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Related Concept Videos

Proteomics01:33

Proteomics

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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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Genomics02:02

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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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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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Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Genomic DNA in Eukaryotes00:58

Genomic DNA in Eukaryotes

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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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Genomic DNA in Prokaryotes00:46

Genomic DNA in Prokaryotes

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The genome of most prokaryotic organisms consists of double-stranded DNA organized into one circular chromosome in a region of cytoplasm called the nucleoid. The chromosome is tightly wound, or supercoiled, for efficient storage. Prokaryotes also contain other circular pieces of DNA called plasmids. These plasmids are smaller than the chromosome and often carry genes that confer adaptive functions, such as antibiotic resistance.
Genomic Diversity in Bacteria
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Managing genomic and proteomic knowledge.

Michael W Lutz1, Patrick V Warren1, Rob W Gill1

  • 1Bioinformatics Division, GlaxoSmithKline Pharmaceuticals, 709 Swedeland Road, P.O. Box 1539, King of Prussia, PA 19406, USA.

Drug Discovery Today. Technologies
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Summary
This summary is machine-generated.

Genomic and proteomic data are vital for understanding diseases and discovering new drugs. This review covers managing, analyzing, and integrating these

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Area of Science:

  • Bioinformatics and Computational Biology
  • Genomics and Proteomics
  • Drug Discovery and Development

Background:

  • 'Omic' data from genomic and proteomic platforms are essential for advancing disease understanding and systems biology.
  • Effective utilization of this data is critical for modern drug discovery pipelines.

Purpose of the Study:

  • To review the essential prerequisites for managing 'omic' data.
  • To outline methods for analyzing 'omic' data and translating it into actionable drug discovery insights.
  • To discuss key challenges and strategies for integrating 'omic' data with chemical, genetic, and clinical information.

Main Methods:

  • Literature review focusing on data management, analysis, and integration strategies for 'omic' datasets.
  • Synthesis of current best practices in bioinformatics and computational approaches for 'omic' data.
  • Analysis of case studies illustrating the application of integrated 'omic' data in drug discovery.

Main Results:

  • Identified critical data management requirements, including standardization, quality control, and secure storage.
  • Described analytical workflows for transforming raw 'omic' data into biological insights relevant to drug targets.
  • Highlighted the importance of multi-modal data integration for a holistic understanding of disease mechanisms and drug responses.

Conclusions:

  • Robust data management and advanced analytical techniques are fundamental for leveraging 'omic' data in drug discovery.
  • Successful integration of diverse data types (chemical, genetic, clinical) with 'omic' data significantly enhances the efficiency and success rate of drug development.
  • 'Omic' data, when properly managed and integrated, represents a powerful resource for accelerating the discovery of novel therapeutics.