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Genomics02:02

Genomics

40.9K
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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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
Although bacterial genomes are much...
48.8K
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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Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

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Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
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DNA-only Transposons02:57

DNA-only Transposons

17.6K
DNA-only transposons are called autonomous transposons since they code for the enzyme transposase that is required for the transposition mechanism. Insertion of transposons can alter gene functions in multiple ways. They can mutate the gene, alter gene expression by introducing a novel promoter or insulator sequence, introduce new splice sites, and change the mRNA transcripts produced, or remodel chromatin structure.
The donor site from where the transposon is excised is either degraded or...
17.6K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

37.3K
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.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
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Related Experiment Video

Updated: Feb 15, 2026

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

24.1K

Genomic signal processing for DNA sequence clustering.

Gerardo Mendizabal-Ruiz1, Israel Román-Godínez1, Sulema Torres-Ramos1

  • 1Departamento de Ciencias Computacionales, Universidad de Guadalajara, Guadalajara, Mexico.

Peerj
|January 31, 2018
PubMed
Summary
This summary is machine-generated.

Genomic signal processing (GSP) methods enable DNA data analysis. This study introduces a novel GSP-based K-means clustering and visualization approach for DNA sequence analysis.

Keywords:
COX1DNAGenomic signal processingK-meansSequence clustering

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Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
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Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomic Data Analysis

Background:

  • Genomic signal processing (GSP) offers novel ways to analyze DNA data.
  • Cluster analysis is crucial for identifying patterns in biological datasets.
  • Existing methods may not fully exploit the potential of GSP for DNA sequence exploration.

Purpose of the Study:

  • To introduce a new method for DNA sequence cluster analysis using GSP.
  • To integrate the K-means algorithm with GSP for genomic data.
  • To develop a visualization technique for analyzing clustering results.

Main Methods:

  • Genomic signal processing (GSP) to convert DNA sequences into numerical representations.
  • K-means clustering algorithm applied to the numerical genomic data.
  • Development of a novel visualization method for interpreting cluster analysis outcomes.

Main Results:

  • Demonstrated the feasibility of using GSP with K-means for DNA sequence clustering.
  • Successfully visualized the results, aiding in the identification of hidden patterns.
  • The proposed method effectively identifies interesting features within DNA datasets.

Conclusions:

  • The proposed GSP-based K-means clustering and visualization method is effective for DNA sequence analysis.
  • This approach facilitates the discovery and interpretation of genomic data features.
  • It opens avenues for applying advanced signal processing techniques in genomics.