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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Synthetic Biology02:55

Synthetic Biology

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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
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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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Gene Duplication and Divergence02:37

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
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Automated gene data integration with Databio.

Robert W Reid1,2, Jacob W Ferrier1, Jeremy J Jay3,4

  • 1Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.

BMC Research Notes
|April 3, 2020
PubMed
Summary
This summary is machine-generated.

Databio automates data analysis and integration for life sciences, simplifying complex -omics data. This tool aids researchers by streamlining data manipulation and linking resources without requiring specialized bioinformatics expertise.

Keywords:
Data integrationKnowledge discoveryWorkflow automation

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Area of Science:

  • Life Sciences Research
  • Translational Medicine
  • -omics Studies

Background:

  • Data analysis and interpretation are major cost factors in -omics studies.
  • Integrating data across multi-disciplinary projects is challenging.
  • Scientists struggle to keep up with research across multiple fields.

Purpose of the Study:

  • To develop a computational tool for automated data parsing and identifier detection.
  • To streamline data manipulation and integration in life sciences.
  • To enable data linkage without specialized bioinformatics knowledge.

Main Methods:

  • Development of the Databio tool (https://datab.io/).
  • Utilizes fast real-time data structures and a large identifier data warehouse (137 million identifiers).
  • Employs automated heuristics for data provenance description.

Main Results:

  • Databio provides a point-and-click interface for data manipulation and integration.
  • Automates common tasks, including identifier detection.
  • Facilitates data linkage and understanding for researchers.

Conclusions:

  • Databio simplifies complex data analysis and integration in life sciences and translational medicine.
  • Reduces the need for specialized bioinformatics training.
  • Enhances data discoverability and linkage for multi-disciplinary research.