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

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

11.8K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
11.8K
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

350
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
350
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.6K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.6K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

38.0K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
38.0K
Sequences01:29

Sequences

276
Sequences are fundamental mathematical objects consisting of ordered lists of numbers that follow a specific rule or pattern. Sequences are critical in various mathematical concepts, including calculus, series, and number theory. They can model real-world phenomena such as population growth, financial investments, and physical processes like the diminishing height of a bouncing ball.Each number in a sequence is referred to as a term. Typically, the terms are denoted as a1, a2, a3,…, where...
276
Sanger Sequencing01:57

Sanger Sequencing

774.5K
DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
774.5K

You might also read

Related Articles

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

Sort by
Same author

Modeling interfacial electron transfer using path integral molecular dynamics.

The Journal of chemical physics·2026
Same author

Noninferiority Study Comparing the Efficacy and Safety of a New Hyaluronic Acid (HA) Filler Containing Lidocaine With an Existing HA Filler for the Treatment of Nasolabial Fold Wrinkles: A Randomized, Double-Blind, Split-Face Trial.

Journal of cosmetic dermatology·2025
Same author

Size-Dependent Lattice Symmetry Breaking Determines the Exciton Fine Structure of Perovskite Nanocrystals.

Nano letters·2023
Same author

Direct Observation of Transient Structural Dynamics of Atomically Thin Halide Perovskite Nanowires.

Journal of the American Chemical Society·2023
Same author

Renormalization of excitonic properties by polar phonons.

The Journal of chemical physics·2022
Same author

Nonlocal Screening Dictates the Radiative Lifetimes of Excitations in Lead Halide Perovskites.

Nano letters·2022

Related Experiment Video

Updated: Feb 1, 2026

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

26.4K

BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing data.

Seokjun Soe1, Yoonjae Park2, Heejoon Chae3

  • 1Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.

BMC Bioinformatics
|December 12, 2018
PubMed
Summary
This summary is machine-generated.

Bisulfite sequencing, a key DNA methylation analysis method, faces computational challenges. BiSpark, a new aligner built on Apache Spark, offers efficient, scalable processing for large datasets, improving DNA methylome analysis.

Keywords:
AlignmentApache SparkBisulfite sequencingDNA methylation

More Related Videos

Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study
06:57

Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study

Published on: July 7, 2023

1.6K
A Highly Scalable Approach to Perform Ecological Surveys of Selfing Caenorhabditis Nematodes
09:10

A Highly Scalable Approach to Perform Ecological Surveys of Selfing Caenorhabditis Nematodes

Published on: March 1, 2022

2.9K

Related Experiment Videos

Last Updated: Feb 1, 2026

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

26.4K
Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study
06:57

Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study

Published on: July 7, 2023

1.6K
A Highly Scalable Approach to Perform Ecological Surveys of Selfing Caenorhabditis Nematodes
09:10

A Highly Scalable Approach to Perform Ecological Surveys of Selfing Caenorhabditis Nematodes

Published on: March 1, 2022

2.9K

Area of Science:

  • Genomics and Bioinformatics
  • Epigenetics and DNA Methylation Analysis

Background:

  • Bisulfite sequencing is a high-resolution method for measuring DNA methylation.
  • Processing bisulfite-treated sequencing data is computationally intensive due to nucleotide conversion.
  • A lack of efficient aligners hinders large-scale DNA methylome analyses.

Purpose of the Study:

  • To develop a highly scalable and efficient bisulfite aligner for large-scale DNA methylome analyses.
  • To address the computational bottleneck in processing bisulfite sequencing data.

Main Methods:

  • Developed BiSpark, a bisulfite aligner implemented on the Apache Spark framework.
  • Utilized Apache Spark for memory-optimized, distributed data processing to maximize parallel efficiency.
  • Incorporated load-balancing features to redistribute imbalanced data and minimize delays in distributed environments.

Main Results:

  • BiSpark demonstrates high scalability and efficiency in processing large volumes of bisulfite sequencing data.
  • The aligner achieves maximum data parallel efficiency through its implementation on Apache Spark.
  • BiSpark effectively minimizes delays in large-scale distributed environments by supporting data redistribution.

Conclusions:

  • BiSpark significantly outperforms existing bisulfite sequencing aligners in speed and scalability.
  • The aligner provides highly consistent and comparable mapping results across various dataset sizes and computing nodes.
  • BiSpark enhances the feasibility of large-scale DNA methylome analyses.