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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Storage01:23

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
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ATP Energy Storage and Release01:31

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ATP is a highly unstable molecule. Unless quickly used to perform work, ATP spontaneously dissociates into ADP and inorganic phosphate (Pi), and the free energy released during this process is lost as heat. The energy released by ATP hydrolysis is used to perform work inside the cell and depends on a strategy called energy coupling. Cells couple the exergonic reaction of ATP hydrolysis with endergonic reactions, allowing them to proceed.
One example of energy coupling using ATP involves a...
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Sugars as Energy Storage Molecules01:10

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Sugar (a simple carbohydrate) metabolism (chemical reactions) is a classic example of the many cellular processes that use and produce energy. Living things consume sugar as a major energy source because sugar molecules have considerable energy stored within their bonds. Consumed carbohydrates have their origins in photosynthesizing organisms like plants. During photosynthesis, plants use the energy of sunlight to convert carbon dioxide gas into sugar molecules, like glucose. Because this...
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Fats as Energy Storage Molecules01:06

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Triglycerides are a form of long-term energy storage molecules. They are made of glycerol and three fatty acids. To obtain energy from fat, triglycerides must first be broken down by hydrolysis into their two principal components, fatty acids and glycerol. This process, called lipolysis, takes place in the cytoplasm. The resulting fatty acids are oxidized by β-oxidation into acetyl-CoA, which is used by the Krebs cycle. The glycerol that is released from triglycerides after lipolysis...
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Quasi-light Storage for Optical Data Packets
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Storage, visualization, and navigation of 3D genomics data.

Jérôme Waldispühl1, Eric Zhang1, Alexander Butyaev1

  • 1School of Computer Science, McGill University, Montréal, Canada.

Methods (San Diego, Calif.)
|May 25, 2018
PubMed
Summary
This summary is machine-generated.

3D genomics generates vast data, exceeding current technology. This review explores advanced computing and platform solutions for managing complex genomic data.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • The field of 3D genomics has experienced rapid growth over the past decade.
  • Increasing volumes and complexity of 2D and 3D genomic data challenge existing sequence distribution technologies.

Purpose of the Study:

  • To review the current state-of-the-art computing technologies relevant to 3D genomics.
  • To examine solutions adopted by existing platforms for handling large-scale genomic data.

Main Methods:

  • Literature review of recent advancements in computing technology.
  • Analysis of current platforms and their data handling capabilities in 3D genomics.

Main Results:

  • Identification of key technological advancements in computing for genomics.
  • Evaluation of existing platform solutions for managing complex 3D genomic datasets.

Conclusions:

  • Emerging technologies offer new opportunities for innovative approaches in 3D genomics.
  • The review highlights the need for scalable and efficient computing solutions to support the growing demands of 3D genomics research.