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Related Concept Videos

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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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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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Trial and Error and Algorithm01:12

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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Genome Size and the Evolution of New Genes03:21

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While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
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Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

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The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
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Genomic Imprinting and Inheritance02:30

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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
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Updated: Feb 10, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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A Secure Alignment Algorithm for Mapping Short Reads to Human Genome.

Yongan Zhao1, Xiaofeng Wang1, Haixu Tang1

  • 1Department of Computer Science, School of Informatics, Computing, and Engineering, Indiana University , Bloomington, Bloomington, Indiana.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 10, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a secure hybrid cloud algorithm for analyzing human genomic data. It enables efficient and private read mapping, crucial for biomedical research, by leveraging public cloud resources securely.

Keywords:
genome privacyprivacy-preserving techniquesread mapping

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Cloud Computing Security

Background:

  • Analyzing massive human genomic data is vital for biomedical research.
  • Privacy concerns hinder outsourcing genomic computations to public/commercial clouds due to donor identifiability.
  • Existing security techniques are too computationally intensive for practical large-scale genomic data analysis.

Purpose of the Study:

  • To present a secure algorithm for read mapping on a hybrid cloud computing model.
  • To enable privacy-preserving analysis of human genomic data in cloud environments.
  • To overcome the limitations of existing security methods for large-scale genomic computations.

Main Methods:

  • Developed a secure algorithm for read mapping using a hybrid cloud model.
  • Delegated most computation to the public cloud, with encryption/decryption on a private cloud.
  • Implemented the algorithm in C++ and Python on a hybrid cloud system utilizing Apache Spark.

Main Results:

  • The algorithm securely performs read mapping, a fundamental task in genomic data analysis.
  • It achieves results comparable to non-secure read mapping algorithms, including accurate read-to-genome alignment.
  • The output is suitable for downstream analyses like genomic variation inference.

Conclusions:

  • The proposed hybrid cloud algorithm offers a practical and secure solution for human genomic data analysis.
  • It effectively balances computational efficiency with data privacy requirements.
  • This approach maximizes public cloud resources while safeguarding sensitive genomic information.