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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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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
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Agouti: A Lethal Allele
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Human Genetics01:28

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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Missing Links Between Gene Function and Physiology in Genomics.

Julio Collado-Vides1,2,3, Pascale Gaudet4, Víctor de Lorenzo5

  • 1Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.

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|March 17, 2022
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Summary
This summary is machine-generated.

Biological databases and ontologies like Gene Ontology organize molecular knowledge but have limitations. Improving data representation is crucial for understanding organism function and computational comparisons.

Keywords:
challenges and issuesgene functiongene ontologymechanisms and physiologymicrobial annotations

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Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Systems Biology

Background:

  • Biological knowledge is increasingly organized in databases using ontological frameworks.
  • Controlled vocabularies, such as Gene Ontology (GO), are essential for computational comparisons of annotations across diverse organisms.
  • Current ontologies capture gene product functions and participation in biological processes.

Purpose of the Study:

  • To qualitatively highlight limitations in current ontological frameworks for biological annotation.
  • To discuss challenges in bridging the gap between database annotations and understanding organismal organization and function.
  • To provide examples, particularly in bacteria, illustrating these challenges.

Main Methods:

  • Qualitative analysis of existing ontological frameworks.
  • Review of functional annotation classifications (e.g., MultiFun, Gene Ontology).
  • Illustration of challenges with specific examples from bacterial biology.

Main Results:

  • Identified limitations in current ontological frameworks for comprehensive biological annotation.
  • Highlighted the gap between current annotation practices and a deeper understanding of organismal principles.
  • Demonstrated specific challenges using bacterial examples.

Conclusions:

  • Users of Gene Ontology and similar systems should exercise caution during data interpretation.
  • There is a need for improved data representation to better reflect biological complexity.
  • Addressing these limitations will enhance computational biology and our understanding of life's fundamental principles.