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Related Concept Videos

Genomics02:02

Genomics

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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Genome-wide Association Studies-GWAS

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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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Conservation of Protein Domains02:26

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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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...

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Related Experiment Video

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
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A domain-centric solution to functional genomics via dcGO Predictor.

Hai Fang1, Julian Gough

  • 1Department of Computer Science, University of Bristol, The Merchant Venturers Building, Bristol BS8 1UB, UK. hfang@cs.bris.ac.uk

BMC Bioinformatics
|March 22, 2013
PubMed
Summary

We developed a domain-centric Gene Ontology (dcGO) framework to predict protein functions. This approach enhances genome annotation by analyzing protein domains and supra-domains for functional insights.

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Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

Published on: October 3, 2018

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Protein function annotation is crucial for understanding newly sequenced genomes.
  • Protein domains are fundamental units of structure, evolution, and function.
  • Supra-domains, combinations of adjacent domains, play roles in functional diversification.

Purpose of the Study:

  • To develop a domain-centric Gene Ontology (dcGO) framework for inferring ontological terms associated with protein domains and supra-domains.
  • To create a predictor tool for functional annotation of protein sequences based on domain information.
  • To validate the method using data from the Critical Assessment of Function Annotation (CAFA) and demonstrate its utility in functional genomics.

Main Methods:

  • Generalizing a framework to automatically infer Gene Ontology (GO) terms from full-length sequence annotations.
  • Applying the framework to UniProtKB-GOA annotations to generate GO term associations with SCOP domains and supra-domains.
  • Utilizing CAFA sequence annotations for method validation and community assessment.

Main Results:

  • The 'dcGO Predictor' was developed, enabling functional annotation of protein sequences.
  • Validation using CAFA data demonstrated the method's effectiveness.
  • Application to completely sequenced genomes showed potential for functional insights via domain-centric GO enrichment analysis.

Conclusions:

  • Domains provide a valuable perspective for function prediction, applicable to both single-domain and multi-domain proteins.
  • The 'dcGO Predictor' shows significant promise for advancing domain-centric functional understanding of genomes in the era of next-generation sequencing.