding stimulates second-messenger kinases to activate or inactivate transcription factors that further regulate gene expression. Many of the yeast intracellular signaling cascades have similar...
17.3K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

53.6K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
53.6K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

814
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
814
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.7K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.7K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.1K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.1K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K

You might also read

Related Articles

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

Sort by
Same author

Towards the construction of a virtual yeast.

Nature·2026
Same author

Multi-omic characterization of nasopharyngeal carcinoma delineates the subtype-specific landscape of response to induction chemotherapy.

Nature cancer·2026
Same author

The adaptive molecular landscape of reprogrammed telomeric sequences.

Nature communications·2026
Same author

Insights into cephalochordate genome and gene evolution from the early-diverging amphioxus <i>Asymmetron lucayanum</i>.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The 2025 Westlake Autumn Symposium for Al Proteomics and Virtual Cell.

Genomics, proteomics & bioinformatics·2026
Same author

The Three Waters of Yeast Biology: Education, Research and Impact.

Yeast (Chichester, England)·2026
Same journal

Author Correction: Direct inoculation of bioreactor-controlled stirred suspension culture with cryopreserved human pluripotent stem cells.

Nature protocols·2026
Same journal

High-throughput measurements of protein domain functions using magnetic separation.

Nature protocols·2026
Same journal

Inducing physiological polarity and performing gene editing using CRISPR-Cas9 in human trophoblast organoids.

Nature protocols·2026
Same journal

Photocatalytic low-temperature defluorination of PTFE.

Nature protocols·2026
Same journal

Multimodal imaging and quantification of lanthanide chelate-labeled micro- and nanoplastics in plants.

Nature protocols·2026
Same journal

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

Nature protocols·2026
See all related articles

Related Experiment Video

Updated: Feb 11, 2026

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.5K

Long-read sequencing data analysis for yeasts.

Jia-Xing Yue1, Gianni Liti1

  • 1Université Côte d'Azur, CNRS, INSERM, IRCAN, Nice, France.

Nature Protocols
|May 5, 2018
PubMed
Summary
This summary is machine-generated.

We developed LRSDAY, a novel computational framework for yeast genome analysis. This tool automates long-read sequencing data processing for high-quality genome assembly and annotation.

More Related Videos

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

24.0K
Amplicon Sequencing using the Long-Read Sequencing Technologies
08:57

Amplicon Sequencing using the Long-Read Sequencing Technologies

Published on: August 29, 2025

544

Related Experiment Videos

Last Updated: Feb 11, 2026

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.5K
Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

24.0K
Amplicon Sequencing using the Long-Read Sequencing Technologies
08:57

Amplicon Sequencing using the Long-Read Sequencing Technologies

Published on: August 29, 2025

544

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Long-read sequencing excels at resolving complex genomic regions.
  • Budding yeast (Saccharomyces cerevisiae) is a vital model organism with many ongoing sequencing projects.
  • Analyzing long-read data for high-quality yeast genome assembly and annotation is challenging.

Purpose of the Study:

  • Introduce LRSDAY, a modular computational framework for yeast genome analysis.
  • Provide a one-stop solution for streamlining long-read sequencing data analysis.
  • Enable automated, high-quality genome assembly and annotation with minimal manual intervention.

Main Methods:

  • Developed a modular computational framework named LRSDAY.
  • Designed LRSDAY for automated processing of raw long-read sequencing data.
  • Integrated annotation of key genomic features including centromeres, genes, tRNAs, and transposable elements.

Main Results:

  • LRSDAY produces chromosome-level genome assemblies and comprehensive annotations.
  • Achieved automated genome assembly and annotation with minimal manual intervention.
  • The workflow takes approximately 41 hours for a complete S. cerevisiae genome from PacBio data using four threads.

Conclusions:

  • LRSDAY is the first tool to offer a one-stop solution for yeast long-read genome analysis.
  • The framework is highly modular and adaptable for other eukaryotic organisms.
  • Facilitates efficient and automated generation of high-quality annotated yeast genomes.