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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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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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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Human Genetics01:28

Human Genetics

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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
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Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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Related Experiment Video

Updated: Aug 19, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

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COVID-19 detection and classification for machine learning methods using human genomic data.

Mohd Thousif Ahemad1, Mohd Abdul Hameed1, Ramdas Vankdothu1

  • 1Department of Computer Science and Engineering, Osmania University Hyderabad, India.

Measurement. Sensors
|December 5, 2022
PubMed
Summary
This summary is machine-generated.

Machine learning aids in identifying coronavirus disease (COVID-19) from CT lung scans. This automated approach assists in early detection and classification, improving upon manual diagnosis methods.

Keywords:
ClassificationCorona virusCovid -19Human Genomic dataMachine learningPneumoniaX-rays

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Area of Science:

  • Medical Imaging
  • Machine Learning
  • Infectious Diseases

Background:

  • The COVID-19 pandemic necessitates rapid and accurate diagnostic tools.
  • Manual diagnosis of COVID-19 from lung imaging is time-consuming and labor-intensive.
  • Early detection of COVID-19 is crucial for limiting viral spread and patient exposure.

Purpose of the Study:

  • To apply machine learning for the identification and classification of COVID-19.
  • To discriminate and categorize COVID-19 in CT lung screening using computer-aided diagnosis (CAD).

Main Methods:

  • Utilized machine learning algorithms including Decision Tree, Support Vector Machine (SVM), K-means clustering, and Radial Basis Function (RBF).
  • Employed CT lung screening data and clinical samples (serum, respiratory secretions, whole blood) assessing 15 parameters.
  • Developed a four-phase CAD system involving pre-processing, segmentation (modified K-means), and classification (SVM, RBF) of ground-glass opacities (GGOs).

Main Results:

  • The study demonstrates the application of machine learning for COVID-19 detection in CT lung images.
  • A modified K-means technique was used for segmenting GGOs, followed by SVM and RBF for classification.
  • A graphical user interface (GUI) tool was created to assist clinicians in obtaining accurate findings.

Conclusions:

  • Machine learning offers a promising approach for automated COVID-19 diagnosis from CT scans.
  • The developed CAD system can aid in the efficient and accurate classification of COVID-19.
  • This automated diagnostic method can supplement traditional methods like RT-PCR and manual image interpretation.