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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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Proteomics01:33

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Mass Analyzers: Overview01:13

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The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
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Genome Annotation and Assembly03:36

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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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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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Updated: Dec 30, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.

Charles Blatti1, Amin Emad1,2, Matthew J Berry3

  • 1Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.

Plos Biology
|January 24, 2020
PubMed
Summary
This summary is machine-generated.

Knowledge Engine for Genomics (KnowEnG) is a free computational system that accelerates biomedical discovery using knowledge-guided data mining. It offers advanced bioinformatics tools, adhering to FAIR principles for broad accessibility and interoperability.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Genomics data analysis requires sophisticated computational tools.
  • Integrating prior biological knowledge with raw data can enhance discovery.
  • Existing tools may lack accessibility or interoperability.

Purpose of the Study:

  • To introduce Knowledge Engine for Genomics (KnowEnG), a novel computational system.
  • To provide accessible and advanced tools for genomics data analysis.
  • To accelerate biomedical discovery through knowledge-guided data mining.

Main Methods:

  • Development of a "Knowledge Network" integrating prior gene information from multiple databases.
  • Implementation of knowledge-guided data mining and machine learning algorithms.
  • Adherence to FAIR principles for findability, accessibility, interoperability, and reusability.
  • Cloud-based execution for scalability and cost-effectiveness.
  • Provision of multiple access modes, including a web portal with visualization tools.

Main Results:

  • KnowEnG offers tools for gene prioritization, sample clustering, gene set analysis, and expression signature analysis.
  • The system successfully analyzed cancer datasets, recreating and expanding upon published results.
  • Demonstrated potential for democratizing advanced genomics analysis tools.

Conclusions:

  • KnowEnG provides a powerful, accessible platform for advanced genomics data analysis.
  • The knowledge-guided approach enhances the utility of bioinformatics tools.
  • KnowEnG facilitates broader participation and accelerates discovery in the genomics era.