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Related Concept Videos

Convenience Sampling Method00:55

Convenience Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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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.
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How Data are Classified: Categorical Data01:11

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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.
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Phase II Reactions: Methylation Reactions01:17

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Methylation is a phase II biotransformation process involving the attachment of a methyl group to a substrate. Enzymes known as methyltransferases orchestrate this reaction.
The mechanism of methylation unfolds in two stages. The first stage sees a methyltransferase enzyme facilitating the transfer of a methyl group from S-adenosylmethionine (SAM) to the substrate, forming S-adenosylhomocysteine (SAH). The second stage involves further metabolism of SAH into homocysteine, which can be recycled...
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DNA Topoisomerases02:02

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Topoisomerases are enzymes that relax overwound DNA molecules during various cell processes, including DNA replication and transcription. These enzymes regulate positive and negative DNA supercoiling without changing the nucleotide sequence. DNA overwinding in a clockwise direction results in positively supercoiled DNA, whereas underwinding in a counterclockwise direction produces negatively supercoiled DNA.
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DNA Helicases

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DNA unwinding helicase enzymes are a type of motor protein. Motor proteins can translocate along filaments or polymers using energy generated from ATP hydrolysis. Helicases are involved in all the important cellular processes where DNA unwinding is required, such as DNA replication, repair, recombination, and transcription. They are present in all living organisms, but vary in their structure, function, and mechanism of action. For example, in prokaryotes, DnaB helicase binds and translocates...
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Updated: Jan 21, 2026

DamID-seq: Genome-wide Mapping of Protein-DNA Interactions by High Throughput Sequencing of Adenine-methylated DNA Fragments
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PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.

Joshua J Levy1,2, Alexander J Titus1, Lucas A Salas1

  • 1Department of Epidemiology, Geisel School of Medicine at Dartmouth.

Bioinformatics (Oxford, England)
|August 2, 2019
PubMed
Summary
This summary is machine-generated.

PyMethylProcess accelerates methylation array data preprocessing using Python. This scalable, reproducible pipeline enhances machine learning readiness and is easily deployable via Docker and PIP.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Methylation array data analysis requires efficient preprocessing for large-scale studies.
  • Existing pipelines may lack scalability and reproducibility.

Purpose of the Study:

  • To present PyMethylProcess, a highly parallelized Python pipeline for methylation array data preprocessing.
  • To enable rapid setup and deployment for downstream analyses and machine learning.

Main Methods:

  • Development of a scalable and reproducible data preprocessing pipeline using Python.
  • Containerization using Docker and distribution via PIP for easy deployment.

Main Results:

  • PyMethylProcess offers accelerated data preparation for methylation analyses.
  • The pipeline is designed for large-scale, production-ready machine learning.

Conclusions:

  • PyMethylProcess provides a robust and efficient solution for methylation array data preprocessing.
  • Facilitates integration into advanced computational biology workflows.